Product Family Configuration Design Evaluation
نویسندگان
چکیده
Product family configuration design has been recognized as a promising dimension for implementing the assembly-to-order production strategy under mass customization environments. With a family of configuration design alternatives derived from a configuration space, product family configuration design evaluation is usually performed to select the “best” configuration design that meets customer value and expectations to the largest extent and deserves further development. To fulfill the task, a capable algorithm is highly desirable to automatically generate a family of feasible configuration designs based on a set of predefined modules and constraints and subsequently select the optimal one. Towards this end, a genetic algorithm is proposed, and meanwhile three major issues are addressed when formulating the optimization methodology. (1). Utility of quality and customization cost are devised as multiple design objectives to fully embody customer value. (2). A hybrid constraint-handling strategy is developed to deal with the feasibility of configuration design alternatives effectively. (3). A generic encoding scheme is conceived to represent configuration design solutions and achieve reusability of the genetic algorithm along with the variations of configuration spaces in various customization cases.
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