ME40358: Design optimisation project
[Page last updated: 03 August 2022]
| Academic Year: | 2022/23 |
| Owning Department/School: | Department of Mechanical Engineering |
| Credits: | 6 [equivalent to 12 CATS credits] |
| Notional Study Hours: | 120 |
| Level: | Masters UG & PG (FHEQ level 7) |
| Period: |
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| Assessment Summary: | CW100 |
 Assessment Detail: |
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| Supplementary Assessment: |
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| Requisites: | |
| Learning Outcomes: | After successfully completing this unit a student will be able to:
* Propose a design optimisation project by identifying, in quantifiable terms, the performance parameters of a product/part, taking into account factors such as budget and timescale. * Identify constraints and freedoms, objectives and performance indices that may be used to describe and then optimise a design. * Identify appropriate experimentation or optimisation techniques to use in conjunction with a design problem, comparing the merits and drawbacks of each feasible method. * Evaluate (quantitatively) by experimentation or practical testing the effect of the approach they have selected, demonstrating their product's/part's performance compared to a previously established baseline. * Reflect on design trade-offs that have been identified and report on how this new knowledge would influence further design iterations. |
| Aims: | This unit aims to: Develop expertise in design optimisation theory, including problem description techniques, design and solution spaces, optimisation using (measurement) data, optimisation solvers and design trade-offs. Introduce the theory of Generative Design and its relationship with design optimisation. Develop a student's ability to identify key performance metrics, which will subsequently be used in optimisation. Develop a student's ability to use tools and techniques to measure the performance of a design using simulation or experimentation, such that they can optimise a design through iteration. |
| Skills: | Problem solving and data analysis (T/F/A); Design Optimisation theory, tools and methods (T); Product specification construction (F/A); team working (F/A); practical product improvement skills (F/A); presentation skills (T/A); written communication (A). |
| Content: | The unit will include taught content on Design Optimisation theory (simulation-based optimisation, experimental optimisation, Design of Experiments, generative design, etc.) and introductions to specific tools. Computer aided optimisation tools include: Finite Element optimisation, general purpose optimisation toolboxes (MATLAB), etc. Practical approaches for the optimisation task include: instrumentation and data analysis techniques using MATLAB. Students will use simulation to rapidly iterate through design changes to improve the performance of a product. Students will then verify their predicted product performance by building suitable physical models for testing. |
| Programme availability: |
ME40358 is Compulsory on the following programmes:Department of Mechanical Engineering
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