Downloads: A PDF of this resource will be available soon.
Related INCOSE Competencies: Toolkit resources are designed to be applicable to any engineering discipline, but educators might find it useful to understand their alignment to competencies outlined by the International Council on Systems Engineering (INCOSE). The INCOSE Competency Framework provides a set of 37 competencies for Systems Engineering within a tailorable framework that provides guidance for practitioners and stakeholders to identify knowledge, skills, abilities and behaviours crucial to Systems Engineering effectiveness. A free spreadsheet version of the framework can be downloaded.
This resource relates to the Systems Thinking, Systems Modelling and Analysis, Configuration Management, Requirements Definition, Communication, Verification, and Validation INCOSE Competencies.
AHEP4 mapping: This resource addresses several of the themes from the UK’s Accreditation of Higher Education Programmes fourth edition (AHEP4):Analytical Tools and Techniques (critical to the ability to model and solve problems), and Integrated / Systems Approach (essential to the solution of broadly-defined problems). In addition, this resource addresses the themes of Sustainability and Communication.
Educational level: Advanced.
Learning and teaching notes:
Overview:
This multi-part case study guides students through the complex systems challenges of Prince Edward Island, Canada’s ambitious 100% renewable energy transition by 2030. Students will experience how technical, social, and economic factors interact through emergence, feedback loops, and multi-scale dynamics that traditional engineering analysis alone cannot capture.
Learners have the opportunity to:
Identify complex systems characteristics (emergence, feedback loops, nonlinearity) in real energy systems.
Apply multiple modelling approaches (ABM, system dynamics, network analysis) to analyse system behaviour.
Evaluate how technical decisions create emergent social and economic consequences.
Synthesise insights from different modelling approaches to inform policy recommendations.
Communicate complex systems concepts and uncertainties to non-technical stakeholders.
Teachers have the opportunity to:
Demonstrate complex systems concepts through hands-on modelling.
Facilitate discussions on emergence and system-level behaviours.
Evaluate learners’ ability to apply systems thinking to engineering problems.
Connect technical modelling to real-world policy and social implications.
Overview: Energy transition as a complex systems challenge:
Prince Edward Island (PEI), Canada’s smallest province, aims to achieve 100% renewable electricity by 2030. Its small grid, dependence on imported power, and growing renewable infrastructure make it a natural laboratory for systems thinking in energy transitions.
This case invites students to explore how technical, social, and policy decisions interact to shape renewable integration outcomes. Using complexity-science tools, they will uncover how local actions produce emergent system behaviour, and why traditional linear models often fail to predict real-world dynamics.
The complex challenge: Traditional engineering approaches often treat energy systems as predictable and linear, optimising components like generation, transmission, or storage in isolation. However, energy transitions are complex socio-technical systems, characterised by feedback loops, interdependencies, and emergent behaviours.
In PEI’s case, replacing stable baseload imports with variable wind and solar generation creates cascading effects on grid stability, pricing, storage demand, and social acceptance. The island’s bounded geography magnifies these interactions, making it an ideal context to observe emergence and system-level behaviour arising from local interactions.
PEI currently imports about 75% of its electricity via two 180 MW submarine cables, while 25% is produced locally through onshore wind farms (204 MW). Plans for offshore wind, community solar, and hydrogen projects have triggered debates around stability, affordability, and social acceptance.
Taking on the role of an engineer at TechnoGrid Consulting, students are tasked to advise Maritime Electric, the island’s utility, on modelling strategies to guide $2.5 billion in renewable investments.
Competing goals:
Maintain grid reliability while replacing fossil baseloads.
Achieve policy targets without increasing public resistance.
Balance economic cost, environmental benefit, and technological feasibility.
Discussion prompt:
In systems terms, where do you see tensions between policy, technology, and society? How might feedback loops amplify or mitigate these tensions?
While Maritime Electric’s engineering team insists the project scope should stay strictly technical, limited to grid hardware, generation, and storage, policy advisors argue that social behaviour, market pricing, and community engagement are part of the system’s real dynamics.
Expanding boundaries makes the model richer but harder to manage; narrowing them simplifies computation but risks missing the very factors that determine success.
Temporal boundaries: timescales from milliseconds (grid response) to decades (infrastructure).
Organisational boundaries: stakeholders, regulations, and markets.
Discuss how including or excluding elements (e.g., electric-vehicle uptake, community cooperatives, carbon policy) changes the model’s focus and meaning.
Learning insight:
Complex systems cannot be fully understood in isolation; boundaries are analytical choices that shape both perception and leverage. Every inclusion or exclusion reflects an assumption about what matters and that assumption determines which complexities emerge, and which stay hidden.
Part three: Modelling the system: Multiple lenses of complexity:
(a) Agent-Based Modelling (ABM) with NetLogo:
Students construct simplified models of households, businesses, and grid operators:
Household agents: decide to adopt rooftop solar based on payback time and neighbour influence.
Technology providers: adjust prices in response to market demand.
Grid operator: balances reliability and cost.
Emergent patterns such as adoption S-curves or network clustering illustrate how simple local rules generate complex collective dynamics.
(b) System Dynamics (SD) with Vensim:
Students then develop causal loop diagrams capturing key feedbacks:
Adoption–Learning Loop: installations ↓ costs ↓ encourage more adoption.
Cost–Acceptance Loop: higher bills ↓ public support ↓ investment capacity.
This provides a macroscopic view of feedback, delay, and leverage points.
(c) Network Analysis with Python (NetworkX):
Students model actor interdependencies: how households, utilities, industries, and regulators interact. Network metrics (centrality, clustering, connectivity) reveal where resilience or vulnerability is concentrated.
Reflection prompt:
Which modelling approach offered the most insight into system-level behaviour? What were the trade-offs in complexity and interpretability?
Part four: Scenario exploration: Pathways to 2030:
Students explore three transition scenarios, each with distinct emergent behaviours:
A. Distributed Solar + Community Storage
300 MW solar, 150 MWh batteries
Decentralised coordination challenges and social clustering effects.
B. Offshore Wind + Grid Enhancement
400 MW offshore wind, new 300 MW interconnection
Weather-dependent reliability and cross-border dependency.
Any views, thoughts, and opinions expressed herein are solely that of the author(s) and do not necessarily reflect the views, opinions, policies, or position of the Engineering Professors’ Council or the Toolkit sponsors and supporters.
Who is this article for?: Thisarticle should be read by educators at all levels in higher education who are seeking an overall perspective on teaching approaches for integrating complex systems in engineering education.
Related INCOSE Competencies: Toolkit resources are designed to be applicable to any engineering discipline, but educators might find it useful to understand their alignment to competencies outlined by the International Council on Systems Engineering (INCOSE). The INCOSE Competency Framework provides a set of 37 competencies for Systems Engineering within a tailorable framework that provides guidance for practitioners and stakeholders to identify knowledge, skills, abilities and behaviours crucial to Systems Engineering effectiveness. A free spreadsheet version of the framework can be downloaded.
This resource relates to the Systems Thinking and Critical Thinking INCOSE competencies.
AHEP mapping: This resource addresses several of the themes from the UK’s Accreditation of Higher Education Programmes fourth edition (AHEP4): Analytical Tools and Techniques (critical to the ability to model and solve problems), and Integrated / Systems Approach (essential to the solution of broadly-defined problems).
Premise:
This document aims to provide definitions of key terms regarding engineered complex systems.
There are many existing relevant glossaries (for example, the Systems Engineering Body of Knowledge or SEBoK) so we have implemented a process to select a curated list of 14 common terms that are fundamental when considering the idea of complexity in engineered solutions, and therefore of importance to educators in this space. Rather than adding new definitions for each term we offer appropriate and accessible definitions from the literature, together with commentary exploring wider context and consideration where relevant.
Approach:
Some care is needed when using any definition around terms relating to complexity – because complexity itself is complex. There are multiple valid perspectives and so any one definition is unlikely to capture the totality of nuance and satisfy the variety of viewpoints. The process for selecting these terms involved collating an initial long list for potential inclusion, along with the ways in which each has been previously defined. These are provided as a supplementary annex to the main glossary. The method is further described in the following sub-section.
An initial list of potential terms to define was generated by cross-referencing existing glossaries. Terms that occurred in multiple glossaries were included in the long list. The definitions of these terms were extracted from these existing glossaries and are cited in the references. In addition, the relationship to the INCOSE Competencies is shown. The range of potential terms, and the variety of definitions that already exist, illustrate the complexity of describing complexity!
The authors used three categorisations of the definitions to help further group and classify the terms. The following categories are tagged to relevant terms in the glossary:
1. Property – whether or not the term describes a property applied to systems;
2. Principle – whether or not the term represents a principle that should be used when engineering complex situations or systems;
3. Approach – whether or not the term represents an approach, or element of an approach that should / could be used when engineering complex situations or systems.
Finally, explanatory commentary was added to most definitions to more specifically address an engineering education context.
Glossary:
Architecture
Definition: “an abstract description of the entities of a system and the relationship between those entities.” Crawley et al. (2016) System Architecture: Strategy & Product Development for Complex Systems
Boundary
#Property #Principle
Definition: “Define the system to be addressed. A description of the boundary of the system can include the following: definition of internal and external elements/items involved in realizing the system purpose as well as the system boundaries in terms of space, time, physical, and operational. Also, identification of what initiates the transitions of the system to operational status and what initiates its disposal is important.” NASA (2007) NASA Systems Engineering Handbook, p304
Commentary: The boundary defines the scope of the system being considered, and by implication, what sits outside of the system. As such, it is critically important to define the boundary of the system-of-interest. When dealing with complex systems this can be a challenging task and may even benefit from acknowledging multiple boundaries (e.g. physical, spatial, functional, logical etc.). For example, the boundary of the physical elements of a system could be considered within a wider boundary of the problem space.
Complexity
#Property
Definition: “A complex system is a system in which there are non-trivial relationships between cause and effect: each effect may be due to multiple causes; each cause may contribute to multiple effects; causes and effects may be related as feedback loops, both positive and negative; and cause-effect chains are cyclic and highly entangled rather than linear and separable.” INCOSE (2019) INCOSE Systems Engineering and Systems Definitions
Commentary: Early conceptions of complexity emphasised the difficulty in understanding, predicting or verifying the behaviours of a system. A key distinction arising from this is the complicated and complex are not synonymous. This concept of the difficulty in predicting behaviours is reflected in the definitions of the NASA Systems Engineering Handbook, SEBoK and ISO 24765. This is the key resultant consideration but does not describe the underlying property which causes this difficulty. While this definition relates more to complex systems than complexity, it is chosen for the way in which it goes beyond the consequences of complexity.
Coupling
#Property #Principle
Definition: “Coupling […] means to fasten together, or simply to connect things […] Coupling suggests a relationship between connected entities. If they are coupled, in some way they can affect each other […] For the system to be useful, its components have to be connected – coupled – so that they can work together. That said, putting them together arbitrarily won’t do the trick. The components have to be coupled in a way that achieves the goals of the system. Not only is coupling the glue that holds a system together, but it also makes the value of the system higher than the sum of its parts.” Khononov (2024) Balancing Coupling in Software Design: Universal Design Principles for Architecting Modular Software Systems, Ch1
Commentary: Coupling is a very important concept. It is the interconnection and interdependence that makes the system more (or less) than the sum of its parts. Standard Systems architecture advice is to minimise coupling between system elements (or between the systems in a system-of-systems). This is because high coupling correlates to higher structural complexity, reduced resilience and flexibility in the system, and introduces challenges for modularity in the system design. Lower or looser coupling means changes in one part of the system (in design or operation) are less likely to induce or require changes in another part. However, this lower coupling is not always possible and may be necessary to improve system performance (for example communication through intermediate layers in a system to reduce coupling can introduce unacceptable amounts of overhead and latency in the system). In design terms, high coupling between system elements means that those elements cannot be designed independently.
Emergence
#Principle
Definition: “As the entities of a system are brought together, their interaction will cause function, behaviour, performance and other intrinsic (anticipated and unanticipated) properties to emerge… Emergence refers to what appears, materializes, or surfaces when a system operates.” Crawley et al. (2016) System Architecture: Strategy & Product Development for Complex Systems
Commentary: It is worth noting that Crawley et al. (2014) go on to add “As a consequence of emergence, change propagates in unpredictable ways. System success occurs when anticipated emergence occurs, while system failure occurs when anticipated emergent properties fail to appear or when unanticipated undesirable emergent properties appear.” This emergence that gives rise to the difficulty in understanding, predicting or verifying the behaviours of a system (see Complexity).
Form
#Property
Definition: “The shape, size, dimensions, mass, weight, and other measurable parameters which uniquely characterize an item.” SAE International (2019) ANSI/EIA-649C
Function
#Principle #Approach
Definition: “A function is defined as the transformation of input flows, with defined performance targets for how well the function is performed in different conditions. A function usually has logical pre-conditions that trigger its operation. ”Systems Engineering Body of Knowledge v2.12 (2025)
Commentary: In general usage it is common to hear reference to ‘Form and Function’ in tandem, but it is the distinction between them and their relationship to one another that is important to engineering complex systems. Thinking in terms of functionality is a good way of abstracting the system to define what it does (or is needed to do) rather than what it is (and therefore by extension its form). Functions are normally allocated to single sub-elements of the system. Complexity arises at functional interfaces, or when different elements perform the same function. Thinking in terms of functionality encourages creativity as designers consider all the different ways in which the function could be performed – and then apply requirement constraints to choose the best/most feasible option. Thinking in terms of “objects” first constrains design by presupposing the solutions. Equally, when the solution goes wrong, thinking in terms of what function is failing and why, rather than focusing on a failed part allows identification of the true root cause. Organisations also have functions (such as Engineering, Human Resources, etc.) as a group of roles that perform a specific set of activities. This is important for considering the organisation/System that creates the engineered solution (which is itself a complex system, but secondary to the main application of the idea of function).
