Risk management based on fuzzy BWM and fuzzy MOORA: Case study-Food industry

Risk management in the food industry reduces costs through better management of quality affairs and reduced returns and waste, and moves towards perfect production using the principles of good production conditions. It creates confidence in customers and the positive opinion of legal regulators and provides proper management of factors affecting the health, safety, and environment of food. In this regard, it is essential to have a tool that assesses the level of food risk and, consequently, estimates the actual deviation. Therefore, the need to recognize and managing risk in food is inevitable. One of the problems of food industry managers is identifying and dealing with risks in this area. Identifying and prioritizing risk due to limitations is an important issue in risk management that needs to be done for successful risk management. The purpose of this study is to present a model based on multi-criteria decision-making method and analysis of the effects of risk situations which is considered as one of the new multi-criteria decision-making techniques, to prioritize the risks of the food industry as well as the risk failure structure approach that structures the risk identification process and identifies the identification phase from the perspective of feature coverage. For this purpose, first, using the risk failure structure approach and using well-known models in this field, risk assessment indicators related to the food industry were extracted in the form of a case study in the food industry of West Azerbaijan province, then using the best - worst combination and Moora method were evaluated and prioritized by considering the opinions of experts, and finally, the risks related to each of the priority indicators were extracted and solutions were presented to manage them