Dual-response optimization using a patient rule induction method. Issue Volume 30:Issues 4(2018) (2nd October 2018)

• Record Type: Journal Article
• Authors: Lee, Dong-Hee; Yang, Jin-Kyung; Kim, Kwang-Jae
• Is Part Of: Quality engineering. Volume 30:Issues 4(2018)
• Page Start: 610
• Page End: 620
• Publication Date: 2018-10-02
• Subjects: data mining -- dual-response surface optimization -- patient rule induction method -- process optimization -- response surface methodology; Quality control -- Periodicals; Production management -- Quality control -- Periodicals; 658.5
• DOI: 10.1080/08982112.2017.1417599
• Languages: English
• ISSNs: 0898-2112

Abstract

ABSTRACT: A dual-response surface optimization approach assumes that response surface models of the mean and standard deviation of a response are fitted well to experimental data. However, it is often difficult to satisfy this assumption when dealing with a large volume of operational data from a manufacturing line. The proposed method attempts to optimize the mean and standard deviation of the response without building response surface models. Instead, it searches for an optimal setting of input variables directly from operational data by using a patient rule induction method. The proposed approach is illustrated with a step-by-step procedure for an example case.