Iteration
#Approach
Definition: “Iteration is used as a generic term for successive application of a systems approach to the same problem situation, learning from each application, in order to progress towards greater stakeholder satisfaction.” Systems Engineering Body of Knowledge v2.12 (2025)
Lifecycle
#Property #Principle #Approach
Definition: “The evolution of a system, product, service, project or other human-made entity from conception through retirement.” ISO (2024) ISO/IEC/IEEE 24748-1:2024
Commentary: Understanding the lifecycle of an engineered artefact is very important. Issues arising in later stages (e.g. production, support/maintenance, upgrade and disposal) must be considered during the system’s initial development. In a system-of-systems or a capability system a significant source of complexity is the fact that different system elements have different lifecycles, and so may change or be changed independently of other elements with which they may interact or interdepend.
Model
#Approach
Definition: “An abstraction of a system, aimed at understanding, communicating, explaining, or designing aspects of interest of that system” Dori, D. (2003) Conceptual modelling and system architecting, p286
Commentary: An abstraction is a simplification. The selection of what to exclude, what to include, and at what level of granularity to depict it, is informed by the purpose of the model and the point of view from which it is created. Models do not have to be quantitative, nor is their purpose exclusively analytical.
Stakeholder
Definition: “A group or individual who is affected by or has an interest or stake in a program or project.” NASA (2019) NASA Systems Engineering Handbook SP-2016-6105 (Rev. 2)
Commentary: It is worth noting the potential difference between a stakeholder of the project that develops the system, and a stakeholder of the system that is developed.
System
#Principle #Approach
Definition: “A system is an arrangement of parts or elements that together exhibit behaviour or meaning that the individual constituents do not.” INCOSE (2019) INCOSE Fellows Briefing to INCOSE Board of Directors, January 2019
Commentary: There are many similar definitions of a system, each may offer a slightly different phrasing which can resonate better with different individuals. The origins of this definition is explained in the Systems Engineering Body of Knowledge. In assessing complexity in engineered system, the concept of “systems” is of course of key value. There are two important aspects two consider:
1) Many schools of Systems Science argue that systems do not actually exist (apart from perhaps the complete universe) – they are defined for the convenience of consideration, and so the definition of the boundary of the “system of interest” is both important and somewhat arbitrary. As such, the system-of-interest can have multiple useful boundaries. While it might be possible to identify and articulate the physical boundary of an engineered artefact (and it should be acknowledged), it might not be the most useful boundary to consider.
2) The point of defining a “system of interest” includes being able to consider it as a system and so use the properties seen in systems (boundary, interface with outside, affected by/affecting environment, made up of parts, part of something larger, has a lifecycle, seen differently by different people (with different perspectives), are dynamic, exhibit emergence etc.) as a “framework for curiosity” (as the INCOSE SE competency framework defines systems thinking).
In engineered systems (rather than natural systems) it is important to distinguish between purpose (what those engineering or creating it want it do) and emergence (what it actually does).
Systems Engineering
#Principle #Approach
Definition: “Systems Engineering is a transdisciplinary and integrative approach to enable the successful realization, use, and retirement of engineered systems, using systems principles and concepts, and scientific, technological, and management methods.” INCOSE (2019) INCOSE Systems Engineering and Systems Definitions
Systems Thinking
#Approach
Definition: “Systems thinking is thinking about a question, circumstance, or problem explicitly as a system – a set of interrelated entities.” Crawley et al. (2016) System Architecture: Strategy & Product Development for Complex Systems
Commentary: Crawley et al (2016) go on to add “This means identifying the system, its form and function, by identifying its entities and their interrelationships, its system boundary and context, and the emergent properties of the system based on the function of the entities, and their functional interactions.”
References:
Crawley, E. Cameron, B. & Selva, D. (2016). System Architecture: Strategy & Product Development for Complex Systems, Pearson
Dori, D. (2003). “Conceptual modeling and system architecting.” Communications of the ACM, 46(10), pp. 62-65.
ISO (2024). Systems and software engineering — Life cycle management -ISO/IEC/IEEE 24748-1:2024
Khononov, V. (2024). Balancing Coupling in Software Design: Universal Design Principles for Architecting Modular Software Systems, Addison-Wesley Professional,
NASA. (2007). Systems Engineering Handbook – Revision 1. Washington, DC, USA: National Aeronautics and Space Administration (NASA). NASA/SP-2007-6105.
NASA (2016). Systems Engineering Handbook – Revision 2. Washington, DC, USA, National Aeronautics and Space Administration (NASA). NASA/SP-2016-6105 (Rev. 2)
SAE International (2019). National Consensus Standard for Configuration Management -ANSI/EIA-649C
Any views, thoughts, and opinions expressed herein are solely that of the author(s) and do not necessarily reflect the views, opinions, policies, or position of the Engineering Professors’ Council or the Toolkit sponsors and supporters.
Licensing:This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. It is based upon the author’s 2025 article “A Simulation Tool for Pinch Analysis and Heat Exchanger/Heat Pump Integration in Industrial Processes: Development and Application in Challenge-based Learning”. Education for Chemical Engineers 52, 141–150.
Related INCOSE Competencies: Toolkit resources are designed to be applicable to any engineering discipline, but educators might find it useful to understand their alignment to competencies outlined by the International Council on Systems Engineering (INCOSE). The INCOSE Competency Framework provides a set of 37 competencies for Systems Engineering within a tailorable framework that provides guidance for practitioners and stakeholders to identify knowledge, skills, abilities and behaviours crucial to Systems Engineering effectiveness. A free spreadsheet version of the framework can be downloaded.
This resource relates to the Systems Thinking, Systems Modelling and Analysis and Critical Thinking INCOSE competencies.
AHEP mapping: This resource addresses several of the themes from the UK’s Accreditation of Higher Education Programmes fourth edition (AHEP4): Analytical Tools and Techniques (critical to the ability to model and solve problems), and Integrated / Systems Approach (essential to the solution of broadly-defined problems). In addition, this resource addresses the themes of Science, mathematics and engineering principles; Problem analysis; and Design.
Educational level: Intermediate.
Educational aim:To equip learners with the ability to model, analyse, and optimise pathways for industrial decarbonisation through a complex-systems lens – integrating technical, economic, and policy dimensions – while linking factory-level design decisions to wider value-chain dynamics, multi-stakeholder trade-offs, and long-term sustainability impacts.
Learning and teaching notes:
This teaching activity explores heat integration for the decarbonisation of industrial processes through the lens of complex systems thinking, combining simulation, systems-level modelling, and reflective scenario analysis. It is especially useful in modules related to energy systems, process systems, or sustainability.
Learners analyse a manufacturing site’s energy system using a custom-built simulation tool to explore the energy, cost and carbon-emission trade-offs of different heat-integration strategies. They also reflect on system feedback, stakeholder interests and real-world resilience using causal loop diagrams and role-played decision frameworks.
This activity frames industrial heat integration as a complex adaptive system, with interdependent subsystems such as process material streams, utilities, technology investments and deployments, capital costs, emissions, and operating constraints.
Learners run the simulation tool to generate outputs to explore different systems integration strategies: pinch-based heat recovery by heat exchangers, with and without heat pump-based waste heat upgrade. Screenshots of the tool graphical user interface are attached as separate files:
The learning is delivered in part, through active engagement with the simulation tool. Learners interpret the composite and grand composite curves and process tables, to explore how system-level outcomes change across various scenarios. Learners explore, using their generated simulation outputs, how subsystems (e.g. hot and cold process streams, utilities) interact nonlinearly and with feedback effects (e.g., heat recovery impacts), shaping global system behaviour and revealing leverage points and emergent effects in economics, emissions and feasibility.
Using these outputs as a baseline, and exploring other systems modelling options, learners evaluate trade-offs between heat recovery, capital expenditure (CAPEX), operating costs (OPEX), and carbon emissions, helping them develop systems-level thinking under constraints.
The activity embeds scenario analysis, including causal loop diagrams, what-if disruption modelling, and stakeholder role-play, using multi-criteria decision analysis (MCDA) to develop strategic analysis and systems mapping skills. Interdisciplinary reasoning is encouraged across thermodynamics, economics, optimisation, engineering ethics, and climate policy, culminating in reflective thinking on system boundary definitions, trade-offs, sustainability transitions and resilience in industrial systems.
Learners have the opportunity to:
Analyse non-linear interactions in thermodynamic systems.
Reconcile conflicting demands (e.g. energy savings vs costs vs emissions vs technical feasibility) using data generated from real system simulation.
Model and interpret feedback-driven process systems using pinch analysis, heat recovery via heat exchangers, and heat upgrade via heat pump integration.
Explore emergent behaviour, trade-offs, and interdisciplinary constraints.
Navigate system uncertainties by simulation data analysis and scenario thinking.
Understand the principles of heat integration using pinch analysis, heat exchanger networks, and heat pump systems, framed within complex industrial systems with interdependent subsystems.
Evaluate decarbonisation strategies and their performances in terms of energy savings, CAPEX/OPEX, carbon reduction, and operational risks, highlighting system-level trade-offs and nonlinear effects
Develop data-driven decision-making, navigating assumptions, parameter sensitivity, and model limitations, reflecting uncertainty and systems adaptation.
Explore ethical, sustainability, and resilience dimensions of engineering design, recognising how small changes or policy shifts may act on leverage points and produce emergent behaviours.
Analyse stakeholder dynamics, policy impacts, and uncertainty as part of the broader system environment influencing energy transition pathways.
Construct and interpret causal loop diagrams (CLDs), explore what-if scenarios, and apply multi-criteria decision analysis (MCDA), building competencies in feedback loops, system boundaries, and systems mapping.
Teachers have the opportunity to:
Embed systems thinking and complex systems pedagogy into energy and process engineering, using real-world simulations and data-rich problem-solving.
Introduce modelling and scenario-based reasoning, helping students understand how interactions between process units, energy streams, and external factors affect industrial decarbonisation.
Facilitate exploration of design trade-offs, encouraging learners to consider technical feasibility, economic sustainability, and environmental constraints within dynamic system contexts.
Support students in identifying leverage points, feedback loops, and emergent behaviours, using tools like CLDs, composite curves, and stakeholder role play.
Assess complex problem-solving capacity, including students’ ability to model, critique and adapt industrial systems under conflicting constraints and uncertain futures.
Proprietary Simulator for Pinch Analysis & Heat Integration. Freely available for educational use and can be accessed online through a secure link provided by the author on request (james.atuonwu@nmite.ac.uk or james.atuonwu@gmail.com). No installation or special setup is required; users can access it directly in a web browser.
About the simulation tool (access and alternatives):
This activity uses a Streamlit-based simulation tool, supported with process data (Appendix A, Table 1, or an educator’s equivalent). The tool is freely available for educational use and can be accessed online through a secure link provided by the author on request (james.atuonwu@nmite.ac.uk or james.atuonwu@gmail.com). No installation or special setup is required; users can access it directly in a web browser.The activity can also be replicated using open-source or online pinch analysis tools such as OpenPinch, PyPinchPinCH, TLK-Energy Pinch Analysis Online. SankeyMATIC can be used for visualising energy balances and Sankey diagrams.
Pinch Analysis, a systematic method for identifying heat recovery opportunities by analysing process energy flows, forms the backbone of the simulation. A brief explainer and further reading are provided in the resources section. Learners are assumed to have prior or guided exposure to its core principles. A key tunable parameter in Pinch Analysis, ΔTmin, represents the minimum temperature difference allowed between hot and cold process streams. It determines the required heat exchanger area, associated capital cost, controllability, and overall system performance. The teaching activity helps students explore these relationships dynamically through guided variation of ΔTmin in simulation, reflection, and trade-off analysis, as outlined below.
Introducing and prioritising ΔTmin trade-offs:
ΔTmin is introduced early in the activity as a critical decision variable that balances heat recovery potential against capital cost, controllability, and safety. Students are guided to vary ΔTmin within the simulation tool to observe how small parameter shifts affect utility demands, exchanger area, and overall system efficiency. This provides immediate visual feedback through the composite and grand composite curves, helping them connect technical choices to system performance.
Educators facilitate short debriefs using the discussion prompts in Part 1 and simulation-based sensitivity analysis in Part 2. Students compare low and high ΔTmin scenarios, reasoning about implications for process economics, operability, and energy resilience.
This experiential sequence allows learners to prioritise competing factors (technical, economic, and operational), while recognising that small changes can create non-linear, system-wide effects. It reinforces complex systems principles such as feedback loops and leverage points that govern industrial energy behaviour.
Data for decisions:
The simulator’s sidebar includes some default values for energy prices (e.g. gas and electricity tariffs) and emission factors (e.g. grid carbon intensity), which users can edit to reflect their own local or regional conditions. For those replicating the activity with other software tools, equivalent calculations of total energy costs, carbon emissions and all savings due to heat recovery investments can be performed manually using locally relevant tariffs and emission factors.
The Part 1–3 tasks, prompts, and assessment suggestions below remain fully valid regardless of the chosen platform, ensuring flexibility and accessibility across different teaching contexts.
Educator support and implementation notes:
The activity is designed to be delivered across 3 sessions (6–7.5 hours total), with flexibility to adapt based on depth of exploration, simulation familiarity, or group size. Each part can be run as a standalone module or integrated sequentially in a capstone-style format.
Part 1: System mapping: (Time: 2 to 2.5 hours) – Ideal for a classroom session with blended instruction and group collaboration:
This stage introduces students to the foundational step of any heat integration analysis: system mapping. The aim is to identify and represent energy-carrying streams in a process plant, laying the groundwork for further system analysis. Educators may use the Process Flow Diagram of Fig. 1, Appendix A (from a real industrial setting: a food processing plant) or another Process Diagram, real or fictional. Students shall extract and identify thermal energy streams (hot/cold) within the system boundary and map energy balances before engaging with software to produce required simulation outputs.
Key activities and concepts include:
Defining system boundaries: Focus solely on thermal energy streams, ignoring non-thermal operations. The boundary is drawn from heat sources (hot streams) to heat sinks (cold streams).
Identifying hot and cold streams: Students classify process material streams based on whether they release or require heat. Each stream is defined by its inlet and target temperatures and its heat capacity flow rate (CP).
Building the stream table: Students compile a simple table of hot/cold streams (name, supply temperature, target temperature and heat capacity flow CP).
