Abstract
In the initial stage of product design, it is essential to define product specifications according to various market niches. An important issue in this process is to provide designers with sufficient design knowledge to find out what customers really want. This paper proposes a data mining method to facilitate this task. The method focuses on mining association rules that reflect the mapping relationship between customer needs and product specifications. Four objectives, support, confidence, interestingness and comprehensibility, are used for evaluating the extracted rules. To solve such a multi-objective problem, a Pareto-based GA is utilized to perform the rule extraction. Through computational experiments on an electrical bicycle case, it is shown that our approach is capable of extracting useful and interesting knowledge from a design database.
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Yu, L., Wang, L. Product portfolio identification with data mining based on multi-objective GA. J Intell Manuf 21, 797–810 (2010). https://doi.org/10.1007/s10845-009-0255-0
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DOI: https://doi.org/10.1007/s10845-009-0255-0