IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v7y2019i10p874-d269144.html
   My bibliography  Save this article

A Novel FMEA Model Based on Rough BWM and Rough TOPSIS-AL for Risk Assessment

Author

Listed:
  • Tai-Wu Chang

    (Department of Industrial Engineering and Management, National Taipei University of Technology, 1, Sec. 3, Zhongxiao E. Rd., Taipei 10608, Taiwan)

  • Huai-Wei Lo

    (Department of Industrial Engineering and Management, National Taipei University of Technology, 1, Sec. 3, Zhongxiao E. Rd., Taipei 10608, Taiwan)

  • Kai-Ying Chen

    (Department of Industrial Engineering and Management, National Taipei University of Technology, 1, Sec. 3, Zhongxiao E. Rd., Taipei 10608, Taiwan)

  • James J. H. Liou

    (Department of Industrial Engineering and Management, National Taipei University of Technology, 1, Sec. 3, Zhongxiao E. Rd., Taipei 10608, Taiwan)

Abstract

Failure mode and effects analysis (FMEA) is a risk assessment method that effectively diagnoses a product’s potential failure modes. It is based on expert experience and investigation to determine the potential failure modes of the system or product to develop improvement strategies to reduce the risk of failures. However, the traditional FMEA has many shortcomings that were proposed by many studies. This study proposes a hybrid FMEA and multi-attribute decision-making (MADM) model to establish an evaluation framework, combining the rough best worst method (R-BWM) and rough technique for order preference by similarity to an ideal solution technique (R-TOPSIS) to determine the improvement order of failure modes. In addition, this study adds the concept of aspiration level to R-TOPSIS technology (called R-TOPSIS-AL), which not only optimizes the reliability of the TOPSIS calculation program, but also obtains more potential information. This study then demonstrates the effectiveness and robustness of the proposed model through a multinational audio equipment manufacturing company. The results show that the proposed model can overcome many shortcomings of traditional FMEA, and effectively assist decision-makers and research and development (R&D) departments in improving the reliability of products.

