Designing a Statistical Process Control Model Through a Fuzzy Inference System to Control Descriptive Characteristic in the Food Industry

Subject Areas :

Bahavar Azarmizad ¹ , Kamaleddin Rahmani Yoshanlui ² , Alireza Bafandeh Zendeh ³ , سیروس فخیمی آذر ⁴

1 - Ph.D Student, Department of Management, Faculty of Management, Economic and Accounting, Tabriz Branch, Islamic Azad University, Tabriz, Iran.
2 - Assistant professor, Department of Management, Faculty of Management, Economic and Accounting, Tabriz Branch, Islamic Azad University, Tabriz, Iran.
3 - Associate professor, Department of Management, Faculty of Management, Economic and Accounting, Tabriz Branch, Islamic Azad University, Tabriz, Iran.
4 - استادیار، گروه مدیریت، دانشکده مدیریت، اقتصاد و حسابداری، واحد تبریز، دانشگاه آزاد اسلامی، تبریز، ایران.

Received: 2023-01-05 Accepted : 2023-02-25 Published : 2025-03-09

Keywords: Fuzzy SPC, Fuzzy Mode, Middle Fuzzy, Fuzzy Inference System.,

Abstract :

The importance of quality in the industry to obtain and produce high quality products has been known for a long time. Quality in the production environment improves reliability, increase production and attracts customer satisfaction. Classical control diagrams, using precise and definite data, place production processes in two groups, «rejection» or «acceptance». Descriptive characteristics are in fuzzy conditions due to ambiguity in the number of defects in the product and decision making by the inspector, and fuzzy sets by defining continuous membership functions and using ambiguous and indefinite data by using triangular and trapezoidal fuzzy numbers in the form of control categories are classified and express the quality level of the product more realistically. This research is an applied and descriptive research, which was carried out with the aim of designing model of Statistical Process Control through a fuzzy inference system to control descriptive characteristics in the food industry. Sampling system has been used in the inspection station to collect information and according to sensory and physical characteristics, the quality level of the produced chocolates was determined. In the Classical Method, 28 cases were identified «under control» and only 2 cases were «out of control». But in the investigation with the fuzzy designed model, 28 samples were «under control», 1 sample was «relatively under control» and 1 sample was «out of control»; Based on the research result, practical suggestions were recommended to the relevant industry.

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