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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)
Semester 1
Assessment Summary: CW100
Further information on unit assessment Assessment Detail:
  • Assessment detail data for this unit is currently being updated as a change has been approved. Updated assessment information will be published here shortly.
Supplementary Assessment:
ME40358 - Reassessment coursework (where allowed by programme regulations)
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
  • UEME-AFM48 : MEng(Hons) Integrated Design Engineering (Year 4)
  • UEME-AKM48 : MEng(Hons) Integrated Design Engineering with Year long work placement (Year 5)


  • This unit catalogue is applicable for the 2022/23 academic year only. Students continuing their studies into 2023/24 and beyond should not assume that this unit will be available in future years in the format displayed here for 2022/23.
  • Programmes and units are subject to change in accordance with normal University procedures.
  • Availability of units will be subject to constraints such as staff availability, minimum and maximum group sizes, and timetabling factors as well as a student's ability to meet any pre-requisite rules.
  • Find out more about these and other important University terms and conditions here.