Constructing energy balances and Sankey Diagrams: Students manually calculate energy balances across each subsystem in the defined system boundary, identifying energy inputs, useful heat recovery, and losses. Using this information, they construct Sankey diagrams to visualise the magnitude and direction of energy flows, strengthening their grasp of system-wide energy performance before optimisation.
Pinch Concept introduction: Students are introduced to the concept of “the Pinch”, including the minimum heat exchanger temperature difference (ΔTmin) and how it affects heat recovery targets (QREC), as well as overall heating and cooling utility demands (QHU & QCU, respectively).
Assumptions: All analysis is conducted under steady-state conditions with constant CP and no heat losses.
Discussion prompts:
What insights does the Sankey diagram reveal about energy use, waste and recovery potential in the system? How might these visual insights shape optimisation decisions?
Why might certain streams be excluded from the analysis?
How does the choice of ΔTmin influence the heat recovery potential and cost?
What trade-offs are involved in system simplification during mapping?
How can assumptions (like steady-state vs. transient) impact integration outcomes?
Student deliverables:
A labelled system map showing the thermal process boundaries, hot and cold streams.
A structured stream data table.
Justification for selected ΔTmin values based on process safety, economics, or practical design and operational considerations.
A basic Sankey diagram representing the energy flows in the mapped system, based on calculated heat duties of each stream.
Part 2: Running and interpreting process system simulation results (Time: 2 to 2.5 hours) – Suitable for lab or flipped delivery;only standard computer access is needed to run the tool (optional instructor demo can extend depth):
Students use the simulation tool to generate their own results.The process scenario of Fig. 1, Appendix A, with the associated stream data (Table 1) can be used as a baseline.
Tool-generated outputs:
Curves: Composite and Grand Composite (pinch location, recovery potential).
Scenario summary: QREC, QHU, QCU; COP (where applicable); CAPEX/OPEX/CO₂; payback period for various values of system levers (e.g., ΔTmin levels, tariffs, emission factors).
Heat Pump (HP) tables: Feasible pairs, Top-N heat pump selections (where N = 0, 1, or 2); QEVAP, QCOND, QCOMP, COP. All notations are designated in the simulator’s help/README section.
Learning tasks:
1. Scenario sweeps Run different scenarios (e.g., different ΔTmin levels, tariffs, emission factors, and Top-N HP selections). Prompts: How do QREC, QHU/QCU, HX area, and CAPEX/OPEX/CO₂ shift across scenarios? Which lever moves the needle most?
2. Group contrast (cases A vs B: see time-phased operations A & B in Appendix A) Assign groups different cases; each reports system behaviours and trade-offs. Prompts: Where do you see CAPEX vs. energy-recovery tension? Which case is more HP-friendly and why?
3. Curve reading Use the Composite & Grand Composite Curves to identify pinch points and bottlenecks; link features on the curves to the tabulated results. Prompts: Where is the pinch? How does ΔTmin change the heat-recovery target and utility demands?
4. Downstream implications Trace how curve-level insights show up in HX sizing/costs and HP options. Prompts: When does adding HP reduce utilities vs. just shifting costs? Where do stream temperatures/CP constrain integration?
5. Systems lens: feedback and leverage Map short causal chains from the results (e.g., tariffs → HP use → electricity cost → OPEX; grid-carbon → HP emissions → net CO₂). Prompts: Which levers (ΔTmin, tariffs, EFs, Top-N) create reinforcing or balancing effects?
Outcome:
Students will be able to generate and interpret industrial simulation outputs, linking technical findings to economic and emissions consequences through a systems-thinking lens. They begin by tracing simple cause–effect chains from the simulation data and progressively translate these into causal loop diagrams (CLDs) that visualise reinforcing and balancing feedback. Through this, learners develop the ability to explain how system structure drives performance both within the plant and across its broader industrial and policy environment.
Optional extension: Educators may provide 2–3 predefined subsystem options (e.g., low-CAPEX HX network, high-COP HP integration, hybrid retrofit) for comparison. Students can use a decision matrix to justify their chosen configuration against CAPEX, OPEX, emissions, and controllability trade-offs.
Part 3: Systems thinking through scenario analysis (Time: 2 to 2.5 hours) – Benefits from larger-group facilitation, a whiteboard or Miro board (optional), and open discussion. It is rich in systems pedagogy:
Having completed simulation-based pinch analysis and heat recovery planning, learners now shift focus to strategic implementation challenges faced in real-world industrial settings. In this part, students apply systems thinking to explore the broader implications of their heat integration simulation output scenarios, moving beyond process optimisation to consider real-world dynamics, trade-offs, and stakeholder interactions. The goal is to encourage students to interrogate the interconnectedness of decisions, feedback loops, and unintended consequences in process energy systems including but not limited to operational complexity, resilience to disruptions, and alignment with long-term sustainability goals.
Activity: Stakeholder role play / Multi-Criteria Decision Analysis Students take on stakeholder roles and debate which design variant or operating strategy should be prioritised. They then conduct a Multi-Criteria Decision Analysis (MCDA), evaluating each option based on criteria such as CAPEX, OPEX savings, emissions reductions, risk, and operational ease.
Stakeholders include:
Operations managers, focused on ease of control and process stability.
Investors and finance teams, focused on return on investment.
Environmental officers, concerned with emissions and policy compliance.
Engineers, responsible for design and retrofitting.
Community members, advocating for sustainable industry practices.
Government reps responsible for regulations and policy formulation, e.g. taxes and subsides.
The team must present a strategic analysis showing how the heat recovery system behaves as a complex adaptive system, and how its implementation can be optimised to balance technical, financial, environmental, and human considerations.
Optional STOP for questions and activities:
Before constructing causal loop diagrams (CLDs), learners revisit key results from their simulation — such as ΔTmin, tariffs, emission factors, and system costs — and trace how these parameters interact to influence overall system performance. Educators guide this transition, helping students abstract quantitative outputs (e.g., changes in QREC, OPEX, or CO₂) into qualitative feedback relationships that reveal cause-and-effect chains. This scaffolding helps bridge the gap between process simulation and systems-thinking representation, supporting discovery of reinforcing and balancing feedback structures.
Activity: Construct a causal loop diagram (CLD) Students identify at least five variables that interact dynamically in the implementation of a heat integration system (e.g. energy cost, investment risk, emissions savings, system complexity, staff training). They must map reinforcing and balancing feedback loops that illustrate trade-offs or virtuous cycles.
Where could policy or process changes trigger leverage points?
How could delays in response (e.g. slow staff adaptation to new technologies) affect outcomes?
How might design choices affect local energy equity, air quality, or community outcomes?
What policy incentives or ethical trade-offs might reinforce or hinder your proposed solution?
Instructor debrief (engineering context with simulation linkage): After students share their CLDs, the educator facilitates a short discussion linking their identified reinforcing and balancing loops to common dynamic patterns observable in the simulation results. For instance:
Limits to growth: As ΔTmin decreases, heat recovery (QREC) initially improves, but exchanger area, CAPEX, and controllability demands grow disproportionately — diminishing overall economic benefit.
Shifting the burden: Installing a heat pump may appear to improve carbon performance, but if low process efficiency remains unaddressed, electricity use and OPEX rise — creating a new dependency that shifts rather than solves the problem.
Tragedy of the commons: Competing units or stakeholders optimising locally (e.g. for their own OPEX or production uptime) can undermine total system efficiency or resilience.
Success to the successful: Design options with early financial or policy support (e.g. high-COP heat pumps) attract more investment and attention, reinforcing a positive but unequal feedback loop.
This reflection connects quantitative model outputs (e.g. QREC, OPEX, CAPEX, emissions) to qualitative system behaviours, helping learners recognise leverage points and understand how design choices interact across technical, economic, and social dimensions of decarbonisation.
Activity: Explore “What if?” scenarios
Working in groups, students choose one scenario to explore using a systems lens:
What if gas prices fluctuate drastically?
What if capital funding is delayed by 6 months?
What if a heat exchanger fouls during peak season?
What if CO₂ emissions policy tightens?
What if current electricity grid decarbonisation trends suffer an unexpected setback?
What if government policies now encourage onsite renewable electricity generation?
Each group evaluates the resilience and flexibility of the proposed integration design. They consider:
System bottlenecks and fragilities.
Leverage points for intervention.
Need for redundancy or modular design.
Educators may add advanced scenarios (e.g. carbon tax introduction, supplier failure, or project delay) to challenge students’ resilience modelling and stakeholder negotiation skills.
Stakeholder impact reflection:
To extend systems reasoning beyond the technical domain, students assess how their chosen design scenarios (e.g., low vs. high ΔTmin, with or without heat pump integration) affect each stakeholder group. For instance:
Operations managers assess control complexity, downtime risk, and maintenance implications.
Finance teams evaluate CAPEX/OPEX trade-offs and payback periods.
Environmental officers examine lifecycle emissions and regulatory compliance.
Engineers reflect on reliability, retrofit feasibility, and process safety.
Community members or regulators consider social and policy outcomes, such as visible sustainability impact or energy equity.
Each team member rates perceived benefits, risks, or compromises under each design case, and the results are summarised in a stakeholder impact matrix or discussion table. This exercise links quantitative system metrics (energy recovery, emissions, cost) to qualitative stakeholder outcomes, reinforcing the “multi-layered feedback” perspective central to complex systems analysis.
Learning Outcomes (Part 3):
By the end of this part, students will be able to:
Identify systemic interdependencies in industrial energy systems.
Analyse how feedback loops and delays influence system behaviour.
Assess the resilience of energy integration solutions under different future scenarios.
Balance multiple stakeholder objectives in complex engineering contexts.
Apply systems thinking tools to communicate complex technical scenarios to diverse stakeholder audiences.
Use systems diagrams and decision tools to support strategic analysis.
Instructor Note – Guiding CLD and archetype exploration:
Moving from numerical heat-exchange and cost data to CLD archetypes can be conceptually challenging. Instructors are encouraged to model this process by identifying at least one reinforcing loop (e.g. “energy savings → lower OPEX → more investment in recovery → further savings”) and one balancing loop (e.g. “higher capital cost → reduced investment → lower heat recovery”). Relating these loops to common system archetypes such as “Limits to Growth” or “Balancing with Delay” helps students connect engineering data to broader system dynamics and locate potential leverage points. The activity concludes with students synthesising their findings from simulation, systems mapping, and stakeholder analysis into a coherent reflection on complex system behaviour and sustainable design trade-offs.
Assessment guidance:
This assessment builds directly on the simulation and systems-thinking activities completed by students. Learners generate and interpret their own simulation outputs (or equivalent open-source pinch analysis results), using these to justify engineering and strategic decisions under uncertainty.
Assessment focuses on students’ ability to integrate quantitative analysis (energy, cost, carbon) with qualitative reasoning (feedbacks, trade-offs, stakeholder dynamics), demonstrating holistic systems understanding.
Deliverables (portfolio; individual or group):
1. Reading and interpretation of simulation outputs
Use the outputs you generate (composite & grand composite curves: HX match/area/cost tables; HP pairing/ranking; summary sheets of QHU, QCU, QREC, COP, CAPEX, OPEX, CO₂, paybacks) for a different industrial process (from the one used in the main learning activity) to:
Identify the pinch point(s) and explain what the curves imply for recovery potential and bottlenecks.
Comment on QHU/QCU/QREC and how they change across the scenarios you run (e.g., ΔTmin, tariffs, emission factors, Top-N HP selection).
Interpret trade-offs among energy, CAPEX, OPEX, emissions, using numbers reported by the simulator. No calculations beyond light arithmetic/annotation.
2. Systems mapping and scenario reasoning
A concise system boundary sketch and a simple stream table.
A Causal Loop Diagram (CLD) highlighting key feedbacks (e.g., tariffs ↔ HP use ↔ grid carbon intensity ↔ emissions/cost).
A short MCDA (transparent criteria/weights) comparing the scenario variants you test; include a brief stakeholder reflection.
3. Decision memo (max 2 pages)
Your recommended integration option under stated assumptions, with one “what-if” sensitivity (e.g., +20% electricity price, tighter CO₂ factor).
State uncertainties/assumptions and any implementation risks (operations, fouling, timing of capital).
Students should include a short reflective note addressing assumptions, feedback insights, and how their stakeholder perspective shaped their recommendation.
Appendix A: Example process scenario for teaching activity:
Sample narrative: Large-scale food processing plant with time-sliced operations
The following process scenario explains the industrial context behind the main teaching activity simulations. A large-scale food processing plant operates a milk product manufacturing line. The process, part of which is shown in Fig. 1, involves the following:
Thermal evaporation of milk feed.
Cooking operations after other ingredient mixing and formulation upstream.
Oven heating to drive off moisture and stimulate critical product attributes.
Pre-finishing operations as the product approaches packaging.
In real operations, the evaporation subprocessoccurs at different times from the cooking/separation, oven and pre-finishing operations. This means that their hot and cold process streams are not simultaneously available for direct heat exchange. For a realistic industrial pinch analysis, the process is thus split into two time slices:
Time Slice A (used for scenario Case A): Evaporation streams only.
Time Slice B (Case B): Cooking/separation, oven and pre-finishing streams only.
Separate pinch analyses are performed for each slice, using the yellow-highlighted sections of Table 1 as stream data for time slice A, and the green-highlighted sections as stream data for time slice B. Any heat recovery between slices would require thermal storage (e.g., a hot-water tank) to bridge the time gap.
Fig.1. Simplified process flowsheet of food manufacturing facility.
Note on storage and system boundaries:
Because the two sub-processes occur at different times, direct process-to-process heat exchange between their streams is not possible without thermal storage. If storage is introduced:
Production surplus heat at time slice A can be stored at high temperature (e.g., 80 °C) and later discharged to preheat time slice B cold streams.
The size of the tank depends on the portion of hot utility demand of sub-process B to be offset, the temperature swing, and the duration of the sub-process B.
Table 1. Process stream data corresponding to flowsheet of Fig. 1. Yellow-highlighted sections represent processes available at time slice A, while green-highlighted sections are processes available at time slice B.
