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Response surface methodology (RSM) is applied to data analysis for experimental models to determine the optimal tolerance design in an assembly. RSM is a combination of mathematical and statistical techniques, which provides designers with not only optimal tolerance values but also the critical components of an assembly. This feature is very important during the design activities as it enables designers to have feedback and suggestions for design improvement. To develop an economical and quality product, the response variable is the total cost which consists of quality loss and tolerance cost in this study. Most of the literature on this subject assumes that the assembly function is known before a tolerance design problem is analysed. With the current development in CAD (computer-aided design) software, design engineers can proceed with tolerance design problems without knowing assembly functions in advance. In this study, the Monte Carlo simulation is employed using VSA-3D/Pro software to obtain experimental data, followed by RSM to optimize and analyse computer results. Consequently, a tolerance design for quality improvement and cost reduction can be achieved for any complex assembly at the early stages of design.
Angus Jeang (Wed,) studied this question.