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This paper presents a methodology for the design of products/processes that makes use of the concepts of robust design and the techniques of multiple criteria optimization for simultaneously optimizing many quality characteristics. First, a systematic approach to the selection of an efficient matrix experiment for a design problem is presented. Appropriate performance measures are obtained so that their joint optimization results in the minimum variation of product characteristics. The use of transformations is highlighted as a useful technique to statistically validate the design process. A discrete multiple criteria optimization algorithm that incorporates the methods of dominated approximations and reference points is developed to obtain nondominated solutions for the design problem. The methodology is illustrated using a case study gleaned from the literature.>
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Stored only when both papers are in the corpus — 37 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
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