Quality design method using process capability index based on Monte-Carlo method and real-coded genetic algorithm

Akimasa Otsuka and Fusaomi Nagata

International Journal of Production Economics, 2018, vol. 204, issue C, 358-364

Abstract: Variability in the performance and quality of products is an important issue in production engineering. Quality variability in mechanical production is due to irregularity of parts dimensions caused by machining errors. The dimensions of each part are usually managed by conventional tolerance at the design stage. Tight tolerance values result in reduced performance variation along with an increase in the manufacturing cost. Therefore tolerancing, which is a downstream process in mechanical design, is important in a detailed design process. Although quality is usually controlled in the manufacturing stage, not only production strategy but also management strategy will change in a positive direction and manufacturing cost is also reduced if the quality is also controlled at the design stage. This is because the design stage is an upstream process in manufacturing. This paper focuses on quality control in the design stage, and proposes a novel design method of process capability, which can statistically control parts dimensions based on product performance. The method consists of a numerical method and a real-coded genetic algorithm. A case study was analysed to evaluate the effectiveness of the proposed method. The result showed that the proposed method suitably allocates the STI for each part so that the product satisfies the required product performance.

Keywords: Statistical tolerance index; Process capability index; Monte-carlo simulation; Real-coded genetic algorithm; Product performance (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:proeco:v:204:y:2018:i:c:p:358-364

DOI: 10.1016/j.ijpe.2018.08.016

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