Appendix B: Suggested marking rubric (Editable):
Adopter note: The rubric below is a suggested template. Instructors may adjust criteria language, weightings and band thresholds to align with local policies and learning outcomes. No marks depend on running software.
1) Interpretation of Simulation Outputs — 25%
A (Excellent): Reads curves/tables correctly; uses QHU/QCU/QREC, COP, CAPEX/OPEX/CO₂, payback figures accurately; draws clear, defensible trade-offs.
B (Good): Mostly accurate; links numbers to decisions with some insight.
C (Adequate): Mixed accuracy; limited or generic trade-off discussion.
D/F (Weak): Frequent misreads; cherry-picks or contradicts generated data.
2) Systems Thinking & Scenario Analysis — 30%
A: Clear CLD with at least one reinforcing and one balancing loop; leverage points identified; scenarios coherent; MCDA with explicit criteria, weights, and justified ranking; uncertainty acknowledged.
B: Reasonable CLD; scenarios sound; MCDA present with partial justification.
C: Superficial CLD; scenarios/MCDA incomplete or weakly reasoned.
D/F: Little or no systems view; scenarios/MCDA absent or not meaningful.
Atuonwu, J.C. (2025). A Simulation Tool for Pinch Analysis and Heat Exchanger/Heat Pump Integration in Industrial Processes: Development and Application in Challenge-based Learning. Education for Chemical Engineers 52, 141-150.
Oh, X.B., Rozali, N.E.M., Liew, P.Y., Klemes, J.J. (2021). Design of integrated energy- water systems using Pinch Analysis: a nexus study of energy-water-carbon emissions. Journal of Cleaner Production 322, 129092.
Rosenow, J., Arpagaus, C., Lechtenböhmer, S.,Oxenaar, S., Pusceddu, E. (2025). The heat is on: Policy solutions for industrial electrification. Energy Research & Social Science 127, 104227.
Bale, C.S.E., Varga, L., Foxon, T.J. (2015). Energy and complexity: New ways forward. Applied Energy 138, 150-159.
Atuonwu, J.C. (2025). Proprietary Simulator for Pinch Analysis & Heat Integration. Private reviewer access available on request (demo video or temporary login).
Any views, thoughts, and opinions expressed herein are solely that of the author(s) and do not necessarily reflect the views, opinions, policies, or position of the Engineering Professors’ Council or the Toolkit sponsors and supporters.
Related INCOSE Competencies: Toolkit resources are designed to be applicable to any engineering discipline, but educators might find it useful to understand their alignment to competencies outlined by the International Council on Systems Engineering (INCOSE). The INCOSE Competency Framework provides a set of 37 competencies for Systems Engineering within a tailorable framework that provides guidance for practitioners and stakeholders to identify knowledge, skills, abilities and behaviours crucial to Systems Engineering effectiveness. A free spreadsheet version of the framework can be downloaded.
This resource relates to the Systems Thinking, Requirements Definition, Communication, Design For, and Critical Thinking INCOSE Competencies.
AHEP4 mapping: This resource addresses several of the themes from the UK’s Accreditation of Higher Education Programmes fourth edition (AHEP4): Analytical Tools and Techniques (critical to the ability to model and solve problems), and Integrated / Systems Approach (essential to the solution of broadly-defined problems). In addition, this resource addresses the themes of Sustainability and Communication.
Educational level: Beginner; intermediate.
Acknowledgement:
The case study underpinning this teaching activity was developed by Prof. Kristen MacAskill (University of Cambridge). The Module was first developed and implemented in teaching by TEDI- London, led by a team of learning technologists, Ellie Bates, Laurence Chater, Pratishtha Poudel, and academic member, Rhythima Shinde. This work was carried out in collaboration with the Royal Academy of Engineering through its Engineering X programme — a global partnership that supports safer, more sustainable engineering education and practice worldwide. With critical support from Professor Kristen MacAskill and involvement of Ana Andrade and Hazel Ingham, Aisha Seif Salim. This was a collective effort involving many individuals across TEDI-London and RAEng (advisors and reviewers), and while we cannot name everyone here, we are deeply grateful for all the contributions that made this module possible.
Learning and teaching notes:
This case study introduces a structured, systems-thinking–based teaching resource. It provides educators with tools and frameworks—such as the Cynefin framework and stakeholder mapping—to analyse and interpret complex socio-technical challenges. By exploring the case of the Queensland, Australia floods, it demonstrates how engineering decisions evolve within interconnected technical and social systems, helping students link theory with practice.
The Cynefin framework (Nachbagauer, 2021; Snowden, 2002), helps decision-makers distinguish between different types of problem contexts—simple, complicated, complex, chaotic, and disordered. In an engineering context, this framework guides learners to recognise when traditional linear methods work (for simple or complicated problems) and when adaptive, experimental approaches are required (for complex or chaotic systems).
Within this teaching activity, Cynefin is used to help students understand how resilience strategies evolve when facing uncertainty, incomplete information, and changing stakeholder dynamics. By mapping case study events to the Cynefin domains, learners gain a structured way to navigate uncertainty and identify appropriate modes of action.
This case study activity assumes basic familiarity with systems concepts and builds on this foundation with deeper application to real-world socio-technical challenges.
Summary of context:
The activity focuses on a case study of 2010–2011 floods in Queensland, Australia, which caused extensive damage to urban infrastructure. The Queensland Reconstruction Authority (QRA) initially directed resources to short-term asset repairs but subsequently shifted towards long-term resilience planning, hazard management, and community-centred approaches.
The case resonates with global engineering challenges, such as flood, fire, and storm resilience, and can be easily adapted to local contexts. This case therefore connects systems thinking theory directly to engineering and governance decisions, illustrating how frameworks like Cynefin can support engineers in navigating uncertainty across technical and institutional domains.
Learning objectives:
Aligned with AHEP4 (Engineering Council, 2020) – Outcomes 6, 10, and 16 on systems approaches, sustainability, and risk – this activity emphasises systems thinking, stakeholder engagement, problem definition, and decision-making under uncertainty.
This teaching activity introduces learners to the principles and practice of systems thinking by embedding a real-world case study into engineering education (Godfrey et al., 2014; Monat et al.,2022). The objectives are to:
Enable students to recognise interconnections, interdependencies, and evolving behaviours of stakeholders within socio-technical systems.
Support learners in applying systems frameworks —particularly the Cynefin framework and stakeholder mapping—to analyse complexity, uncertainty, and decision-making in climate resilience and disaster mitigation contexts.
Apply systems thinking tools and frameworks to real-world challenges, such as climate resilience and disaster mitigation.
Strengthen confidence in addressing uncertainty and complexity in engineering problem-solving.
Collaborate effectively across diverse teams, appreciating multiple stakeholder perspectives.
Reflect critically on trade-offs and decision-making in engineering practice.
Equip students to transfer systems insights from case-based scenarios to broader projects in their curriculum and future professional practice.
Teachers have the opportunity to:
Introduce students to complex systems concepts through engaging, real-world case studies.
Facilitate interactive, blended learning using narrative-driven tools, explainer animations, and role-play exercises.
Assess learners’ baseline and improved understanding of systems thinking through pre- and post-module surveys.
Guide students in navigating multiple systems frameworks while managing cognitive load.
Encourage interdisciplinary collaboration and stakeholder-focused analysis within classroom or project-based settings.
Adapt and scale the teaching activity for different educational levels, contexts, and case study themes (e.g., floods, wildfires, extreme heat).
This dedicated platform hosts the interactive modules designed for this teaching activity. Students progress through three modules — Context, Analysis and Insights, and Discussion and Transferable Learning. Each module includes animations, narrative-driven content, scenario prompts, and interactive tasks. The platform ensures flexibility: it can be used in fully online, hybrid, or face-to-face settings. All necessary digital assets (readings, maps, videos, and quizzes) are embedded, so learners have a “one-stop” environment.
The core teaching narrative is anchored in this Engineering X case study. It documents the evolution of the Queensland Reconstruction Authority (QRA) from a short-term flood recovery body to a long-term resilience institution. This resource provides students with authentic socio-technical detail — including stakeholder conflicts, institutional learning, and systemic barriers — which they then interrogate using systems thinking frameworks.
This resource provides a suggested delivery schedule for facilitators. It maps when live sessions, asynchronous tasks, and group discussions should occur, ensuring students remain engaged over the course. It also indicates where key reflective points and assessments (both formative and summative) can be integrated.
5. Pre- and post-module assessment form: (Appendix C)
This tool evaluates students’ systems thinking learning outcomes. It includes:
Baseline survey: assesses initial understanding of systems thinking, approaches to complex problems, and confidence in collaboration.
Scenario-based survey: applies systems thinking questions to a specific context (e.g. extreme monsoon rains and flooding in the case of Sakura Cove – as per the group assignment in module 1).
Post-module survey: measures changes in understanding, confidence, and skills, while also capturing qualitative reflections on learning.
The form provides both quantitative data (Likert scales) and qualitative insights (open-ended reflections), enabling robust evaluation of teaching impact.
Assessment:
Formative: Pre- and post-module surveys assess changes in learners’ self-reported understanding of systems thinking (Appendix A). Facilitators may adapt reflective prompts and scenario-based activities as part of coursework.
Summative (optional): Students can integrate insights into ongoing design projects (e.g. climate resilience in urban redevelopment), with assessment based on problem analysis, stakeholder engagement, and solution development.
Narrative of the case:
Learners are introduced to the case via a fictional guide, “Bernice,” who frames the scenario and supports navigation through the material. Students work through three stages that progressively apply the Cynefin framework and other systems tools to understand how resilience emerges through evolving governance and engineering responses:
1. Context module:
Initial Mandate: Students explore how the QRA was first tasked with rapid technical recovery—fixing roads after flood damage.
Narrative Depth: They study the Queensland floods of 2010–11 not just as a physical shock, but as a systemic stress test on multiple layers: infrastructure, governance, and community systems.
2. Analysis & insights module:
Framework Application: Learners apply systems frameworks (e.g., Cynefin, stakeholder maps) to see how QRA’s remit expanded over time—from asset restoration to hazard anticipation and community resilience.
Knowledge Types: Students distinguish between explicit knowledge (e.g., rebuild standards, hydrology data) and tacit knowledge (e.g., local inter-agency trust, relational coordination).
Governance Layers: Activities explore how resilience depends on multi-level governance, local-state-federal coordination, and overcoming systemic barriers like funding cycles or short-lived institutional mandates.
3. Discussion & transfer learning module:
Reflective Debate: Students weigh whether engineering alone can deliver resilience, or whether social relationships and institutions are equally critical.
Barrier Identification: They debate typical constraints—political, funding, institutional—and propose ways systems thinking can mitigate them.
Transfer Lab: Learners apply the evolved QRA model to other scenarios—e.g., urban heat adaptation or wildfires—considering both technical measures and governance dynamics.
Interactive learning design:
The teaching activity integrates multiple interactive elements to immerse students in systems thinking:
Role-play simulations: Learners take on the role of Queensland Reconstruction Authority (QRA) decision-makers, negotiating trade-offs between immediate engineering fixes and long-term institutional resilience. This requires balancing technical priorities with building trust, relationships, and governance capacity.
Scenario challenges: Students are presented with governance disruptions (e.g. funding cuts, loss of stakeholder trust, leadership turnover). They must reframe solutions using systems approaches, moving from reactive technical patchworks towards adaptive, capacity-building strategies.
Interactive digital tools: The online platform provides hotspot maps for exploring interdependencies, drag-and-drop activities for categorising frameworks, explainer animations, and AI-driven chatbot negotiations with sceptical stakeholders. These exercises develop critical and applied problem-solving skills.
Collaborative reflection: Group discussions and peer-to-peer feedback allow learners to surface diverse perspectives, debate trade-offs, and integrate insights into ongoing project briefs.
Why this approach adds value:
Although rooted in social-technical interactions, the activity explicitly connects systems thinking to core engineering design competencies—problem framing, stakeholder analysis, and iterative solution development under uncertainty
Holistic understanding of resilience: Students experience resilience as more than just technical recovery. They engage with a dynamic system that includes knowledge creation, governance evolution, and social relationships.
Adaptive systems thinking in action: The evolving narrative demonstrates how system boundaries shift over time, and how sustainable outcomes require not only engineering but institutional and cultural change.
Direct relevance to real-world engineering: The case mirrors global infrastructure challenges where effective disaster response and resilience planning depend on the interplay between technical solutions, governance capacity, and community engagement.
Guided questions and activities:
Facilitators can use these prompts to stimulate inquiry and structured reflection:
Who are the key stakeholders in the QRA flood response, and where do their priorities align or conflict?
How do feedback loops and interdependencies influence resilience planning?
What trade-offs exist between rapid repair and long-term resilience?
How can systems frameworks such as the Cynefin model or stakeholder mapping guide decision-making under uncertainty?
In role-play: how would you convince a sceptical funder (AI chatbot) to invest in resilience measures?
How could lessons from flood mitigation be applied to other contexts such as wildfire or urban heat resilience?
Opportunities for extension:
In addition to the Queensland floods and Sakura Cove examples, educators may draw parallels with urban heat planning in London, wildfire adaptation in Australia, or storm resilience in the Netherlands. These comparative cases allow learners to generalise systems insights beyond one event or geography.
The activity is designed to be scalable and adaptable:
Broader case study base: Educators can expand beyond flood resilience to include wildfire, storm, or extreme heat events.
Integration with larger modules: The activity can be embedded into project-based learning modules (e.g. urban redevelopment, transport network resilience).
Advanced complexity: For higher-level learners, facilitators can introduce additional frameworks (e.g. agent-based modelling, system dynamics) to deepen analysis.
This flexibility allows educators to tailor the activity to their students’ level of expertise, institutional context, and disciplinary focus.
References:
Design Council. (2021). Beyond Net Zero: A systemic design approach. Design Council.
Godfrey, P., Crick, R. D., & Huang, S. (2014). Systems thinking, systems design and learning power in engineering education. International Journal of Engineering Education.
Monat, J., Gannon, T., & Amissah, M. (2022). The case for systems thinking in undergraduate engineering education. International Journal of Engineering Pedagogy, 12(3), 50–88.
