Developing one-sided specification six-sigma fuzzy quality index and testing model to measure the process performance of fuzzy information

Kuen-Suan Chen, Ching-Hsin Wang, Kim Hua Tan and Shun-Fung Chiu

International Journal of Production Economics, 2019, vol. 208, issue C, 560-565

Abstract: Depending on the quality characteristic, a process capability index (PCI) can be used for one-sided specifications or for bilateral specifications. A number of researchers have investigated the statistical properties of one-sided specification indices and proposed methods for applications. The later introduction of the Six Sigma approach also assisted many firms in effectively enhancing their production capacities, reducing waste, and increasing effectiveness. Chen et al. (2017a) modified the PCI for one-sided specifications and proposed the Six Sigma Quality Index (SSQI), which coincidently equals the quality level and has a one-to-one relationship with yield. However, uncertainty in quality characteristic measurements is common in practice, which can lead to judgment errors in conventional process capability assessment methods. This study therefore developed an SSQI for one-sided specifications based on the fuzzy testing method created by Buckley (2005) and developed a Six Sigma fuzzy evaluation index and testing model. In addition to having a simpler calculation procedure, the model takes the process capability and Six Sigma quality level into consideration and can process the uncertainties in the data to make it more convenient for the industry to solve engineering issues. Finally, we presented a practical example to demonstrate the applications. The model proposed in this study can provide the industry with a practical approach to assess process quality in a fuzzy environment.

Keywords: Six sigma quality index; Uncertain data; One-sided specification; Fuzzy test (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (11)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:proeco:v:208:y:2019:i:c:p:560-565

DOI: 10.1016/j.ijpe.2018.12.025

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