Investigation of order delays in a built-in factory via type-2 fuzzy rule based failure mode and effects analysis

In today's competitive conditions, companies are consistently striving to enhance the quality of their products and services. Every demand that is not met on time can cause customer dissatisfaction, and if the problem is not resolved and repeated, it can cause customer losses. Failure Mode and Effects Analysis (FMEA) is a technique that identifies the risks of potential or known failures and prioritizes failure modes according to these risks. Since this technique is based on the principle of preventing errors before occurring or reaching the customer, it is widely used as a preventive technique. In FMEA, failures are prioritized based on their probability of occurrence, the severity of their impact on the customer when they occur, and their detectability. It is aimed to reduce the internal and external failure costs caused by poor quality by taking improvement action according to this order. In this study, the problem of tardy delivery of orders to customers in an built-in company was analyzed based on the Process FMEA (P-FMEA) form, which ranks failure types by determining action priority according to the guide published by AIAG (Automotive Industry Action Group) & VDA (Verband Der Automobilindustrie) in 2019. Because of the fact that the probability, severity, and detectability levels in FMEA are based on linguistic expressions, the fuzzy logic method was used. Type-1, Type-2, and Interval Type-2 fuzzy sets were calculated using MATLAB Fuzzy Logic Designer, and the results were compared. As a result of the analyses, different prioritizations were obtained, and the used to grey relational analysis approach, which identifies important factors by examining. The ranking obtained indicated that raw material and semi-finished product stock deviations were primarily responsible for order delays.