Optimisation is key to the improvement of most engineering products. Although the concepts of optimisation date back thousands of years, Computer Aided Engineering (CAE) based optimisation has only been widely developed over the past twenty years or so. Most conventional optimisation algorithms focus on a single application with a single goal (objective); for example, minimising the mass of a vehicle crash structure, or maximising the profit margin of a specific product. Although these objectives are different in nature they relate to the same product; and most often also indirectly influence each other, making the individual optimisation “less efficient”. Multi-objective optimisation algorithms do exist; but multi-objective and multi-disciplinary algorithms are neither well developed nor well understood. The overarching research question for this PhD study is: How to optimise an engineering product from a holistic viewpoint? The ideology of holistic optimisation is to obtain the ideal product by determining the optimum “compromise” between a number of indirectly linked aspects, such as structural performance and manufacturing costs. The ultimate aim, and the original contribution to knowledge of this PhD is to create a holistic optimisation algorithm / tool able to cater for the above. This will include aspects such as material selection, manufacturing methods, structural performance, end of life attributes, life cycle assessment, product cost, CO2equivalence, etc. The approach is to utilise a parametric model to analyse and optimise the overall “performance” of the product. Two different approaches to holistic optimisation will be evaluated: parallel and sequential. The ideology of the parallel approach is to optimise the aspects independently of each other. The sequential approach optimises the aspects sequentially with varying priorities.
|Date of Award||Jul 2018|
|Supervisor||Jesper Christensen (Supervisor)|