Kumar, A., Keane, A.J., Nair, P.B. and Shaphar, S.
Efficient robust design for manufacturing process capability.
In, 6th ASMO-UK/ISSMO International Conference on Engineering Design Opimization, Oxford, UK,
03 - 04 Jul 2006.
The presence of process variations in manufacturing any product is inevitable. Manufacturing variations can result in performance loss, high scrap, rdesign and product failure. This paper proposes a methodology for robust design against manufacturing process variations. The proposed method is employed to seek compressor blade designs which ahve less sensitive aerodynamic performance in presence of manufacturing uncertainties. A novel geometry modeling technique is presented to model the manufacturing uncertainty in compressor blades. A Gaussian Stochastic Process Model is employed as a surrogate to the expensive CFD simulations. The probabilistic performance of each design is evaluated using Bayesian Monte Carlo Simulation. This is combined with a Multiobjective Optimization process to allow explicit trade-off between the mean and standard deviation of the performance. The aim is to provide the designer with a Pareto-Optimal robust design set to choose the design which meets the performance specifications in presence of manufacturing uncertainty.
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