Manufacturing cost based methodologies for design optimisation

Rao, A. (2006) Manufacturing cost based methodologies for design optimisation. University of Southampton, School of Engineering Sciences, Doctoral Thesis, 202pp.

Abstract

The objective of this research is to develop a methodology for incorporating cost models based on manufacturing process information within multidisciplinary design optimisation problems. Although cost considerations are critical in product design and development, cost models are rarely used in optimising designs mainly due to the inability in acquiring accurate manufacturing cost estimates in early design. In this thesis, we present a new technique for embedding manufacturing process knowledge within a modelling tool which can be utilised to provide accurate cost estimates in design optimisation applications. We use the proposed cost estimating technique for optimising the geometry of two components from a Rolls-Royce civil aircraft engine by designing a sequential workflow consisting of CAD, analysis and cost models along with optimisation algorithms within an integrated system. Initial results from the first component (which is treated as a model problem) show that significant cost savings as well as shape changes can be achieved by using an accurate cost model in the objective function. The second case study dealt with is the shape optimisation of the initial 2D profile of a high pressure turbine disc. We develop highly flexible geometry parameterisation schemes to accurately represent manufacturing, supplier and inspection constraints inherent in the cost model for the disc. Significant differences in the geometry are achieved when the design is optimised for low manufacturing cost as compared to traditional weight minimisation leading to the second part of this thesis that deals with the hypothesis that low volume and low cost are conflicting attributes. Multiobjective optimisation approaches are then utilised to generate a Pareto front of designs with optimum combinations of both objectives. We then proceed to list the obstacles which prevent a straightforward application of multiobjective techniques to sophisticated design problems and propose modifications which enhance the quality of results achieved. Finally, a flowchart detailing the design optimisation framework used in this thesis is described for the benefit of future applications. We then conclude by stating the salient contributions of this work and interesting avenues of future research that can be pursued.

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Contributors

Thesis advisor: A.J. Keane

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