Nachbagauer, A. (2021). Managing complexity in projects: Extending the Cynefin framework. Project Leadership and Society, 2, 100017.
Snowden, D. (2002). Complex acts of knowing: paradox and descriptive self‐awareness. Journal of knowledge management, 6(2), 100-111.
Any views, thoughts, and opinions expressed herein are solely that of the author(s) and do not necessarily reflect the views, opinions, policies, or position of the Engineering Professors’ Council or the Toolkit sponsors and supporters.
Related INCOSE Competencies: Toolkit resources are designed to be applicable to any engineering discipline, but educators might find it useful to understand their alignment to competencies outlined by the International Council on Systems Engineering (INCOSE). The INCOSE Competency Framework provides a set of 37 competencies for Systems Engineering within a tailorable framework that provides guidance for practitioners and stakeholders to identify knowledge, skills, abilities and behaviours crucial to Systems Engineering effectiveness. A free spreadsheet version of the framework can be downloaded.
This resource relates to the Systems Thinking, Systems Modelling and Analysis, Ethics and Professionalism, Technical Leadership and Critical Thinking INCOSE Competencies.
AHEP4 mapping: This resource addresses several of the themes from the UK’s Accreditation of Higher Education Programmes fourth edition (AHEP4): Analytical Tools and Techniques (critical to the ability to model and solve problems), and Integrated / Systems Approach (essential to the solution of broadly-defined problems). In addition, this resource addressesAHEP themes of Design, Ethics and Communication.
Educational level: Intermediate; Advanced.
Learning and teaching notes:
The case is built around 3 × 90-minute sessions and independent report writing. A suggested breakdown of the activities can be seen below.
Learners have the opportunity to:
Explore how technical, human, and organisational factors interact in complex socio-technical systems.
Apply Fault Tree Analysis (FTA) to diagnose ambiguous real-world engineering failures.
Practice making judgements under uncertainty with incomplete and conflicting data.
Analyse competing stakeholder perspectives and the ethical trade-offs in engineering decision-making.
Develop professional communication skills by producing expert reports and presenting findings to a stakeholder panel.
Reflect on their own reasoning, assumptions, and handling of complexity.
Teachers have the opportunity to:
Use an authentic, narrative-driven case to introduce systems thinking and failure analysis.
Facilitate active learning through group FTA construction and peer review.
Engage students in interdisciplinary learning that links materials science, engineering practice, regulation, and ethics.
Adapt the complexity of the case (technical vs organisational) depending on learners’ level and course focus.
Provide formative and summative assessment using expert reports, presentations, and reflective writing.
Encourage metacognitive development by prompting students to examine uncertainty and assumptions in engineering practice.
20 min: Introduce case scenario and system context; 30 min: Group discussion on initial impressions, key stakeholders, and potential causes; 40 min: Begin Fault Tree Analysis (FTA) construction using initial evidence.
2
Investigation and analysis
30 min: Continue FTA construction and data evaluation; 30 min: Peer review of other groups’ fault trees; 30 min: Consolidate findings and prepare draft report outline.
3
Reporting and reflection
30 min: Present findings to a simulated stakeholder panel; 30 min: Discuss feedback and defend conclusions; 30 min: Individual reflection on complexity, uncertainty, and assumptions.
Summary of the system or context:
Rail transport systems consist of thousands of interdependent components, including rails, fasteners, sleepers, signalling systems, and maintenance processes. Failures in a single component can cascade, affecting:
Safety: Malfunctions may cause derailments or delays.
Economics: Service interruptions lead to financial losses and reputational damage.
Public trust: Media scrutiny increases scrutiny of operational practices.
On a cold January morning, a commuter train was halted after inspectors discovered a fractured rail joint component. Services were disrupted for several hours, stranding thousands of passengers. The media quickly picked up the story, raising questions about safety and reliability.
The rail operator urgently commissioned an engineering consultancy (the students) to investigate the failure. Their findings will inform both the safety authority’s decision on whether the line can reopen and the legal proceedings to determine liability.
The dilemma:
The operator demands a rapid report to resume services.
The manufacturer insists the component was produced to specification and blames poor maintenance.
The regulator requires an unbiased, defensible technical opinion before approving operations.
The public expects transparency and reassurance about safety.
As consultants, students face incomplete evidence: some lab tests are missing, inspection logs are inconsistent, and eyewitness accounts conflict. They must use Fault Tree Analysis (FTA) to map possible causes, evaluate data, and produce an expert opinion report — knowing that their conclusions could influence legal outcomes and public safety decisions.
Groups: 3–5 students per group; 3-4 groups can run in parallel.
Materials required: case narrative handouts, sample inspection log, example FTA, whiteboards/flipcharts, sticky notes for FTA mapping.
Activity flow:
1. Introduce case and assign roles.
2. Construct initial fault trees using evidence.
3. Peer-review across groups.
4. Draft expert report and present to simulated stakeholder panel.
5. Individual reflection on complexity and uncertainty.
Why use Fault Tree Analysis (FTA):
FTA is a structured approach to trace a failure from an observed event back to potential causes, including technical, human, and organisational factors.
FTA is particularly suitable for this case because it allows students to structure complex, uncertain information in a logical and transparent way. It helps them trace the chain of causes behind the rail component failure, linking material, human, and organisational factors into one coherent framework. By visualising how small events combine into system-level failures, FTA encourages learners to think critically about interdependencies, data gaps, and assumptions. It also mirrors real-world engineering investigations, where professionals must justify conclusions under uncertainty and demonstrate clear reasoning to stakeholders such as regulators or courts.
Visualises cause-effect relationships, interdependencies, and failure paths.
Encourages discussion of assumptions and uncertainties.
Questions and activities:
Discussion prompts:
Prompt
Expected insight / reflection
What technical, human, and organisational factors might have contributed to this failure?
Students identify multiple interacting factors, illustrating interdependencies and emergent risks.
How does Fault Tree Analysis help structure uncertainty in this investigation?
Learners recognise FTA’s role in visualising cause-effect pathways and clarifying assumptions.
Which assumptions are you forced to make, and how might they affect your conclusions?
Students reflect on data gaps, biased observations, and ethical implications of assumptions.
How do different stakeholders’ interests shape urgency and framing of your analysis?
Learners understand trade-offs, pressures from conflicting priorities, and the precautionary principle.
What are the risks of issuing a preliminary report under time pressure?
Students explore implications for safety, liability, professional integrity, and public trust.
Classroomactivities:
Activity
Focus
What “good practice” looks like
Facilitator notes / tips
1. FTA construction
Collaborative problem analysis
Teams discuss evidence openly, question assumptions, and co-create a logical tree linking technical, human, and organisational causes.
Encourage each group to identify at least one “human/organisational” branch and to label any data gaps explicitly.
2. Peer review
Critical reflection and systems perspective
Groups provide constructive critique, highlighting hidden assumptions, missing branches, or unclear logic. Dialogue stays professional and evidence-based.
Provide coloured sticky notes or digital comments to record feedback; model how to frame critique as questions (“Have you considered…?”).
3. Report writing (in-class drafting)
Synthesis and professional communication
Drafts show a clear, defensible reasoning chain from evidence to conclusion. Teams justify assumptions and note uncertainties.
Remind students to separate “facts” from “interpretations.” Encourage use of structured headings (Findings – Analysis – Conclusions).
4. Simulation role-Play
Perspective-taking and communication under pressure
Presentations are concise (≤5 min), factual, and adapted to stakeholder roles. Learners respond respectfully and clearly to challenging questions.
Provide role cards for the panel (operator, regulator, manufacturer, public). Rotate students if possible.
5. Reflection
Metacognition and learning from uncertainty
Students identify what surprised them, what they found ambiguous, and how their view of engineering judgment evolved.
Offer prompts like “What would you do differently next time?” or “Where did your reasoning feel uncertain?”
Further challenge:
Instructors may choose to introduce a second “reveal” phase: a new metallurgical test result or a whistle-blower statement emerges halfway through the case. Students must revise their fault tree and defend whether and how their conclusions change. This highlights the evolving nature of complex systems investigations.
Assessment opportunities:
Fault Tree Diagram (30%) – accuracy, depth, clarity.
Presentation and defence (20%) – clarity, stakeholder awareness, handling questions.
Reflective summary (20%) – insight into uncertainty, assumptions, systems thinking.
Any views, thoughts, and opinions expressed herein are solely that of the author(s) and do not necessarily reflect the views, opinions, policies, or position of the Engineering Professors’ Council or the Toolkit sponsors and supporters.
Activity: Assessment. This example demonstrates how the questions provided in Assessing ethics: Rubric can be used to assess the competencies stipulated at each level.
Authors: Dr. Natalie Wint (UCL); Dr. William Bennett (Swansea University).
This example demonstrates how the questions provided in the accompanying rubric can be used to assess the competencies stipulated at each level. Although we have focused on ‘Water Wars’ here, the suggested assessment questions have been designed in such a way that they can be used in conjunction with the case studies available within the toolkit, or with another case study that has been created (by yourself or elsewhere) to outline an ethical dilemma.
Year 1
Personal values: What is your initial position on the issue? Do you see anything wrong with how DSS are using water? Why, or why not?
Students should provide a stance, but more importantly their stance should be justified. In this instance this may involve reference to common moral values such as environmental sustainability, risk associated with power issues and questions of ownership.
Professional responsibilities: What ethical principles and codes of conduct are relevant to this situation?
Students should refer to relevant principles (e.g. from the Joint Statement of Ethical Principles). For example, in this case some of the relevant principles may include (but not be limited to) “protect, and where possible improve, the quality of built and natural environment”, “maximise the public good and minimise both actual and potential adverse effects for their own and succeeding generations” and “take due account of the limited availability of natural resources”.
Ethical principles and codes of conduct can be used to guide our actions during an ethical dilemma. How does the guidance provided in this case align/differ with your personal views? (This is a question we had created in addition to those provided within the case study to meet the requirements stipulated in the accompanying rubric.)
Students’ answers will depend upon those given to the previous questions but should include some discussion of similarities and differences between their own initial thoughts and principles/codes of conducts, and allude to the tensions involved in ethical dilemmas and the impact on decision making.
What are the moral values involved in this case and why does it constitute an ethical dilemma? (This is a question we had created in addition to those provided within the case study to meet the requirements stipulated in the accompanying rubric.)
Students should be able to identify relevant moral values and explain that an ethical dilemma constitutes a problem in which two or more moral values or norms cannot be fully realised at the same time.
There are two (or a limited number of) options for action and whatever they choose they will commit a moral wrong. The crucial feature of a moral dilemma is not the number of actions that are available but the fact that all possible actions are morally unsatisfactory.
What role should an engineer play in influencing the outcome? What are the implications of not being involved? (This is a question we had created in addition to those provided within the case study to meet the requirements stipulated in the accompanying rubric.)
Engineers are responsible for the design of technological advancements which necessitate data storage. Although this brings many benefits, engineers need to consider the adverse impact of technological advancement such as increased water use. Students may therefore want to consider the wider implications of data storage on the environment and how these can be mitigated.
Year 2
Formulate a moral problem statement which clearly states the problem, its moral nature and who needs to act. (This is a question we had created in addition to those provided within the case study to meet the requirements stipulated in the accompanying rubric.)
An example could be: “Should the civil engineer working for DSS remain loyal to the company and defend them against accusations of causing environmental hazards, or defend their water rights and say that they will not change their behaviour”. It should be clear what the problem is, the moral values at play and who needs to act.
Stakeholder mapping: Who are all the stakeholders in the scenario? What are their positions, perspective and moral values?
Below is a non-exhaustive list of some of the relevant stakeholders and values that may come up.
Stakeholder
Perspectives/interests
Moralvalues
DataStorageSolutions (DSS)
Increasing production in a profitable way; meeting legal requirements; good reputationtomaintain/grow customer base.
Representviewsofthose concerned about biodiversity. May be interested in opening ofgreenbattery plant.
Human welfare; environmental sustainability;justice.
LocalCouncil
Represent views of all stakeholders and would needtoconsidereconomic benefits of DSS (tax and employment), the need of theuniversityandhospital, as well as the needs of local farmers and environmentalists. May beinterestedinopeningof green battery plant.
This may depend on their beliefs as an individual, their employment status and their use of services such as the hospital and university. Typically interested in low taxes/responsible spending of public money. May be interested in opening of green batteryplant.
Reliable storage. They mayalsobeinterestedin being part of an ethical supply chain.
Trust; privacy; accountability;autonomy.
Non-humanstakeholders
Environmental sustainability.
What are some of the possible courses of action in the situation. What responsibilities do you have to the various stakeholders involved? What are some of the advantages and disadvantages associated with each? (Reworded from case study.)
Students should provide a stance but may recognise the tensions involved. For example, at a micro level, tensions between loyalty to the profession and loyalty to the company/personal financial stability. Responsibilities to fellow employees may include the degree to which you risk their jobs by being honest. They may also feel that they should protect environmental and natural resources.
At a macro level, they may consider the need for engineers to inform decisions regarding issues that engineering and technology raise for society (e.g. increased water being needed for data storage) and listen to the aspirations and concerns of others, and challenging statements or policies that cause them professional concern.
What are the relevant facts in this scenario and what other information would you like to help inform your ethical decision making? (This is a question we had created in addition to those provided within the case study to meet the requirements stipulated in the accompanying rubric.)
Students should identify which facts within the case study are relevant in terms of making an ethical decision. In this case, some of the relevant facts may include:
Water use permissible by law (“the data centre always uses the maximum amount legally allotted to it.”)
This centre manages data which is vital for the local community, including the safe running of schools and hospitals, and that its operation requires sufficient water for cooling.
In more arid months, the nearby river almost runs dry, resulting in large volumes of fish dying.
Water levels in farmers’ wells have dropped, making irrigation much more expensive and challenging.
A new green battery plant is planned to open nearby that will create more data demand and has the potential to further increase DSS’ water use.
Obtaining water from other sources will be costly to DSS and may not be practically possible, let alone commercially viable.
