Journal of Industrial Engineering Research in Production Systems

Journal of Industrial Engineering Research in Production Systems

Risk Assessment in the Food Industry with the Combined Approach of FMEA and BWM in Intuitionistic Fuzzy Conditions (Case Study: Tashal Quchan Dairy Factory)

Document Type : Research Paper

Authors
Fatemeh Rahmatinezhad 1
Mohammad Zarei Mahmoudabadi 2
Hossein Sayyadi 2
1 MA in Industrial Management, Department of Industrial Management, Meybod University, Meybod, Iran
2 Associate Professor Department of Industrial Management, Meybod University, Meybod, Iran
10.22084/ier.2023.5426
Abstract
Milk and its products have a high nutritional value due to the variety and abundance of available compounds. There have always been many risks in the process of preparing and producing these valuable products. In order to produce this product in a healthy way and to prevent additional costs that may be imposed on the production complex at different stages of production, it is necessary to identify the existing risks. For this purpose, a new hybrid approach has been presented and used in a case study. In this research, in order to collect data, three methods of interview, questionnaire, documents, and library documents were used. First, risk items were identified through interviews with experts. Then, the Best-Worst Method and Analytic Hierarchy Process fuzzy questionnaires were distributed. Next, using the collected data, intuitive fuzzy weights of factors and items were calculated. Ultimately, the decision matrix was formed and the risk items were prioritized using the Simple Additive Weighting method. Items “not performing proper ventilation and vacuum”, “increasing the microbial load of milk” and “the pressure of the homogenizer not reaching 120 bar” were assigned the first to third priority. In addition, in order to control and reduce the identified risk items, corrective actions have been presented
Keywords
Risk Assessment
Failure Modes and Effects Analysis (FMEA)
Best-Worst Method (BWM)
Intuitionistic Fuzzy Approach
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Journal of Industrial Engineering Research in Production Systems
Volume 11, Issue 22
September 2023
Pages 171-185