Reliability Estimation of a Milk Manufacturing Unit using Weakest t-norm based Arithmetic Operations on Intuitionistic Fuzzy Sets

Abstract

The dairy industry relies heavily on efficient milk manufacturing units to produce high-quality dairy products. Any disruption in the milk manufacturing process can have significant repercussions, including product contamination, financial losses, and potential danger to consumers. Therefore, ensuring the safety and reliability of the milk manufacturing system is paramount. In addition, failure probability analysis of components is essential for determining the most important preventive and corrective actions and identifying potential hazards. Many studies have implemented various techniques in traditional and fuzzy fault trees to perform detailed system reliability analyses. This study introduces a novel reliability analysis approach by incorporating the concept of a fault tree within an intuitionistic fuzzy framework. In this approach, triangular intuitionistic fuzzy numbers are utilized to accurately assess the failure potential of fundamental events in a milk processing unit. The study further applies approximate intuitionistic fuzzy arithmetic operations based on the weakest t-norm to improve the reliability of milk manufacturing systems. By incorporating the proposed approach, the failure probability of the milk manufacturing unit is obtained as (0.01132, 0.01142, 0.01227, 0.01537, 0.01547), with corresponding reliability values of (0.98677, 0.98688, 0.98773, 0.99083, 0.99093). This approach not only provides these estimates but also quantitatively evaluates the extent to which each basic failure event contributes to the overall system failure. The effectiveness of the aforesaid approach is further demonstrated through a systematic comparison of the obtained results with those from existing reliability assessment approaches.

Keywords

Intuitionistic fuzzy sets / fault tree analysis / reliability / milk manufacturing unit / ranking

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