IDEAS home Printed from https://ideas.repec.org/a/spr/joinma/v30y2019i2d10.1007_s10845-016-1269-z.html
   My bibliography  Save this article

Identification of to-be-improved components for redesign of complex products and systems based on fuzzy QFD and FMEA

Author

Listed:
  • Hongzhan Ma

    (Shanghai Jiao Tong University)

  • Xuening Chu

    (Shanghai Jiao Tong University)

  • Deyi Xue

    (University of Calgary)

  • Dongping Chen

    (Shanghai Jiao Tong University
    AVIC Commercial Aircraft Engine Co. Ltd)

Abstract

Since the activities to design complex products and systems (CoPSs) mainly focus on redesign of the existing CoPSs to satisfy customer requirements and improve product reliability, identification of the to-be-improved components plays a key role in the redesign process. In the existing methods to identify the to-be-improved components, customer requirements are primarily considered while the failure knowledge, a critical information to improve product reliability, is often ignored. The objective of this research is to identify the to-be-improved components considering both customer requirements and product reliability. The customer requirements are used in redesign through quality function deployment, while the reliability is used in redesign through failure mode and effects analysis (FMEA). Different from the traditional FMEA, the failure causality relationships between and within components are analyzed in this work to provide a means of making use of failure information more effectively for constructing a directed failure causality relationship network. In this network, the failure modes of all components are modeled as vertices, and the causality relationships between failure modes are modeled as directed edges. A new index is introduced to calculate the importance of component from the viewpoint of reliability through integrating the internal and external failure effects. Fuzzy permanent function is developed to measure the internal failure effects, while the external failure effect index is developed to measure the external failure effects. A case study for identification of the to-be-improved components for the operation device of a crawler crane is implemented to demonstrate the effectiveness of the developed approach.

Suggested Citation

  • Hongzhan Ma & Xuening Chu & Deyi Xue & Dongping Chen, 2019. "Identification of to-be-improved components for redesign of complex products and systems based on fuzzy QFD and FMEA," Journal of Intelligent Manufacturing, Springer, vol. 30(2), pages 623-639, February.
    • Handle: RePEc:spr:joinma:v:30:y:2019:i:2:d:10.1007_s10845-016-1269-z
    DOI: 10.1007/s10845-016-1269-z
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10845-016-1269-z
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10845-016-1269-z?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Yan, Hong-Bin & Ma, Tieju, 2015. "A group decision-making approach to uncertain quality function deployment based on fuzzy preference relation and fuzzy majority," European Journal of Operational Research, Elsevier, vol. 241(3), pages 815-829.
    2. Chan, Lai-Kow & Wu, Ming-Lu, 2002. "Quality function deployment: A literature review," European Journal of Operational Research, Elsevier, vol. 143(3), pages 463-497, December.
    3. 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.
    4. Weiqiang Jia & Zhenyu Liu & Zhiyun Lin & Chan Qiu & Jianrong Tan, 2016. "Quantification for the importance degree of engineering characteristics with a multi-level hierarchical structure in QFD," International Journal of Production Research, Taylor & Francis Journals, vol. 54(6), pages 1627-1649, March.
    5. Shun-Hsing Chen, 2016. "Determining the service demands of an aging population by integrating QFD and FMEA method," Quality & Quantity: International Journal of Methodology, Springer, vol. 50(1), pages 283-298, January.
    6. Hu-Chen Liu & Yi-Zeng Chen & Jian-Xin You & Hui Li, 2016. "Risk evaluation in failure mode and effects analysis using fuzzy digraph and matrix approach," Journal of Intelligent Manufacturing, Springer, vol. 27(4), pages 805-816, August.
    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. Kübra Yazıcı & Seda Hatice Gökler & Semra Boran, 2021. "An integrated SMED-fuzzy FMEA model for reducing setup time," Journal of Intelligent Manufacturing, Springer, vol. 32(6), pages 1547-1561, August.
    2. Hamid Reza Fazeli & Qingjin Peng, 2023. "Integrated approaches of BWM-QFD and FUCOM-QFD for improving weighting solution of design matrix," Journal of Intelligent Manufacturing, Springer, vol. 34(3), pages 1003-1020, March.
    3. Liting Jing & Qingqing Xu & Tao Sun & Xiang Peng & Jiquan Li & Fei Gao & Shaofei Jiang, 2020. "Conceptual Scheme Decision Model for Mechatronic Products Driven by Risk of Function Failure Propagation," Sustainability, MDPI, vol. 12(17), pages 1-28, September.

