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An integrated SMED-fuzzy FMEA model for reducing setup time

Author

Listed:
  • Kübra Yazıcı

    (Türkisch-Deutsche Universität)

  • Seda Hatice Gökler

    (Sakarya University)

  • Semra Boran

    (Sakarya University)

Abstract

Today, the companies apply lean or customized production methods, which enable the production of different kinds of products in small quantities, to meet different customer demands. But, the increase in the product variety leads to an increase in the number of setups and thus production time. The companies aim to reduce the setup time by improving activities and by eliminating the problems causing extending setup time. Single minute exchange of die (SMED) method is the most common setup method that makes it possible to perform equipment setup operations in fewer than 10 min, i.e. several minutes expressed by a single digit. It is possible to further reduce setup times by integrating quality tools and methods into the SMED method. In this study, it is developed a novel SMED model that integrating the traditional SMED and fuzzy failure modes and effects analysis (fuzzy-FMEA) methods. Fuzzy FMEA method is used to prevent problems causing further extending setup time on setup activities. A new operation worksheet, “Setup Observation and Analysis Form” that leads the analyst in during the investigation of the machine and its set-up process, is also designed. The new approach is applied to set up a plastic injection mold for a pen manufacturing company. The setup time is reduced from 71.32 to 36.97 min, achieved a 48% improvement.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:joinma:v:32:y:2021:i:6:d:10.1007_s10845-020-01675-x
    DOI: 10.1007/s10845-020-01675-x
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    References listed on IDEAS

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    1. 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.
    2. Arash Geramian & Arash Shahin & Behzad Minaei & Jiju Antony, 2020. "Enhanced FMEA: An integrative approach of fuzzy logic-based FMEA and collective process capability analysis," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 71(5), pages 800-812, May.
    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. Bikram Jit Singh & Dinesh Khanduja, 2012. "Risk management in complex changeovers through CFMEA: an empirical investigation," International Journal of Industrial and Systems Engineering, Inderscience Enterprises Ltd, vol. 10(4), pages 470-494.
    5. 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.
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    Cited by:

    1. Xiaoyan Li & Xuedong Liang & Zhi Li, 2023. "The Strategy of Strengthening Efficiency and Environmental Performance of Product Changeover in the Multiproduct Production System," SAGE Open, , vol. 13(3), pages 21582440231, September.
    2. Yildiz Kose & Hatice Nida Civan & Ertugrul Ayyildiz & Emre Cevikcan, 2022. "An Interval Valued Pythagorean Fuzzy AHP–TOPSIS Integrated Model for Ergonomic Assessment of Setup Process under SMED," Sustainability, MDPI, vol. 14(21), pages 1-30, October.

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