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Abstract

Systematic design methodologies can produce good products particularly where complexity, teamwork and avoiding costly errors are concerned. In this thesis two accepted methodologies have been developed and they are linked to improved design parameter selection in the context of four industrial case studies.

Robust Engineering Design of a product minimises performance variability over its lifecycle; this approach is dependent upon the appropriate selection and configuration of design parameters. Two energy-based approaches have been developed in this research and shown to provide valuable insights. The means for using parameter values from standard production runs have been demonstrated and has incorporated adjustments for unbalanced noise conditions. In addition, a technique for handling multiple objectives has been shown to provide an incentive for continuous improvement based upon competitive benchmarking.

Quality Function Deployment, which processes multiple objectives, has historically been underexploited in terms of the correlations between design parameters. In this thesis enhancements have been made to incorporate identification of causal relationships. This has enabled a graphical representation of the design procedure which clarifies information flow and deepens the understanding of the design problem. Design retrieval has also been enhanced since causal information about parameters can be stored in the correlation roof.

Publication Type:	Thesis (Doctoral)
Subjects:	T Technology > TA Engineering (General). Civil engineering (General)
Departments:	School of Science & Technology > Engineering School of Science & Technology > School of Science & Technology Doctoral Theses Doctoral Theses

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