Unapređenje procesa proizvodnje primenom modifikovane PFMEA analize i metoda optimizacije

Abstract

Organization and management of the production process in automotive industry companies are very important and complex tasks that require the application of different methods and techniques. The reliability of this business process can be affected by numerous factors, such as unfavorable and unsafe working conditions, malfunctioning of production and control equipment, inadequate materials, etc. The process of identifying and analyzing potential failure modes that may occur in the automotive industry production process is based on the application of the Process Failure Mode and Effect Analysis (PFMEA) method. In this doctoral dissertation, a total of five models have been developed. The first two models are based on the modification and improvement of the PFMEA analysis, using Interval type-2 fuzzy Multi-Attribute Decision Making (IT2FMADM) methods. In the first model, a modification of the traditional PFMEA analysis was carried out through the application of the Interval type-2 fuzzy Best-Worst Method (IT2FBWM) with interval type-2 fuzzy numbers. In addition, the ranking of failure modes was performed according to the instructions from the latest PFMEA handbook. In the second model, a methodology for ranking failure modes was developed based on the combination of the IT2FBWM method and the Multi-Criteria Optimization and Compromise Solution method extended with interval type-2 fuzzy numbers (IT2FVIKOR). The third developed model is a model for the analysis and selection of suppliers, based on the application of the Interval type-2 fuzzy Analytic Hierarchy Process (IT2FAHP) method and the Interval type-2 fuzzy Multi-Attributive Border Approximation area Comparison (IT2FMABAC) method. The fourth model was developed for the analysis of factors affecting the safety and health of employees in the workplace. The model integrates the application of the Delphi method and two methods for ranking failure modes extended with interval type-2 fuzzy numbers, which are the Interval type-2 fuzzy Technique for Order Preference by Similarity to Ideal Solution (IT2FTOPSIS) method and the Interval type-2 fuzzy Simple Additive Weighting (IT2FSAW) method. The fifth model refers to the application of two heuristics, the Genetic Algorithm (GA) and the Variable Neighborhood Search (VNS), to determine the priorities of failure modes. The proposed models were tested on data originating from companies in the automotive industry. The considered companies are located at different levels in the automotive supply chain and produce different types of products.