Studentsshouldbeawarethatincompleteinformationhindersdecisionmakingduring ethical dilemmas, and that in some cases, further information will be needed to help inform decisions. In this case, some of the questions may pertain to:
Exactly how much water is being used and the legal rights.
Relationship between farmer and DSS/contractual obligations.
How costly irrigation is to the farmers (economic impact), as well as the knock-on impact to their business and supply chain.
How many people DSS employ and how important they are for local economy.
Detail regarding biodiversity loss and its wider impact.
How likely it is that the green battery plant will open and whether DSS is the only eligible supplier.
How much the green battery plant contract is worth to DSS.
How much water the green battery plant will use in the case that DSS get the contract.
Whether DSS is the only option for hospital and university.
What will happen if the services DSS provide to the hospital and university stop or becomes unreliable.
Year 2/Year 3
(At Year 2, students could provide options; at Year 3 they would evaluate and form a judgement.)
Make use of ethical frameworks and/or professional codes to evaluate the options for DSS both short term and long term. How do the uncertainty and assumptions involved in this case impact decision making?
Students should list plausible options. They can then analyse them with respect to different ethical frameworks (whilst we don’t necessary make use of normative ethical theories, analysis according to consequences, intention or action may be a useful approach to this). Below we have included a non-exhaustive list of options with ideas in terms of analysis.
Option
Consequences
Intention
Action
Keepusing water
May lead to expansion and profit of DSS and thus tax revenue/employment and supply.
Reputational damage of DSS may increase. Individual employee piece of mind may be at risk.
Farmers still don’t have water and biodiversity still suffers which may have further impact long term.
Intentionbehindaction notconsistentwith that expected by an engineer, other than with respect to legality
Actionfollowslegalnormsbut not social norms such as good will and concern for others.
Keep using the water but limit furtherwork
May limit expansion and profit of DSS and thus tax revenue/employment and supply.
Farmers still don’t have water and biodiversity still suffers and may have further impact long term. This could still result in reputation damage.
Intentionbehindaction partially consistent with that expected by an engineer.
Actionfollowslegalnormsbut only partially follow social norms such as good will and concern for others.
Makeuseof other sources of water
Data storage continues.
Potential for reputation to increase.
Potential increase in cost of water resulting in less profit potentially less tax revenue/employment.
Farmers have water and biodiversity may improve.
Alternativewatersourcesmaybeassociated with the same issues or worse.
Intention behind action seems consistent with that expected by an engineer. However, this is dependent upon
whether they chose to source sustainablewaterwithlessimpact on biodiversity etc.
Thismaybedependenton the degree to which DSS proactively source sustainable water.
Reduce worklevels or shut down
Impact on profit and thus tax revenue/employment and supply chain. Farmers have water and biodiversity may improve.
May cause operational issues for those whose data is stored.
Seems consistent with those expected of engineer. Raises questions more generally about viability and feasibility of datastorage.
Action doesn’t follow social norms of responsibility to employeesandshareholders.
Investigate othercooling methods which don’t require as much water/don’t take on extra work untilanother method identified.
May benefit whole sector.
May cause interim loss of service.
This follows expectations of the engineeringprofession in terms of evidence-baseddecisionmaking and consideration for impact of engineering in society.
It follows social norms in termsofresponsibledecision making.
Any views, thoughts, and opinions expressed herein are solely that of the author(s) and do not necessarily reflect the views, opinions, policies, or position of the Engineering Professors’ Council or the Toolkit sponsors and supporters.
Author: Dr. Jemma L. Rowlandson (University of Bristol).
Keywords: Design and innovation; Conflicts of interest; Ethics; Regulatory compliance; Stakeholder engagement; Environmental impact; AHEP; Sustainability; Higher education; Pedagogy; Assessment.
Sustainability competency: Systems thinking; Anticipatory; Critical thinking; Integrated problem-solving; Strategic; Collaboration.UNESCO has developed eight key competencies for sustainability that are aimed at learners of all ages worldwide. Many versions of these exist, as are linked here*. In the UK, these have been adapted within higher education by AdvanceHE and the QAA with appropriate learning outcomes. The full list of competencies and learning outcome alignment can be found in the Education for Sustainable Development Guidance*. *Click the pink ''Sustainability competency'' text to learn more.
AHEP mapping: This resource addresses two of the themes from the UK’s Accreditation of Higher Education Programmes fourth edition (AHEP4): The Engineer and Society (acknowledging that engineering activity can have a significant societal impact) and Engineering Practice (the practical application of engineering concepts, tools and professional skills). To map this resource to AHEP outcomes specific to a programme under these themes, access AHEP 4 here and navigate to pages 30-31 and 35-37.
Related SDGs: SDG 7 (Affordable and Clean Energy); SDG 9 (Industry, Innovation and Infrastructure); SDG 12 (Responsible Consumption and Production); SDG 13 (Climate Action).
Reimagined Degree Map Intervention: More real-world complexity; Active pedagogies and mindset development; Authentic assessment.The Reimagined Degree Map is a guide to help engineering departments navigate the decisions that are urgently required to ensure degrees prepare students for 21st century challenges. Click the pink ''Reimagined Degree Map Intervention'' text to learn more.
Educational aim: Apply interdisciplinary engineering knowledge to a real-world sustainability challenge in aviation, foster ethical reasoning and decision-making with regards to environmental impact, and develop abilities to collaborate and communicate with a diverse range of stakeholders.
Educational level: Intermediate.
Learning and teaching notes:
This case study provides students an opportunity to explore the role of hydrogen fuel in the aviation industry. Considerable investments have been made in researching and developing hydrogen as a potential clean and sustainable energy source, particularly for hydrogen-powered aircraft. Despite the potential for hydrogen to be a green and clean fuel there are lingering questions over the long-term sustainability of hydrogen and whether technological advancements can progress rapidly enough to significantly reduce global carbon dioxide emissions. The debate around this issue is rich with diverse perspectives and a variety of interests to consider. Through this case study, students will apply their engineering expertise to navigate this complex problem and examine the competing interests involved.
This case is presented in parts, each focusing on a different sustainability issue, and with most parts incorporating technical content. Parts may be used in isolation, or may be used to build up the complexity of the case throughout a series of lessons.
Learners have the opportunity to:
Understand the principles of hydrogen production, storage, and emissions in the context of aviation.
Assess the environmental, economic, and social impacts of adopting hydrogen technology in the aviation industry.
Develop skills in making estimates and assumptions in real-world engineering scenarios.
Explore the ethical dimensions of engineering decisions, particularly concerning sustainability and resource management.
Examine the influence of policy and stakeholder perspectives on the adoption of green hydrogen within the aviation industry.
Teachers have the opportunity to:
Integrate concepts related to renewable energy sources, with a focus on hydrogen.
Discuss the engineering challenges and solutions in storing and utilising hydrogen in aviation.
Foster critical thinking about the balance between technological innovation, environmental sustainability, and societal impact.
Guide students in understanding the role of policy in shaping technological advancements and environmental strategies.
Assess students’ ability to apply engineering principles to solve complex, open-ended, real-world problems.
Supporting resources:
Learning and teaching resources:
Hydrogen fundamentals resources:
Case Study Workbook – designed for this study to give a broad overview of hydrogen, based primarily on the content below from US DoE.
Hydrogen Aware – Set of modules for a more comprehensive background to hydrogen with a UK-specific context.
We recommend encouraging the use of sources from a variety of stakeholders. Encourage students to find their own, but some examples are included below:
FlyZero Open Source Reports Archive: A variety of technical reports focused on hydrogen in aviation specifically including concept aircraft, potential life cycle emissions, storage, and usage.
Hydrogen in Aviation Alliance: Press release (September 2023) announcing an agreement amongst some of the major players in aviation to focus on hydrogen.
Safe Landing: A group of aviation workers campaigning for long-term employment. Projected airline growth is not compatible with net zero goals and the current technology is not ready for decarbonisation, action is drastically needed now to safeguard the aviation industry and prevent dangerous levels of warming.
UK Government Hydrogen Strategy: Sets out the UK government view of how to develop a low carbon hydrogen sector including aviation projects including considerations of how to create a market.
Pre-Session Work:
Students should be provided with an overview of the properties of hydrogen gas and the principles underlying the hydrogen economy: production, storage and transmission, and application. There are several free and available sources for this purpose (refer to the Hydrogen Fundamentals Resources above).
Introduction
“At Airbus, we believe hydrogen is one of the most promising decarbonisation technologies for aviation. This is why we consider hydrogen to be an important technology pathway to achieve our ambition of bringing a low-carbon commercial aircraft to market by 2035.” – Airbus, 2024
As indicated in the industry quote above, hydrogen is a growing area of research interest for aviation companies to decarbonise their fleet. In this case study, you are put in the role of working as an engineering consultant and your customer is a multinational aerospace corporation. They are keen to meet their government issued targets of reducing carbon emissions to reach net zero by 2050 and your consultancy team has been tasked with assessing the feasibility of powering a zero-emission aircraft using hydrogen. The key areas your customer is interested in are:
The feasibility of using green hydrogen as a fuel for zero-emission aviation;
The feasibility of storing hydrogen in a confined space like an aircraft;
Conducting a stakeholder analysis on the environmental impact of using hydrogen for aviation.
Part one: The aviation landscape
Air travel connects the world, enabling affordable and reliable mass transportation between continents. Despite massive advances in technology and infrastructure to produce more efficient aircraft and reduce passenger fuel consumption, carbon emissions have doubled since 2019 and are equivalent to 2.5 % of global CO2 emissions.
Activity: Discuss what renewable energy sources are you aware of that could be used for zero-emission aviation?
Your customer is interested in the feasibility of hydrogen for aviation fuel. However, there is a debate within the management team over the sustainability of hydrogen. As the lead engineering consultant, you must guide your customer in making an ethical and sustainable decision.
Hydrogen is a potential energy carrier which has a high energy content, making it a promising fuel for aviation. Green hydrogen is produced from water and is therefore potentially very clean. However, globally most hydrogen is currently made from fossil fuels with an associated carbon footprint. Naturally occurring as a gas, the low volumetric density makes it difficult to transport and add complications with storage and transportation.
Activity: From your understanding of hydrogen, what properties make it a promising fuel for aircraft? And what properties make it challenging?
Optional activity: Recap the key properties of hydrogen – particularly the low gas density and low boiling point which affect storage.
Part two: Hydrogen production
Hydrogen is naturally abundant but is often found combined with other elements in various forms such as hydrocarbons like methane (CH4) and water (H2O). Methods have been developed to extract hydrogen from these compounds. It is important to remember that hydrogen is an energy carrier and not an energy source; it must be generated from other primary energy sources (such as wind and solar) converting and storing energy in the form of hydrogen.
Research: What production methods of hydrogen are you aware of? Where does most of the world’s hydrogen come from currently?
The ideal scenario is to produce green hydrogen via electrolysis where water (H2O) is split using electricity into hydrogen (H2) and oxygen (O2). This makes green hydrogen potentially completely green and clean if the process uses electricity from renewable sources. The overall chemical reaction is shown below:
However, the use of water—a critical resource—as a feedstock for green hydrogen, especially in aviation, raises significant ethical concerns. Your customer’s management team is divided on the potential impact of this practice on global water scarcity, which has been exacerbated by climate change. You have been tasked with assessing the feasibility of using green hydrogen in aviation for your client. Your customer has chosen their London to New York route (3,500 nmi), one of their most popular, as a test-case.
Activity: Estimate how much water a hydrogen plane would require for a journey of 3500 nmi (London to New York). Can you validate your findings with any external sources?Hint: How much water does it take to produce 1 kg of green hydrogen? Consider the chemical equation above.
Activity: Consider scaling this up and estimate how much water the entire UK aviation fleet would require in one year. Compare your value to the annual UK water consumption, would it be feasible to use this amount of water for aviation?
Discussion: From your calculations and findings so far, discuss the practicality of using water for aviation fuel. Consider both the obstacles and opportunities involved in integrating green hydrogen in aviation and the specific challenges the aviation industry might face.
Despite its potential for green production, globally the majority of hydrogen is currently produced from fossil fuels – termed grey hydrogen. One of your team members has proposed using grey hydrogen as an interim solution to bridge the transition to green hydrogen, in order for the company to start developing the required hydrogen-related infrastructure at airports. They argue that carbon capture and storage technology could be used to reduce carbon emissions from grey hydrogen while still achieving the goal of decarbonisation. Hydrogen from fossil fuels with an additional carbon capture step is known as blue hydrogen.
However, this suggestion has sparked a heated debate within the management team. While acknowledging the potential to address the immediate concerns of generating enough hydrogen to establish the necessary infrastructure and procedures, many team members argued that it would be a contradictory approach. They highlighted the inherent contradiction of utilising fossil fuels, the primary driver of climate change, to achieve decarbonisation. They emphasised the importance of remaining consistent with the ultimate goal of transitioning away from fossil fuels altogether and reducing overall carbon emissions. Your expertise is now sought to weigh these options and advise the board on the best course of action.
Optional activity: Research the argument for and against using grey or blue hydrogen as an initial step in developing hydrogen infrastructure and procedures, as a means to eventually transition to green hydrogen. Contrast this with the strategy of directly implementing green hydrogen from the beginning. Split students into groups to address both sides of this debate.
Discussion: Deliberate on the merits and drawbacks of using grey or blue hydrogen to catalyse development of hydrogen aviation infrastructure. What would you recommend—prioritising green hydrogen development or starting with grey or blue hydrogen as a transitional step? How will you depict or visualise your recommendation to your client?
Part three: Hydrogen storage
Despite an impressive gravimetric energy density (the energy stored per unit mass of fuel) hydrogen has the lowest gas density and the second-lowest boiling point of all known chemical fuels. These unique properties pose challenges for storage and transportation, particularly in the constrained spaces of an aircraft.
Activity: Familiarise yourself with hydrogen storage methods. What hydrogen storage methods are you aware of? Thinking about an aviation context what would their advantages and disadvantages be?
As the lead engineering consultant, you have been tasked with providing expert advice on viable hydrogen storage options for aviation. Your customer has again chosen their London to New York route (3,500 nmi) as a test-case because it is one of their most popular, transatlantic routes. They want to know if hydrogen storage can be effectively managed for this route as it could set a precedent for wider adoption for their other long-haul flights. The plane journey from London to New York is estimated to require around 15,000 kg of hydrogen (or use the quantity estimated previously estimated in Part 2 – see Appendix for example).
