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In the engineering design domain, product design process is a major focus. In this process, product designs are conceived through several consecutive stages, where several decision making tools are deployed. Decision making in such settings involves a variety of complexities such as uncertainty, or ambiguity of available data, or missing information. Despite these complexities, however, designers and manufacturers need to make appropriate decisions to prevent from design failures, and achieve success in the marketplace. Accordingly, decision makers require an effective tool to assist them in making appropriate decisions. In this work, we introduce data envelopment analysis (DEA) to the product design domain for solving problems in two important focus areas: conceptual design problems and product family design problems. DEA has been widely applied in various fields and has been proved to be effective. In the book, we provide DEA implementations on three case studies to demonstrate its applicability in the product design domain. The results of the case studies reveal that DEA is effective in generating appropriate product design strategies.

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Chun-yu Lin is pursuing a Ph.D. degree in Industrial Engineering at Penn State. His research interests focus on developing methods to solve product design and development problems. Gül Okudan Kremer is an Associate Professor of Engineering Design and Industrial Engineering at Penn State. She has been an AFRL Faculty Fellow and a Fulbright Scholar.

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