Suggested Citation

  • Tai-Wu Chang & Huai-Wei Lo & Kai-Ying Chen & James J. H. Liou, 2019. "A Novel FMEA Model Based on Rough BWM and Rough TOPSIS-AL for Risk Assessment," Mathematics, MDPI, vol. 7(10), pages 1-20, September.
    • Handle: RePEc:gam:jmathe:v:7:y:2019:i:10:p:874-:d:269144
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/7/10/874/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/7/10/874/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Lo, Huai-Wei & Liou, James J.H. & Huang, Chun-Nen & Chuang, Yen-Ching, 2019. "A novel failure mode and effect analysis model for machine tool risk analysis," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 173-183.
    2. Kuo, Ting, 2017. "A modified TOPSIS with a different ranking index," European Journal of Operational Research, Elsevier, vol. 260(1), pages 152-160.
    3. Chemweno, Peter & Pintelon, Liliane & Van Horenbeek, Adriaan & Muchiri, Peter, 2015. "Development of a risk assessment selection methodology for asset maintenance decision making: An analytic network process (ANP) approach," International Journal of Production Economics, Elsevier, vol. 170(PB), pages 663-676.
    4. Željko Stević & Dragan Pamučar & Marko Subotić & Jurgita Antuchevičiene & Edmundas Kazimieras Zavadskas, 2018. "The Location Selection for Roundabout Construction Using Rough BWM-Rough WASPAS Approach Based on a New Rough Hamy Aggregator," Sustainability, MDPI, vol. 10(8), pages 1-27, August.
    5. Hossein Safari & Zahra Faraji & Setareh Majidian, 2016. "Identifying and evaluating enterprise architecture risks using FMEA and fuzzy VIKOR," Journal of Intelligent Manufacturing, Springer, vol. 27(2), pages 475-486, April.
    6. Rezaei, Jafar, 2015. "Best-worst multi-criteria decision-making method," Omega, Elsevier, vol. 53(C), pages 49-57.
    7. Dragan Pamučar & Ljubomir Gigović & Zoran Bajić & Miljojko Janošević, 2017. "Location Selection for Wind Farms Using GIS Multi-Criteria Hybrid Model: An Approach Based on Fuzzy and Rough Numbers," Sustainability, MDPI, vol. 9(8), pages 1-23, July.
    8. Željko Stević & Irena Đalić & Dragan Pamučar & Zdravko Nunić & Slavko Vesković & Marko Vasiljević & Ilija Tanackov, 2019. "A new hybrid model for quality assessment of scientific conferences based on Rough BWM and SERVQUAL," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(1), pages 1-30, April.
    9. Seyed-Hosseini, S.M. & Safaei, N. & Asgharpour, M.J., 2006. "Reprioritization of failures in a system failure mode and effects analysis by decision making trial and evaluation laboratory technique," Reliability Engineering and System Safety, Elsevier, vol. 91(8), pages 872-881.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Farzad Sharifi & Mohammad Ali Vahdatzad & Behrad Barghi & Nasibeh Azadeh-Fard, 2022. "Identifying and ranking risks using combined FMEA-TOPSIS method for new product development in the dairy industry and offering mitigation strategies: case study of Ramak Company," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(5), pages 2790-2807, October.
    2. Jen-Jen Yang & Yen-Ching Chuang & Huai-Wei Lo & Ting-I Lee, 2020. "A Two-Stage MCDM Model for Exploring the Influential Relationships of Sustainable Sports Tourism Criteria in Taichung City," IJERPH, MDPI, vol. 17(7), pages 1-16, March.
    3. Shih-Ping Shen & Jung-Fa Tsai, 2022. "Evaluating the Sustainable Development of the Semiconductor Industry Using BWM and Fuzzy TOPSIS," Sustainability, MDPI, vol. 14(17), pages 1-17, August.
    4. Peace Y. L. Liu & James J. H. Liou & Sun-Weng Huang, 2023. "Exploring the Barriers to the Advancement of 3D Printing Technology," Mathematics, MDPI, vol. 11(14), pages 1-20, July.
    5. Ferenc Bognár & Csaba Hegedűs, 2022. "Analysis and Consequences on Some Aggregation Functions of PRISM (Partial Risk Map) Risk Assessment Method," Mathematics, MDPI, vol. 10(5), pages 1-19, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mu-Hsin Chang & James J. H. Liou & Huai-Wei Lo, 2019. "A Hybrid MCDM Model for Evaluating Strategic Alliance Partners in the Green Biopharmaceutical Industry," Sustainability, MDPI, vol. 11(15), pages 1-20, July.
    2. Dhalmahapatra, Krantiraditya & Garg, Ashish & Singh, Kritika & Xavier, Nirmal Francis & Maiti, J., 2022. "An integrated RFUCOM – RTOPSIS approach for failure modes and effects analysis: A case of manufacturing industry," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    3. Mi, Xiaomei & Tang, Ming & Liao, Huchang & Shen, Wenjing & Lev, Benjamin, 2019. "The state-of-the-art survey on integrations and applications of the best worst method in decision making: Why, what, what for and what's next?," Omega, Elsevier, vol. 87(C), pages 205-225.
