# Optimization of PFMEA Team Composition in the Automotive Industry Using the IPF-RADAR Approach
## 1 Introduction
Although additional relevant criteria, such as interest in participating in the PFMEA team and workload in the primary job position, should be taken into account when selecting PFMEA team members, in this case, all candidates were first interviewed and asked whether they were willing and able to participate in the PFMEA team activities. Besides the additional responsibility, it is common practice in the company that this assignment brings benefits such as a monetary bonus on the monthly salary, opportunities for faster promotion, access to additional training, the possibility to collaborate with colleagues from other departments, increased recognition within the company, and more. To address the problem under consideration, a Multi-Attribute Decision-Making (MADM) approach was employed. MADM, broadly speaking, falls under the group of Multi-Criteria Decision-Making (MCDM) methods and is used for solving optimization problems in various engineering domains, such as advanced manufacturing [3; 4], logistics [5; 6], material selection [7; 8], failure analysis [9; 10], energy sector [11; 12], supplier selection [13; 14], selection of electric vehicles [15; 16], etc. In this case, the MADM approach was extended by the application of Interval-Valued Pythagorean Fuzzy Numbers (IVPFNs). The MADM method used for ranking potential candidates in this study was the Ranking based on the Distances And Range (RADAR) method [17; 18]. In the literature, there are two variations of the RADAR method, namely RADAR and RADAR II, which differ in the way values are normalized. The RADAR method favours the stability of an alternative by mitigating the influence of extremely high values across a small number of criteria, whereas the RADAR II method evaluates alternatives more objectively. However, in this study, due to the limitations of fuzzy algebra for IVPFNs, which does not recognize classical mathematical operations, such as subtraction and division, distances between two IVPFNs were used instead of these operations. Therefore, two variants of the RADAR method extended by the application of IVPFNs were used in this study, referred to as the IPF-RADAR approach. For the purposes of the case study, a shift manager, HR specialist, and production supervisor were engaged as independent experts in the decision-making process. All other individuals who were potential candidates for PFMEA team membership, or who were already part of the existing PFMEA team within the company, were considered as candidates. The case study was conducted in a Tier-1 company in the automotive supply chain, primarily producing rubber components, along with certain plastic parts for automobiles. This paper is organized as follows: The introductory chapter provides fundamental considerations regarding the research problem, presents the objective of the study, and outlines the applied methodology. The second chapter offers a literature review on the application of MADM methods for solving personnel/candidate selection problems. The third chapter explains the employed methodology, starting with the fundamentals of IVPFNs and continuing to the applied IPF-RADAR approach. The fourth chapter presents the practical implementation of the proposed model, while the final chapter highlights the key conclusions of the research.