Activity: Estimate the volume required to store the 15,000 kg of hydrogen as a compressed gas and as a liquid.
Discussion: How feasible are compressed gas and liquid hydrogen storage solutions? The space taken up by the fuel is one consideration but what other aspects are important to consider? How does this compare to the current storage solution for planes which use conventional jet fuel. Examples of topics to consider are: materials required for storage tanks, energy required to liquify or compress the hydrogen, practicality of hydrogen storage and transport to airports, location and distance between hydrogen generation and storage facilities, considerations of fuel leakage. When discussing encourage students to compare to the current state of the art, which is jet fuel.
Part four: Emissions and environmental impact
In Part four, we delve deeper into the environmental implications of using hydrogen as a fuel in aviation with a focus on emissions and their impacts across the lifecycle of a hydrogen plane. Aircraft can be powered using either direct combustion of hydrogen in gas turbines or by reacting hydrogen in a fuel cell to produce electricity that drives a propeller. As the lead engineering consultant, your customer has asked you to choose between hydrogen combustion in gas turbines or the reaction of hydrogen in fuel cells. The management team is divided on the environmental impacts of both methods, with some emphasising the technological readiness and efficiency of combustion and others advocating for the cleaner process of fuel cell reaction.
Activity: Research the main emissions associated with combustion of hydrogen and electrochemical reaction of hydrogen in fuel cells. Compare to the emissions associated with combustion of standard jet fuel.Students should consider not only CO2 emissions but also other pollutants such as NOx, SOx, and particulate matter.
Discussion: What are the implications of these emissions on air quality and climate change. Discuss the trade-offs between the different methods of utilising hydrogen in terms of the environmental impact. Compare to the current standard of jet fuel combustion.
Both combustion of hydrogen in an engine and reaction of hydrogen in a fuel cell will produce water as a by-product. The management team are concerned over the effect of using hydrogen on the formation of contrails. Contrails are clouds of water vapour produced by aircraft that have a potential contribution to global warming but the extent of their impact is uncertain.
Activity: Investigate how combustion (of both jet fuel and hydrogen) and fuel cell reactions contribute to contrail formation. What is the potential climactic effect of contrails?
Optional extension: How can manufacturers and airlines act to reduce water emissions and contrail formation – both for standard combustion of jet fuel and future hydrogen solutions?
Discussion: Based on your findings, which hydrogen propulsion technology would you recommend to the management team?
So far we have considered each aspect of the hydrogen debate in isolation. However, it is important to consider the overall environmental impact of these stages as a whole. Choices made at each stage of the hydrogen cycle – generation, storage, usage – will collectively impact the overall environmental impact and sustainability of using hydrogen as an aviation fuel and demonstrates how interconnected our decisions can be.
Activity: Assign students to groups based on the stage of a hydrogen lifecycle (generation, storage/transport, usage). Each group could research and discuss the potential emissions and environmental impacts associated with their assigned stage. Consider both direct and indirect emissions, like energy used in production processes or emissions related to infrastructure development. Principles such as life cycle assessment can be incorporated for a holistic view of hydrogen emissions.
Activity: After the individual group discussions, each group could present their findings and perspectives on their stage of the lifecycle. The whole class could then reflect on the overall environmental impacts of hydrogen in aviation. How do these impacts compare across different stages of the lifecycle? What are the trade-offs involved in choosing different types of hydrogen (green, blue, grey) and storage/transportation solutions?
Discussion: Conclude with a reflective discussion. Students bring together their findings on the life cycle stages of hydrogen and present their overall perspectives on the environmental sustainability of using hydrogen in aviation.
Part five: Hydrogen aviation stakeholders
Hydrogen aviation is an area with multiple stakeholders with conflicting priorities. Understanding the perspectives of these key players is important when considering the feasibility of hydrogen in the aviation sector.
Activity: Who are the key players in this scenario? What are their positions and perspectives? How can you use these perspectives to understand the complexities of the situation more fully?
Your consultancy firm is hosting a debate for the aviation industry in order to help them make a decision around hydrogen-based technologies. You have invited representatives from consumer groups, the UK government, Environmental NGOs, airlines, and aircraft manufacturers.
Activity: Take on the role of these key stakeholders, ensuring you understand their perspective and priorities. This could form part of a separate research exercise, or students can use the key points given below. Debate whether or not hydrogen fuel should be used to help the aviation sector reach net zero.
Stakeholder
Key priorities and considerations
Airline & Aerospace Manufacturer
Cost efficiency (fuel, labour, fleet maintenance) – recovering from pandemic.
Passenger experience (commercial & freight).
Develop & maintain global supply chains.
Safety, compliance and operational reliability.
Financial responsibility to employees and investors.
Need government assurances before making big capital investments.
UK Government
Achieve net zero targets by 2050
Promote economic growth and job creation (still recovering from pandemic).
Fund research and innovation to put their country’s technology ahead.
Fund renewable infrastructure to encourage industry investment.
Environmental NGOs
Long-term employment for aviation sector.
Demand a sustainable future for aviation to ensure this – right now, not in 50 years.
Standards and targets for industry and government and accountability if not met.
Some NGOs support drastic cuts to flying.
Want to raise public awareness over sustainability of flying.
Consumer
Environmentally aware (understand the need to reduce carbon emissions).
Also benefit greatly from flying (tourism, commercial shipping, etc.).
Safety and reliability of aircraft & processes.
Cost effectiveness – want affordable service
Appendix: Example calculations
There are multiple methods for approaching these calculations. The steps shown below are just one example for illustrative purposes.
Part two: Hydrogen production
Challenge: Estimate the volume of water required for a hydrogen-powered aircraft.
Assumptions around the hydrogen production process, aircraft, and fuel requirement can be given to students or researched as a separate task. In this example we assume:
All hydrogen is generated via electrolysis of fresh water with an efficiency of 100%.
A mid-size aircraft required with ~300 passenger capacity and flight range of ~3500 nmi (London to New York).
Flight energy requirement for a kerosene-fuelled jet is the same as a hydrogen-fuelled jet.
Example estimation:
1. Estimate the energy requirement for a mid-size jet
No current hydrogen-fuelled aircraft exists, so we can use a kerosene-fuelled analogue. Existing aircraft that meet the requirements include the Boeing 767 or 747. The energy requirement is then:
2. Estimate the hydrogen requirement
Assuming a hydrogen plane has the same fuel requirement:
3. Estimate the volume of water required
Assuming all hydrogen is produced from the electrolysis of water:
Electrolysis reaction:
For this reaction, we know one mole of water produces one mole of hydrogen. We need to calculate the moles for 20,000 kg of hydrogen:
With a 1:1 molar ratio, we can then calculate the mass of water:
This assumes an electrolyser efficiency of 100%. Typical efficiency values are under 80%, which would yield:
Challenge: Is it feasible to power the UK aviation fleet with water?
The total energy requirement for UK aviation can be given to students or set as a research task.
Estimation can follow a similar procedure to the above.
Multiple methods for validating and assessing the feasibility of this quantity of water. For example, the UK daily water consumption is 14 billion litres. The water requirement estimated above is < 1 % of this total daily water consumption, a finding supported by FlyZero.
Part three: Hydrogen storage
Challenge: Is it feasible to store 20,000 kg of hydrogen in an aircraft?
There are multiple methods of determining the feasibility of storage volume. As example is given below.
1. Determining the storage volume
The storage volume is dependent on the storage method used. Density values associated with different storage techniques can be research or given to students (included in Table 2). The storage volume required can be calculated from the mass of hydrogen and density of storage method, example in Table 2.
Table 2: Energy densities of various hydrogen storage methods
2. Determining available aircraft volume
A straightforward method is to compare the available volume on an aircraft with the hydrogen storage volume required. Aircraft volumes can be given or researched by students. Examples:
This assumes hydrogen tanks are integrated into an existing aircraft design. Liquid hydrogen can feasibly fit into an existing design, though actual volume will be larger due to space/constraint requirements and additional infrastructure (pipes, fittings, etc) for the tanks. Tank size can be compared to conventional kerosene tanks and a discussion encouraged over where in the plane hydrogen tanks would need to be (conventional liquid fuel storage is in the wings of aircraft, this is not possible for liquid storage tanks due to their shape and infrastructure storage is inside the fuselage). Another straightforward method for storage feasibility is modelling the hydrogen volume as a simple cylinder and comparing to the dimensions of a suitable aircraft.
Any views, thoughts, and opinions expressed herein are solely that of the author(s) and do not necessarily reflect the views, opinions, policies, or position of the Engineering Professors’ Council or the Toolkit sponsors and supporters.
Sustainability competency: Self-awareness; Normative. UNESCO has developed eight key competencies for sustainability that are aimed at learners of all ages worldwide. Many versions of these exist, as are linked here*. In the UK, these have been adapted within higher education by AdvanceHE and the QAA with appropriate learning outcomes. The full list of competencies and learning outcome alignment can be found in the Education for Sustainable Development Guidance*. *Click the pink ''Sustainability competency'' text to learn more.
AHEP mapping: This resource addresses two of the themes from the UK’s Accreditation of Higher Education Programmes fourth edition (AHEP4): The Engineer and Society (acknowledging that engineering activity can have a significant societal impact) and Engineering Practice (the practical application of engineering concepts, tools and professional skills). To map this resource to AHEP outcomes specific to a programme under these themes, access AHEP 4 here and navigate to pages 30-31 and 35-37.
Related SDGs: SDG 4 (Quality education); SDG 13 (Climate action).
Reimagined Degree Map Intervention: More real-world complexity; Active pedagogies and mindset development; Cross-disciplinarity.The Reimagined Degree Map is a guide to help engineering departments navigate the decisions that are urgently required to ensure degrees prepare students for 21st century challenges. Click the pink ''Reimagined Degree Map Intervention'' text to learn more.
Who is this article for? This article should be read by educators at all levels in higher education who are seeking to apply an approach of teaching with case studies in order to reveal the links between ethics and sustainability. Engaging with this topic will also help to prepare students with the soft skill sets that employers are looking for.
As environmental pressures mount, the world demands not just engineering solutions, but sustainable ones. This shift presents profound challenges and opportunities for engineering educators. How can we equip future engineers with the ethical frameworks and critical thinking skills needed to navigate the complex trade-offs inherent in green solutions?
This article provides a guide for integrating ethical considerations into engineering education by using case studies. By fostering awareness of sustainability principles and promoting responsible decision-making through real-world examples, we can empower students to become stewards of a more equitable and resilient future.
The interplay of ethics and sustainability:
At its core, sustainability goes beyond environmental impact. It encompasses social responsibility, economic viability, and intergenerational equity. Ethical engineering aligns with these principles by:
Prioritising transparency and honesty: Green solutions shouldn’t mask potential downsides or mislead stakeholders.
Respecting all stakeholders: Engineers must consider the needs and voices of local communities, indigenous populations, and future generations.
Envisioning long-term consequences: Solutions conceived with short-term gain in mind can have unforeseen environmental and social repercussions.
Integrating ethical considerations into engineering curricula presents several challenges:
Balancing economic pressures: Sustainable solutions don’t always align with immediate cost-effectiveness. Educators must help students navigate these complex trade-offs and advocate for long-term benefits.
Fostering interdisciplinary collaboration: Sustainability demands diverse perspectives. Educators can encourage partnerships with ecologists, sociologists, and other experts to enrich student understanding.
Staying updated with evolving technologies: The sustainability landscape is dynamic. Educators must themselves embrace continuous learning to ensure their curriculum reflects the latest developments and potential ethical dilemmas.
Learning from a case study:
The sprawling Ivanpah Solar Electric Generating System in California’s Mojave Desert, initially celebrated as a beacon of clean energy, now casts a complex shadow on the region’s ecological landscape. While harnessing the sun’s power to electrify millions, its concentrated solar technology inadvertently unleashed unintended consequences. The intense heat generated by the mirrors tragically claimed thousands of birds, particularly desert tortoises, a threatened species. Drawn to the shimmering light, they would collide with the mirrors or structures, falling victim to a technological mirage. This stark reality challenged the “green” label of a project originally intended to combat climate change.
Unforeseen costs of progress:
Ivanpah’s case highlights the hidden costs of even well-intentioned renewable energy projects. It sparks critical questions for students to grapple with:
Sustainability beyond carbon emissions: While reducing carbon footprint is crucial, broader ecosystem impacts must be considered. Can technological advancements mitigate harm to vulnerable species and habitats?
Balancing energy needs with ecological needs: How can we find the sweet spot between harnessing renewable energy and preserving biodiversity? Can alternative technologies or site selection minimise ecological disruption?
Engaging stakeholders in ethical decision-making: How can local communities and ecological experts be meaningfully included in planning and mitigation strategies to ensure equitable outcomes?
By delving into the Ivanpah case (and others like it*), students can develop critical thinking skills to analyse the long-term implications of seemingly green solutions. They learn to consider diverse perspectives, advocate for responsible design practices, and prioritise environmental stewardship alongside energy production.
As educators, we hold the power to shape the ethical compass of future engineers. By integrating ethical considerations into the fabric of our curriculum, we can equip them with the tools and knowledge necessary to:
Make informed decisions: Students should learn to analyse solutions through the lens of ethics, considering environmental impact, social responsibility, and economic viability.
Engage in open dialogue: Cultivating a culture of critical thinking and open communication is crucial for addressing diverse perspectives and mitigating potential ethical concerns.
Collaborate ethically: Students should understand the importance of interdisciplinary collaboration, respecting diverse expertise and working towards shared goals that benefit all stakeholders.
Conclusion:
The pursuit of a sustainable future demands ethical engineers, engineers who can not only innovate, but also act with integrity and responsibility. By equipping students with the knowledge and skills necessary to grapple with complex ethical dilemmas, we can empower them to become transformative agents of change, shaping a world that thrives for generations to come.
References:
Delong, D. (2012). ‘Sustainable engineering: A comprehensive introduction’. John Wiley & Sons.