    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. María Carmen Carnero, 2020. "Waste Segregation FMEA Model Integrating Intuitionistic Fuzzy Set and the PAPRIKA Method," Mathematics, MDPI, vol. 8(8), pages 1-29, August.
    2. Hisham Alidrisi, 2021. "An Innovative Job Evaluation Approach Using the VIKOR Algorithm," JRFM, MDPI, vol. 14(6), pages 1-19, June.
    3. 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.
    4. Kübra Yazıcı & Seda Hatice Gökler & Semra Boran, 2021. "An integrated SMED-fuzzy FMEA model for reducing setup time," Journal of Intelligent Manufacturing, Springer, vol. 32(6), pages 1547-1561, August.
    5. Chen, Liang-Hsuan & Ko, Wen-Chang & Yeh, Feng-Ting, 2017. "Approach based on fuzzy goal programing and quality function deployment for new product planning," European Journal of Operational Research, Elsevier, vol. 259(2), pages 654-663.
    6. Linlin Liu & Dongming Fan & Zili Wang & Dezhen Yang & Jingjing Cui & Xinrui Ma & Yi Ren, 2019. "Enhanced GO methodology to support failure mode, effects and criticality analysis," Journal of Intelligent Manufacturing, Springer, vol. 30(3), pages 1451-1468, March.
    7. Meinel, Martin & Eismann, Tobias T. & Baccarella, Christian V. & Fixson, Sebastian K. & Voigt, Kai-Ingo, 2020. "Does applying design thinking result in better new product concepts than a traditional innovation approach? An experimental comparison study," European Management Journal, Elsevier, vol. 38(4), pages 661-671.
    8. Li, Yan-Lai & Tang, Jia-Fu & Chin, Kwai-Sang & Jiang, Yu-Shi & Han, Yi & Pu, Yun, 2011. "Estimating the final priority ratings of engineering characteristics in mature-period product improvement by MDBA and AHP," International Journal of Production Economics, Elsevier, vol. 131(2), pages 575-586, June.
    9. Han, Chang Hee & Kim, Jae Kyeong & Choi, Sang Hyun, 2004. "Prioritizing engineering characteristics in quality function deployment with incomplete information: A linear partial ordering approach," International Journal of Production Economics, Elsevier, vol. 91(3), pages 235-249, October.
    10. Pushparenu Bhattacharjee & Syed Abou Iltaf Hussain & V. Dey & U. K. Mandal, 2023. "Failure mode and effects analysis for submersible pump component using proportionate risk assessment model: a case study in the power plant of Agartala," 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. 14(5), pages 1778-1798, October.
    11. Yan, Hong-Bin & Ma, Tieju & Huynh, Van-Nam, 2017. "On qualitative multi-attribute group decision making and its consensus measure: A probability based perspective," Omega, Elsevier, vol. 70(C), pages 94-117.
    12. Iranmanesh, Hossein & Thomson, Vince, 2008. "Competitive advantage by adjusting design characteristics to satisfy cost targets," International Journal of Production Economics, Elsevier, vol. 115(1), pages 64-71, September.
    13. J-B Yang & D-L Xu & X Xie & A K Maddulapalli, 2011. "Multicriteria evidential reasoning decision modelling and analysis—prioritizing voices of customer," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(9), pages 1638-1654, September.
    14. Robert N. Boute & Maud M. Van den Broeke & Kristof A. Deneire, 2017. "Barco Implements Platform-Based Product Development in Its Healthcare Division," Decision Analysis, INFORMS, vol. 48(01), pages 35-44, February.
    15. Yakubu, Hanan & Kwong, C.K., 2021. "Forecasting the importance of product attributes using online customer reviews and Google Trends," Technological Forecasting and Social Change, Elsevier, vol. 171(C).
    16. Nasser Fegh-hi Farahmand, 2016. "Imperative Strategic Planning as Improvement of the Decision Making of Organization," Bulletin of Business and Economics (BBE), Research Foundation for Humanity (RFH), vol. 5(1), pages 10-19, March.
    17. Yuan, Jiahai & Li, Xinying & Xu, Chuanbo & Zhao, Changhong & Liu, Yuanxin, 2019. "Investment risk assessment of coal-fired power plants in countries along the Belt and Road initiative based on ANP-Entropy-TODIM method," Energy, Elsevier, vol. 176(C), pages 623-640.
    18. Chowdhury, Md. Maruf Hossan & Quaddus, Mohammed A., 2015. "A multiple objective optimization based QFD approach for efficient resilient strategies to mitigate supply chain vulnerabilities: The case of garment industry of Bangladesh☆,☆☆☆This manuscript was pro," Omega, Elsevier, vol. 57(PA), pages 5-21.
    19. Quan Xiao & Shanshan Wan & Fucai Lu & Shun Li, 2019. "Risk Assessment for Engagement in Sharing Economy of Manufacturing Enterprises: A Matter–Element Extension Based Approach," Sustainability, MDPI, vol. 11(17), pages 1-29, September.
    20. Chao Song & Jian-Qiang Wang & Jun-Bo Li, 2020. "New Framework for Quality Function Deployment Using Linguistic Z-Numbers," Mathematics, MDPI, vol. 8(2), pages 1-20, February.

    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:spr:joinma:v:30:y:2019:i:2:d:10.1007_s10845-016-1269-z. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.