Optimising Risk Management in Wood-based Manufacturing: A Fuzzy AHP-FMEA Framework Approach
This study integrates the Fuzzy Analytic Hierarchy Process (AHP) with the Failure Mode and Effects Analysis (FMEA) to enhance risk prioritisation in wood-based manufacturing. Traditional FMEA methods face challenges in handling subjective evaluations and complex environments. By incorporating fuzzy...
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| Format: | Article |
| Language: | English |
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North Carolina State University
2025-03-01
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| Series: | BioResources |
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| Online Access: | https://ojs.bioresources.com/index.php/BRJ/article/view/24289 |
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| author | Ivana Perić Kristina Klarić Andreja Pirc Barčić Karla Vukman Tomislav Sedlar Petra Grošelj |
| author_facet | Ivana Perić Kristina Klarić Andreja Pirc Barčić Karla Vukman Tomislav Sedlar Petra Grošelj |
| author_sort | Ivana Perić |
| collection | DOAJ |
| description | This study integrates the Fuzzy Analytic Hierarchy Process (AHP) with the Failure Mode and Effects Analysis (FMEA) to enhance risk prioritisation in wood-based manufacturing. Traditional FMEA methods face challenges in handling subjective evaluations and complex environments. By incorporating fuzzy logic, this study refines the Risk Priority Number (RPN) calculation, enabling a more nuanced assessment of failure modes. Critical failure points, such as delays in order processing, production, and delivery, were identified, highlighting their impact on operational efficiency, customer satisfaction, and financial outcomes. Using the Pareto principle, it was revealed that addressing the top 20% of the identified risks could mitigate approximately 80% of the overall risk exposure. Proposed corrective measures, including enhanced employee training, streamlined workflows, and improved communication protocols, provide actionable strategies to optimise processes and ensure sustainability. Conducted within a Croatian wood-manufacturing company, this framework demonstrated its efficacy in refining risk assessments and supporting continuous improvement. The findings advance risk management methodologies and showcase the potential for broader applications in dynamic and complex industrial environments. |
| format | Article |
| id | doaj-art-d07fc5332ef34429b8ada85ae576becd |
| institution | DOAJ |
| issn | 1930-2126 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | North Carolina State University |
| record_format | Article |
| series | BioResources |
| spelling | doaj-art-d07fc5332ef34429b8ada85ae576becd2025-08-20T03:07:16ZengNorth Carolina State UniversityBioResources1930-21262025-03-01202297930012560Optimising Risk Management in Wood-based Manufacturing: A Fuzzy AHP-FMEA Framework ApproachIvana Perić0https://orcid.org/0000-0002-2253-9352Kristina Klarić1https://orcid.org/0000-0002-0212-2197Andreja Pirc Barčić2https://orcid.org/0000-0003-0127-3740Karla Vukman3https://orcid.org/0009-0000-5165-8679Tomislav Sedlar4https://orcid.org/0000-0002-7124-4470Petra Grošelj5https://orcid.org/0000-0001-9363-9783University of Zagreb Faculty of Forestry and Wood Technology, 10000 Zagreb, CroatiaUniversity of Zagreb Faculty of Forestry and Wood Technology, 10000 Zagreb, CroatiaUniversity of Zagreb Faculty of Forestry and Wood Technology, 10000 Zagreb, CroatiaUniversity of Zagreb Faculty of Forestry and Wood Technology, 10000 Zagreb, CroatiaUniversity of Zagreb Faculty of Forestry and Wood Technology, 10000 Zagreb, CroatiaDepartment of Forestry and Renewable Forest Resources, Biotechnical Faculty, University of Ljubljana, 1000 Ljubljana, SloveniaThis study integrates the Fuzzy Analytic Hierarchy Process (AHP) with the Failure Mode and Effects Analysis (FMEA) to enhance risk prioritisation in wood-based manufacturing. Traditional FMEA methods face challenges in handling subjective evaluations and complex environments. By incorporating fuzzy logic, this study refines the Risk Priority Number (RPN) calculation, enabling a more nuanced assessment of failure modes. Critical failure points, such as delays in order processing, production, and delivery, were identified, highlighting their impact on operational efficiency, customer satisfaction, and financial outcomes. Using the Pareto principle, it was revealed that addressing the top 20% of the identified risks could mitigate approximately 80% of the overall risk exposure. Proposed corrective measures, including enhanced employee training, streamlined workflows, and improved communication protocols, provide actionable strategies to optimise processes and ensure sustainability. Conducted within a Croatian wood-manufacturing company, this framework demonstrated its efficacy in refining risk assessments and supporting continuous improvement. The findings advance risk management methodologies and showcase the potential for broader applications in dynamic and complex industrial environments.https://ojs.bioresources.com/index.php/BRJ/article/view/24289fuzzy ahpfmeapareto analysisrisk prioritisationwood manufacturingprocess optimisationsustainability |
| spellingShingle | Ivana Perić Kristina Klarić Andreja Pirc Barčić Karla Vukman Tomislav Sedlar Petra Grošelj Optimising Risk Management in Wood-based Manufacturing: A Fuzzy AHP-FMEA Framework Approach BioResources fuzzy ahp fmea pareto analysis risk prioritisation wood manufacturing process optimisation sustainability |
| title | Optimising Risk Management in Wood-based Manufacturing: A Fuzzy AHP-FMEA Framework Approach |
| title_full | Optimising Risk Management in Wood-based Manufacturing: A Fuzzy AHP-FMEA Framework Approach |
| title_fullStr | Optimising Risk Management in Wood-based Manufacturing: A Fuzzy AHP-FMEA Framework Approach |
| title_full_unstemmed | Optimising Risk Management in Wood-based Manufacturing: A Fuzzy AHP-FMEA Framework Approach |
| title_short | Optimising Risk Management in Wood-based Manufacturing: A Fuzzy AHP-FMEA Framework Approach |
| title_sort | optimising risk management in wood based manufacturing a fuzzy ahp fmea framework approach |
| topic | fuzzy ahp fmea pareto analysis risk prioritisation wood manufacturing process optimisation sustainability |
| url | https://ojs.bioresources.com/index.php/BRJ/article/view/24289 |
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