Engineering Design Practice in 2040: Implications for OU Teaching

1. What will engineering design practice be like in 2040?Implications for OU teaching Prof Claudia Eckert Prof Ola Isaksson, System Engineering Design, Chalmers

2. Motivation • Underlying future trends are analysed from multiple angles • Societal: e.g. globalisation, aging population, migration • Environmental: e.g. climate change, resource availability • Technological: e.g. industry 4.0, nanotechnology • What does this mean for engineering practise over the next 20 years? • What does this mean for engineering education to support practise? • What does this mean for OU teaching?

3. Our approach • Ask experienced engineers how they think engineering design will change • Focus on the practise of product development of complex products • Generational products, incremental development • Connected to other products and services • Multi-disciplinary, but currently still controlled largely by the original disciplines • Some of the policy intensions for 2040 are already launched

4. Methodology

5. Interviewees

6. The interviews • Past and present research collaborators • 8 – 35 years of experience in senior product development roles, e.g. system architects, strategic problem planers, engineering team leaders etc. • Questions centred around • What trends do you see? • What skills will be required? • How can academia help? • Teaching • Tools and method development

7. Trends based on the interviews

8. Trends • Transportation • Integrated transport solutions • In service data gathering • Order of innovation creates path dependency • New business models emerging • Energy • Battery used in multiple products • Regulation and funding regimes affect energy mix • System architecture • Legacy systems plus innovation • Sharing of components

9. Engineering practise • Discipline blending: mechanical, electrical, software, systems, mathematics, statistics, data science, material science • Trade-offs • Representations • Collaboration skills • New and enhanced skills • Better system thinking • More numerate • Understanding diverse markets • Expertise • Deep subject matter expertise need to be complemented with systems and generalist thinking. • People don’t stay long enough to become subject matter experts. • Process • Trend away from prescriptive processes to greater flexibility • More design engineers, fewer production people

10. Conflicting trends • Efficiency vs flexibility • Optimization vs innovation • Current company would have the money to fund radical concepts • Optimization vs remanufacturablity • Individualization (travel from A to B) vs standardization of modules • Industry needs specialists and generalists

11. Trends from the workshop

12. Workshop Participants

13. Workshop • Hosted by GoCo innovation cluster • Senior engineers largely from Sweden • International academics • Interview finding circulated before hand • Introduction talk on interview findings and sustainability predictions

14. Technology Trends • Technology • Artificial Intelligence and Augmented / Virtual Reality • Increased computational power, quantum computing • Cyberphysical products pose challenge in cybersecurity • Additive Manufacturing • New smart materials • Modelling and Simulation • Flexible working, organise tasks and workflow • Digital twins • Virtual testing • Gamification of design

15. Soft trends • Society • Sustainability principles will become main stream • Circular economy, nexus, upgrade, repair etc. • Clearer regulation • Ways of working • Cross disciplinary, diverse teams including robots / Ais • Small core teams and gigging engineers • Beyond stage gate • Life long learning • Individual ownership of life long learning • New forms of university / industry collaboration

16. Observation on OU and trends • OU teaching is already doing very well • Remote teaching prepare engineers for remote working • Interdisciplinary engineering • Sustainability well integrated into curriculum • OU has some weaknesses • Exposure of students to complex engineering processes • Modelling and simulation only gradually introduced • High degree of mathematical competency don’t be assumed

17. Potential for OU courses • Introduction of a AI / big data pathway in collaboration with maths and computing • Increased literacy in • AI • Modelling • Data management • Specific cross disciplinary training, e.g. cross disciplinary team projects • Clearer positioning in generalist – specialist spectrum • Teach remote collaboration explicitly

18. Reflections • OU courses designed now will run to 2030 • We need to prepare the students for the trends that are coming • We should engage with employers about the skills that they expect to need • Draw on the research connection to gain access to experts