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Journal of Intelligent Manufacturing

, Volume 20, Issue 2, pp 139–149 | Cite as

Construction of quality control charts by using probability and fuzzy approaches and an application in a textile company

  • İrfan Ertuğrul
  • Esra Aytaç
Article

Abstract

A method that uses statistical techniques to monitor and control product quality is called statistical process control (SPC), where control charts are test tools frequently used for monitoring the manufacturing process. In this study, statistical quality control and the fuzzy set theory are aimed to combine. As known, fuzzy sets and fuzzy logic are powerful mathematical tools for modeling uncertain systems in industry, nature and humanity; and facilitators for common-sense reasoning in decision making in the absence of complete and precise information. In this basis for a textile firm for monitoring the yarn quality, control charts proposed by Wang and Raz are constructed according to fuzzy theory by considering the quality in terms of grades of conformance as opposed to absolute conformance and nonconformance. And then with the same data for textile company, the control chart based on probability theory is constructed. The results of control charts based on two different approaches are compared. It’s seen that fuzzy theory performs better than probability theory in monitoring the product quality.

Keywords

Statistical quality control Fuzzy logic Quality control charts Fuzzy quality control charts 

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Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  1. 1.The Faculty of Economic and Administrative Sciences, Department of Bussiness AdministrationUniversity of PamukkaleDenizliTurkey

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