Advancing PFMEA Decision-Making: FRADAR Based Prioritization of Failure Modes Using AP, RPN, and Multi-Attribute Assessment in the Automotive Industry

This research proposes a novel way to improve Process Failure Modes and Effects Analysis (PFMEA) by using the Fuzzy RAnking based on the Distances And Range (FRADAR) method to prioritize activities for mitigating or eliminating failure modes in the automotive industry. The suggested approach seeks t...

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Main Authors: Nikola Komatina, Dragan Marinković, Danijela Tadić, Dragan Pamučar
Format: Article
Language:English
Published: University North 2025-01-01
Series:Tehnički Glasnik
Subjects:
Online Access:https://hrcak.srce.hr/file/480462
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author Nikola Komatina
Dragan Marinković
Danijela Tadić
Dragan Pamučar
author_facet Nikola Komatina
Dragan Marinković
Danijela Tadić
Dragan Pamučar
author_sort Nikola Komatina
collection DOAJ
description This research proposes a novel way to improve Process Failure Modes and Effects Analysis (PFMEA) by using the Fuzzy RAnking based on the Distances And Range (FRADAR) method to prioritize activities for mitigating or eliminating failure modes in the automotive industry. The suggested approach seeks to improve classic PFMEA by using fuzzy sets to better assess risk-related criteria and their inherent uncertainty. The criteria used to prioritize actions for mitigating failure modes include the Action Priority (AP) and Risk Priority Number (RPN) approach, as well as the cost-effectiveness of actions, the time required to resolve issues, and their impact on production, all of which are assessed by a PFMEA team using predefined linguistic terms and suggestions. Applied to a case study of a Tier-1 automotive supplier, the FRADAR method effectively ranks failure modes, providing a structured and precise approach for action prioritization. The results highlight the model’s potential to enhance decision-making processes, offering a robust framework for implementing PFMEA recommendations in the automotive industry.
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institution Kabale University
issn 1846-6168
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language English
publishDate 2025-01-01
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series Tehnički Glasnik
spelling doaj-art-50f00820c62c41348a6f2c0c3a96d9e22025-08-20T03:45:28ZengUniversity NorthTehnički Glasnik1846-61681848-55882025-01-0119344245110.31803/tg-20250221185213Advancing PFMEA Decision-Making: FRADAR Based Prioritization of Failure Modes Using AP, RPN, and Multi-Attribute Assessment in the Automotive IndustryNikola Komatina0Dragan Marinković1Danijela Tadić2Dragan Pamučar3University of Kragujevac, Faculty of Engineering, Sestre Janjić 6, 34000 Kragujevac, Serbia(1) Faculty of Mechanical Engineering and Transport Systems, TU Berlin, Straße des 17. Juni 135, 10623 Berlin, Germany / (2) Institute of Mechanical Science, Vilnius Gediminas Technical University, LT-10105 Vilnius, LithuaniaUniversity of Kragujevac, Faculty of Engineering, Sestre Janjić 6, 34000 Kragujevac, Serbia(1) Széchenyi István University, Győr, Hungary / (2) Department of Operations Research and Statistics, Faculty of Organizational Sciences, University of Belgrade, Jove Ilića 154, 11000 Belgrade, Serbia / (3) Department of Applied Mathematical Science, College of Science and Technology, Korea University Sejong 30019, Republic of KoreaThis research proposes a novel way to improve Process Failure Modes and Effects Analysis (PFMEA) by using the Fuzzy RAnking based on the Distances And Range (FRADAR) method to prioritize activities for mitigating or eliminating failure modes in the automotive industry. The suggested approach seeks to improve classic PFMEA by using fuzzy sets to better assess risk-related criteria and their inherent uncertainty. The criteria used to prioritize actions for mitigating failure modes include the Action Priority (AP) and Risk Priority Number (RPN) approach, as well as the cost-effectiveness of actions, the time required to resolve issues, and their impact on production, all of which are assessed by a PFMEA team using predefined linguistic terms and suggestions. Applied to a case study of a Tier-1 automotive supplier, the FRADAR method effectively ranks failure modes, providing a structured and precise approach for action prioritization. The results highlight the model’s potential to enhance decision-making processes, offering a robust framework for implementing PFMEA recommendations in the automotive industry.https://hrcak.srce.hr/file/480462Action PriorityAutomotive industryFRADARPFMEARPN
spellingShingle Nikola Komatina
Dragan Marinković
Danijela Tadić
Dragan Pamučar
Advancing PFMEA Decision-Making: FRADAR Based Prioritization of Failure Modes Using AP, RPN, and Multi-Attribute Assessment in the Automotive Industry
Tehnički Glasnik
Action Priority
Automotive industry
FRADAR
PFMEA
RPN
title Advancing PFMEA Decision-Making: FRADAR Based Prioritization of Failure Modes Using AP, RPN, and Multi-Attribute Assessment in the Automotive Industry
title_full Advancing PFMEA Decision-Making: FRADAR Based Prioritization of Failure Modes Using AP, RPN, and Multi-Attribute Assessment in the Automotive Industry
title_fullStr Advancing PFMEA Decision-Making: FRADAR Based Prioritization of Failure Modes Using AP, RPN, and Multi-Attribute Assessment in the Automotive Industry
title_full_unstemmed Advancing PFMEA Decision-Making: FRADAR Based Prioritization of Failure Modes Using AP, RPN, and Multi-Attribute Assessment in the Automotive Industry
title_short Advancing PFMEA Decision-Making: FRADAR Based Prioritization of Failure Modes Using AP, RPN, and Multi-Attribute Assessment in the Automotive Industry
title_sort advancing pfmea decision making fradar based prioritization of failure modes using ap rpn and multi attribute assessment in the automotive industry
topic Action Priority
Automotive industry
FRADAR
PFMEA
RPN
url https://hrcak.srce.hr/file/480462
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AT danijelatadic advancingpfmeadecisionmakingfradarbasedprioritizationoffailuremodesusingaprpnandmultiattributeassessmentintheautomotiveindustry
AT draganpamucar advancingpfmeadecisionmakingfradarbasedprioritizationoffailuremodesusingaprpnandmultiattributeassessmentintheautomotiveindustry