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ME40358: Design optimisation project

[Page last updated: 27 October 2020]

Follow this link for further information on academic years Academic Year: 2020/1
Further information on owning departmentsOwning Department/School: Department of Mechanical Engineering
Further information on credits Credits: 6      [equivalent to 12 CATS credits]
Further information on notional study hours Notional Study Hours: 120
Further information on unit levels Level: Masters UG & PG (FHEQ level 7)
Further information on teaching periods Period:
Semester 1
Further information on unit assessment Assessment Summary: CW 60%, OR 40%
Further information on unit assessment Assessment Detail:
  • Project Proposal (CW 20%)
  • Final Report (CW 40%)
  • Prototype Presentation (OR 40%)
Further information on supplementary assessment Supplementary Assessment:
ME40358 - Reassessment coursework (where allowed by programme regulations)
Further information on requisites Requisites:
Description: 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 strip down a product/part and identify its 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.

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.

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).

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: FEA/topology optimisation, materials selection software, general purpose optimisation toolboxes (MATLAB), etc. Practical approaches for the optimisation task include: instrumentation and data analysis techniques using Labview or Matlab. Students will be given a product and tasked with improving an aspect of its performance. In teams of two, students will use simulation to rapidly iterate through design changes to improve the performance of their product. Students will then verify their predicted product performance by building suitable physical models for testing.
Further information on programme availabilityProgramme 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)