Abstract

Product families are frequently used to provide consumers with a variety of appealing products and to help maintain reasonably low production costs for manufacturers. Three common objectives in the design of product families are used to balance the interests of both consumers and manufacturers. These objectives are to maximize (i) product performance, (ii) product distinctiveness as perceived by the consumer, and (iii) product commonality as seen by the manufacturer. In this thesis, three methods are introduced that use multiobjective optimization and Smart Pareto filtering to satisfy the three objectives of product family design. The methods are progressive in nature and begin with the selection of product family members using Smart filtering and develop through the establishment of scale- based product platforms to the design of combined scale- based and module-based product platforms. Each of the methods is demonstrated using a well-know universal electric motor example problem. The results of each method are then compared to a benchmark electric motor product family that was previously defined in the literature. Additionally, a pressure vessel example problem is used to further demonstrate the first of the three methods.

Degree

College and Department

Ira A. Fulton College of Engineering and Technology; Mechanical Engineering

Rights

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