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Manufacturers seek to improve the quality of their products while reducing costs and decreasing production time. Toward this end, designers are now beginning to consider downstream issues, such as manufacturability and ease of assembly, early in the preliminary design phase. Despite progress made by these 'design for X' approaches, engineering designs are ultimately evaluated with respect to many criteria. The design process, therefore, should be driven by simultaneous consideration of these multiple criteria, rather than evaluation of a single criterion at each stage of the design process. Further, the ultimate evaluator of a product is the customer. We therefore need a way to integrate customer satisfaction in the concurrent design process. The "House of Quality" offers a way to organize and communicate market information to engineering. This construct uses a symbolic representation to model the interrelated functions within an organization which contribute to product design, development, and manufacture. This representation makes clear the connections between engineering design decisions and their impact on the customer. The methodology presented in this thesis builds on this quality-based construct by using customer preferences and a transformation of the symbolic customer-engineering relationship matrix to form constraints on the feasible design space. Multiattribute Utility Theory, a decision analysis tool, provides the mathematical basis to model competing design goals simultaneously and to make rational decisions to affect overall design improvement. The utility function serves as an objective function toward maximization of total quality. When coupled with the constraints, this construct completes a mathematical programming model of the concurrent design problem. With two examples, we demonstrate how to determine the optimal design, defined as the optimum combination of multiple quality attributes. This new methodology for optimal concurrent design has several noteworthy advantages. First, the utility function lends mathematical rigor and a theoretical motivation for normative design decision making. Secondly, this model permits designers to evaluate the worth of a design as a function of several attributes and, by determining the functional relationships between each of these attributes and the variables controlled by the designer, provides a mechanism to guide the design process. Thirdly, since the model is a mathematical program, it may be solved using established optimization methods to yield the best design as perceived by the customer. Lastly the advances proposed for the House of Quality make this tool much more valuable to industry. This methodology provides a formal framework for decision making in design, allowing manufacturers to Design for Quality.