    4. Shih-Ping Shen & Jung-Fa Tsai, 2022. "Evaluating the Sustainable Development of the Semiconductor Industry Using BWM and Fuzzy TOPSIS," Sustainability, MDPI, vol. 14(17), pages 1-17, August.
    5. James J. H. Liou & Perry C. Y. Liu & Huai-Wei Lo, 2020. "A Failure Mode Assessment Model Based on Neutrosophic Logic for Switched-Mode Power Supply Risk Analysis," Mathematics, MDPI, vol. 8(12), pages 1-19, December.
    6. Željko Stević & Irena Đalić & Dragan Pamučar & Zdravko Nunić & Slavko Vesković & Marko Vasiljević & Ilija Tanackov, 2019. "A new hybrid model for quality assessment of scientific conferences based on Rough BWM and SERVQUAL," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(1), pages 1-30, April.
    7. Besharati Fard, Moein & Moradian, Parisa & Emarati, Mohammadreza & Ebadi, Mehdi & Gholamzadeh Chofreh, Abdoulmohammad & Klemeŝ, Jiří Jaromír, 2022. "Ground-mounted photovoltaic power station site selection and economic analysis based on a hybrid fuzzy best-worst method and geographic information system: A case study Guilan province," Renewable and Sustainable Energy Reviews, Elsevier, vol. 169(C).
    8. Milad Kolagar & Seyed Mohammad Hassan Hosseini & Ramin Felegari & Parviz Fattahi, 2020. "Policy-making for renewable energy sources in search of sustainable development: a hybrid DEA-FBWM approach," Environment Systems and Decisions, Springer, vol. 40(4), pages 485-509, December.
    9. Sarbast Moslem & Muhammet Gul & Danish Farooq & Erkan Celik & Omid Ghorbanzadeh & Thomas Blaschke, 2020. "An Integrated Approach of Best-Worst Method (BWM) and Triangular Fuzzy Sets for Evaluating Driver Behavior Factors Related to Road Safety," Mathematics, MDPI, vol. 8(3), pages 1-20, March.
    10. Željko Stević & Dragan Pamučar & Marko Subotić & Jurgita Antuchevičiene & Edmundas Kazimieras Zavadskas, 2018. "The Location Selection for Roundabout Construction Using Rough BWM-Rough WASPAS Approach Based on a New Rough Hamy Aggregator," Sustainability, MDPI, vol. 10(8), pages 1-27, August.
    11. Huang, Jia & You, Jian-Xin & Liu, Hu-Chen & Song, Ming-Shun, 2020. "Failure mode and effect analysis improvement: A systematic literature review and future research agenda," Reliability Engineering and System Safety, Elsevier, vol. 199(C).
    12. Lo, Huai-Wei & Liou, James J.H. & Huang, Chun-Nen & Chuang, Yen-Ching, 2019. "A novel failure mode and effect analysis model for machine tool risk analysis," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 173-183.
    13. Balali, Amirhossein & Yunusa-Kaltungo, Akilu & Edwards, Rodger, 2023. "A systematic review of passive energy consumption optimisation strategy selection for buildings through multiple criteria decision-making techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 171(C).
    14. Jianghong Zhu & Bin Shuai & Rui Wang & Kwai-Sang Chin, 2019. "Risk Assessment for Failure Mode and Effects Analysis Using the Bonferroni Mean and TODIM Method," Mathematics, MDPI, vol. 7(6), pages 1-17, June.
    15. Huai-Wei Lo & Chao-Che Hsu & Chun-Nen Huang & James J. H. Liou, 2021. "An ITARA-TOPSIS Based Integrated Assessment Model to Identify Potential Product and System Risks," Mathematics, MDPI, vol. 9(3), pages 1-17, January.
    16. Morteza Yazdani & Prasenjit Chatterjee & Maria Jose Montero-Simo & Rafael A. Araque-Padilla, 2019. "An Integrated Multi-Attribute Model for Evaluation of Sustainable Mobile Phone," Sustainability, MDPI, vol. 11(13), pages 1-18, July.
    17. Amin Vafadarnikjoo & Madjid Tavana & Tiago Botelho & Konstantinos Chalvatzis, 2020. "A neutrosophic enhanced best–worst method for considering decision-makers’ confidence in the best and worst criteria," Annals of Operations Research, Springer, vol. 289(2), pages 391-418, June.
    18. Penjani Hopkins Nyimbili & Turan Erden, 2021. "Comparative evaluation of GIS-based best–worst method (BWM) for emergency facility planning: perspectives from two decision-maker groups," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 105(1), pages 1031-1067, January.
    19. Perry C. Y. Liu & Huai-Wei Lo & James J. H. Liou, 2020. "A Combination of DEMATEL and BWM-Based ANP Methods for Exploring the Green Building Rating System in Taiwan," Sustainability, MDPI, vol. 12(8), pages 1-19, April.
    20. Abbas Bonyani & Moslem Alimohammadlou, 2021. "A novel approach to solve the problems with network structure," Operational Research, Springer, vol. 21(2), pages 1279-1297, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:7:y:2019:i:10:p:874-:d:269144. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.