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Optimizing 3D printing facility selection for ubiquitous manufacturing using an evolving fuzzy big data analytics approach

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Abstract

Three-dimensional (3D) printing has been considered a sustainable and competitive tool for manufacturing products and their components in numerous industries. However, since there are more and more available 3D printing facilities providing unequal services, choosing a suitable 3D printing facility remains a challenging task to manufacturers. In addition, a decision maker also needs to make negotiation between selection criteria that may be conflicting and dependent. To overcome this challenge, this study proposes an evolving fuzzy big data analytics approach. In the proposed methodology, the modified evolving fuzzy assessment (MEFA) method is devised to improve the accuracy of deriving the fuzzy priorities of criteria efficiently. Subsequently, to remove the dependency between criteria, PCA is applied. Finally, the dependency-removed fuzzy technique for order preference via similarity to ideal solutions (FTOPSIS) (Dr-FTOPSIS) is proposed to assess and compare the 3D printing facilities under consideration. The evolving fuzzy big data analytics approach has been applied to a real case of choosing suitable 3D printing facilities in a prosthetic limb supply chain. The experimental results supported the effectiveness of the proposed methodology in improving the derivation process and making a more reasonable choice of suitable 3D printing facilities. The MEFA approach increased the efficiency of deriving fuzzy priorities by 80%. In addition, the overall performance of the best 3D printing facility recommended by the proposed methodology was about 7% better than those recommended by the existing methods.

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Authors and Affiliations

  1. Department of Industrial Engineering and Management, National Yang Ming Chiao Tung University, Hsinchu City, Taiwan

    Tin-Chih Toly Chen

  2. Department of Industrial Engineering and Systems Management, Feng Chia University, Taichung City, Taiwan

    Chi-Wei Lin

  3. Department of Industrial Engineering and Management, National Chin-Yi University of Technology, Taichung City, Taiwan

    Min-Chi Chiu

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  1. Tin-Chih Toly Chen
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  2. Chi-Wei Lin
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  3. Min-Chi Chiu
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Correspondence to Chi-Wei Lin.

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Chen, TC.T., Lin, CW. & Chiu, MC. Optimizing 3D printing facility selection for ubiquitous manufacturing using an evolving fuzzy big data analytics approach. Int J Adv Manuf Technol 127, 4111–4121 (2023). https://doi.org/10.1007/s00170-023-11799-y

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