Any views, thoughts, and opinions expressed herein are solely that of the author(s) and do not necessarily reflect the views, opinions, policies, or position of the Engineering Professors’ Council or the Toolkit sponsors and supporters.
Professional situations: Rigour; Informed consent; Misuse of data.
Educational level: Intermediate.
Educational aim: Gaining ethical knowledge. Knowing the sets of rules, theories, concepts, frameworks, and statements of duty, rights, or obligations that inform ethical attitudes, behaviours, and practices.
Learning and teaching notes:
This case study involves an engineer hired to develop and install an Industrial Internet of Things (IIoT) online machine monitoring system for a manufacturing company. The developments include designing the infrastructure of hardware and software, writing the operation manuals and setting policies. The project incorporates a variety of ethical components including law and policy, stakeholders, and risk analysis.
This case study addresses three of the themes from the Accreditation of Higher Education Programmes fourth edition (AHEP4): Design and Innovation (significant technical and intellectual challenges commensurate the level of study), the Engineer and Society (acknowledging that engineering activity can have a significant societal impact) and Engineering Practice (the practical application of engineering concepts, tools, and professional skills). To map this case study to AHEP outcomes specific to a programme under these themes, access AHEP 4 hereand navigate to pages 30-31 and 35-37.
The dilemma in this case is presented in three parts. If desired, a teacher can use Part one in isolation, but Part two and Part three develop and complicate the concepts presented in Part one to provide for additional learning. The case study allows teachers the option to stop at multiple points for questions and/or activities as desired.
Learners have the opportunity to:
apply their ethical judgement relating to privacy and consent on the use of machine data;
determine the societal impact of a technical solution to a complex problem;
analyse risks associated with ethical concerns and justify their ethical decisions;
communicate these risks and judgements to both technical and non-technical audiences.
Teachers have the opportunity to:
highlight a range of ethical considerations within the scope of a complex engineering project;
introduce methods for risk analysis and ethical decision-making;
link Engineering Council statements of ethical principles with real world situations;
IIoT is a new technology that can provide accurate condition monitoring and predict component wear rates to optimise machine performance, thereby improving the machining precision of the workpiece and reducing the production cost.
Oxconn is a company that produces auto parts. The robotic manipulators and other automation machines on the production line have been developed at considerable cost and investment, and regular production line maintenance is essential to ensure its effective operation. The current maintenance scheme is based on routine check tests which are not reliable and efficient. Therefore Oxconn has decided to install an IIoT-based machine condition monitoring system. To achieve fast responses to any machine operation issues, the machine condition data collected in real time will be transferred to a cloud server for analysis, decision making, and predictive maintenance in the future.
Dilemma – Part one – Data protection on customers’ machines:
You are a leading engineer who has been hired by Oxconn to take charge of the project on the IIoT-based machine monitoring system, including designing the infrastructure of hardware and software, writing the operation manuals, setting policies, and getting the system up and running. With your background in robotic engineering and automation, you are expected to act as a technical advisor to Oxconn and liaise with the Facilities, Security, Operation, and Maintenance departments to ensure a smooth deployment. This is the first time you have worked on a project that involves real time data collection. So as part of your preparation for the project, you need to do some preliminary research as to what best practices, guidance, and regulations apply.
Optional STOP for questions and activities:
1. Discussion: What are the legal issues relating to machine condition monitoring? Machines’ real-time data allows for the identification of production status in a factory and is therefore considered as commercial data under GDPR and the Data Protection Act (2018). Are there rules specifically for IIoT, or are they the same no matter what technology is being used? Should IIoT regulations differ in any way? Why?
2. Discussion: Sharing data is a legally and ethically complex field. Are there any stakeholders with which the data could be shared? For instance, is it acceptable to share the data with an artificial intelligence research group or with the public? Why, or why not?
3. Discussion: Under GDPR, individuals must normally consent to their personal data being processed. For machine condition data, how should consent be handled in this case?
4. Discussion: What ethical codes relate to data security and privacy in an IIoT scenario?
5. Activity: Undertake a technical activity that relates to how IIoT-based machine monitoring systems are engineered.
6. Discussion: Based on your understanding of how IIoT-based machine monitoring systems are engineered, consider what additional risks, and what kind of risks (such as financial or operational), Oxconn might incur if depending on an entirely cloud-based system. How might these risks be mitigated from a technical and non-technical perspective?
Dilemma – Part two – Computer networks security issue brought by online monitoring systems:
The project has kicked off and a senior manager requests that a user interface (UI) be established specifically for the senior management team (SMT). Through this UI, the SMT members can have access to all the real-time data via their computers or mobiles and obtain the analysis result provided by artificial intelligence technology. You realise this has implications on the risk of accessing internal operating systems via the external information interface and networks. So as part of your preparation for the project, you need to investigate what platforms can be used and what risk analysis must be taken in implementation.
Optional STOP for questions and activities:
The following activities focus on macro-ethics. They address the wider ethical contexts of projects like the industrial data acquisition system.
1. Activity: Explore different manufacturers and their approaches to safety for both machines and operators.
2. Activity: Technical integration – Undertake a technical activity related to automation engineering and information engineering.
3. Activity: Research what happens with the data collected by IIoT. Who can access this data and how can the data analysis module manipulate the data?
4. Activity: Develop a risk management register, taking considerations of the findings from Activity 3 as well as the aspect of putting in place data security protocols and relevant training for SMT.
5. Discussion/activity: Use information in the Ethical Risk Assessment guide to help students consider how ethical issues are related to the risks they have just identified.
6. Discussion: In addition to cost-benefit analysis, how can the ethical factors be considered in designing the data analysis module?
7. Activity: Debate the appropriateness of installing and using the system for the SMT.
8. Discussion: What responsibilities do engineers have in developing these technologies?
Dilemma – Part three – Security breach and legal responsibility:
At the beginning of operation, the IIoT system with AI algorithms improved the efficiency of production lines by updating the parameters in robot operation and product recipes automatically. Recently, however, the efficiency degradation was observed, and after investigation, there were suspicions that the rules/data in AI algorithms have been subtly changed. Developers, contractors, operators, technicians and managers were all brought in to find out what’s going on.
Optional STOP for questions and activities:
1. Discussion: If there has been an illegal hack of the system, what might be the motive of cyber criminals?
2. Discussion: What are the impacts on company business? How could the impact of cyber-attacks on businesses be minimised?
3. Discussion: How could threats that come from internal employees, vendors, contractors or partners be prevented?
4. Discussion: When a security breach happens, what are the legal responsibilities for developers, contractors, operators, technicians and managers?
Any views, thoughts, and opinions expressed herein are solely that of the author(s) and do not necessarily reflect the views, opinions, policies, or position of the Engineering Professors’ Council or the Toolkit sponsors and supporters.
Author: Peter Beattie (Ultra Group).
Topic: Dealing with contracts or subcontracts with potential slave or forced labour.
Ethical issues: Social responsibility; Human rights; Risk.
Professional situations: Legal implications; Company/organisational reputation; Conflicts with leadership/management.
Educational level: Beginner.
Educational aim: Practising Ethical Reasoning: the application of critical analysis to specific events in order to evaluate and respond to problems in a fair and responsible way.
Learning and teaching notes:
This case study puts students in the shoes of an engineer who is required to select a subcontractor to manufacture systems and parts. There are stipulations around who can be selected, among which are legal and ethical concerns around suspicions of slavery or forced labour. The engineer must navigate communication with both their supervisors and their potential subcontractor, and ultimately justify their decision.
This case study addresses two of the themes from the Accreditation of Higher Education Programmes fourth edition (AHEP4): The Engineer and Society (acknowledging that engineering activity can have a significant societal impact) and Engineering Practice (the practical application of engineering concepts, tools and professional skills). To map this case study to AHEP outcomes specific to a programme under these themes, access AHEP 4 here and navigate to pages 30-31 and 35-37.
The case is presented in three parts. If desired, a teacher could use the Summary and Part one in isolation, but Parts two and three enable additional professional situations to be brought into consideration. The case study allows teachers the option to stop at multiple points for questions and/or activities as desired.
Learners have the opportunity to:
analyse ethical dimensions and complexities of a professional situation;
analyse risks associated with potentially questionable practice, considering short- and long-term consequences to both business and social interests;
make and justify an ethical decision;
communicate these risks and judgements to public and business audiences.
Teachers have the opportunity to:
highlight the ethical considerations within business and supply chain decisions relating to an engineering project;
introduce or reinforce concepts and methods related to risk analysis and ethical decision-making;
evaluate critical thinking, argumentation, and/or communication skills.
Autonomous Vehicle Corporation (AVC) has recently been awarded a contract to provide a bespoke design unmanned air vehicle to India. AVC is a UK certified B Corp that prides itself on maintaining the highest standards of social and environmental performance, transparency, and accountability.
A stipulation of the newly awarded contract is that at least 30% of the contract value is spent on the manufacture of sub-systems and parts from subcontractors based in India. AVC is responsible for identifying and contracting these suppliers.
After many years working as a Systems Engineer for AVC, you have been selected as the Lead Engineer for the project, responsible for the selection of the Indian suppliers. You are aware from your initial research of reports regarding slave and forced labour in the region’s manufacturing industry and are concerned that this situation might affect the project and the company. Additionally, you would personally feel uncomfortable knowing that you might contract a supplier who engaged in those practices.
Optional STOP for questions and activities:
1. Activity: To consider how AVC might be impacted from engaging a supplier that utilises slave or forced labour, chart out the viewpoints of different stakeholders, such as customers, investors, other suppliers, communities, and employees.
2. Discussion: Are there other factors besides ethical considerations that may influence your selection of supplier? What are these?
3. Discussion: How would you weigh the importance of ethical considerations, such as the use of slave or forced labour, against the other factors identified in the previous question? What information or resources might you use in guiding your weighting of these considerations?
4. Activity: Contrast the UK Engineering Council’s code of ethics with the Engineering Council of India’s Code of Ethics. How do the two differ? Which code should you be primarily guided by in this situation? Why? How might cultural expectations and norms influence what is seen as ethical?
Dilemma – Part one:
One supplier you are considering is Quality Electronics Manufacturing Pvt. Ltd. (QEM), a company based outside Naya Raipur in one of India’s poorest provinces. During a video call, QEM’s managing director assures you that they comply with a strict code of ethics and conduct all recruitment through a carefully selected list of brokers and agencies. He tells you that QEM sources raw materials from around the world, and none of their suppliers have ever been convicted of any offences relating to slavery. He invites you to tour their factory when you are in the country next month and will personally escort you to answer any questions you may have.
Optional STOP for questions and activities:
1. Activity: Does anything you have heard give you cause for concern regarding the risk of slave or forced labour at QEM in particular? Research this issue from the perspective of various sources, such as investigative journalism, academic papers, government reports, and industry publications. Do their conclusions align or differ in any significant ways? Are there any gaps in knowledge that these sources haven’t adequately covered?
2. Discussion: QEM mentions that they source raw materials from around the world. The reality of modern supply chains is that they often involve multiple complex layers of subcontractors. Does AVC have an ethical duty to consider the whole supply chain? Would this be the same if AVC were further down the supply chain? If AVC were further down the supply chain, would they have to consider the upstream elements of the supply chain? What are the business implications of considering an entire supply chain?
3. Activity: List possible contextual risk factors and potential indicators of slave and forced labour. Which are present in the case of QEM?
4. Activity and discussion: Create a set of questions you wish to answer during your visit to QEM to help assess the risk that they are engaged in the use of slave or forced labour. How will you get this information? Who will you need to talk to? What evidence would you expect to see and collect? To practise business communication, students could draft a memo to their supervisor explaining the situation and outlining their proposed course of action.
Dilemma – Part two:
During your visit to QEM’s factory, you meet with workers at all levels and you review QEM’s policies and procedures. You identify some potential risk factors that could indicate QEM is using forced labour in its workforce. You raise this with QEM’s managing director, but he responds indignantly, “QEM creates good jobs for our workers and without us they would not be able to feed their families. Your contract would allow us to sustain those jobs and create many more for the local community.”
You know that QEM is the lowest cost supplier for the work you want them to undertake, and you are under pressure to keep budgets down. You have no conclusive evidence that QEM uses forced labour. You also know that the alternative suppliers you could use are all based in regions with high employment, which means the risk of not being able to staff your work (resulting in schedule delays) is high.
Upon your return to the UK, your project manager calls you into her office and tells you she needs your decision on whether to utilise QEM by the end of the week.
Optional STOP for questions and activities:
1. Activity: Conduct a risk analysis that identifies what might be the impact of not using QEM and what might be the impact of using QEM.
2. Debate: Do you use QEM as one of your suppliers? Why, or why not? You may wish to consider your answer using the lens of uncertainty and risk.
3. Discussion: What actions could you put in place with QEM to reduce the incidence/risk of slave or forced labour in its workforce? Which of these would you recommend, and which would you require, QEM to implement as part of contracting with them? How would you enforce them, and what evidence of them being successfully implemented would you need?
Dilemma – Part three – Postscript:
If you chose to use QEM: It is now two years after you subcontracted QEM. An investigation by an NGO has uncovered the rampant use of slave and forced labour within the global electronics manufacturing industry by companies with B-Corp status. AVC is named as one of the perpetrators, and a story about workers at QEM is scheduled to run in a leading tabloid newspaper tomorrow morning. AVC has called an emergency press conference to give its side of the story.
If you chose not to use QEM: The following week, your project manager calls you into her office again. She tells you that she has just stepped out of a meeting with the board, and they are deeply concerned about spiralling costs on your project. In particular, they are concerned that you rejected QEM’s proposal in favour of another supplier who is more than twice as expensive. You have been asked to present your reasoning to the board when they reconvene shortly.
Optional STOP for activity:
1. Roleplay either the press conference or the board meeting and defend your decision.
Any views, thoughts, and opinions expressed herein are solely that of the author(s) and do not necessarily reflect the views, opinions, policies, or position of the Engineering Professors’ Council or the Toolkit sponsors and supporters.
Toolkit: Complex Systems Toolkit.
Authors: