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A Multicriteria Decision-Making Method for Additive Manufacturing Process Selection

Ren, Diqian
http://orcid.org/0000-0003-3429-8928
http://rave.ohiolink.edu/etdc/view?acc_num=dayton1638911171558197

Abstract Details

2021, Doctor of Philosophy (Ph.D.), University of Dayton, Mechanical Engineering.
Due to the significant differences in the features and requirements of specific products and in the capabilities of various additive manufacturing (AM) solutions, selecting the most appropriate AM technology can be challenging. Given that the AM industry is also rapidly growing, and the capability of each AM technology is changing quickly, all AM processes must be evaluated in line with the latest AM information in order to make a wise selection. For that purpose, decision-makers need a decision-making system that can efficiently integrate their multiple requirements and the appropriate AM technologies. This research proposes a unique multicriteria decision-making (MCDM) solution, which employs an exclusive weightings calculation algorithm that converts the decision-makers’ subjective priority of the involved criteria into comparable values. This novel AM process selection system is powered by certainty pairwise comparisons (CPC) to assist decision-makers’ selection under ambiguous circumstances. Our CPC decision-making tool pairs each comparison result with its certainty to compute the weightings of the required criteria for the decision-making process. The proposed framework can reduce decision-makers’ comparison duty and potentially reduce errors in the pairwise comparisons. It also can be easily combined with other MCDM tools to help them better account for certainty levels and provide a more informed decision. To demonstrate the feasibility and reliability of the proposed methodology, a case study describes a detailed industrial application in rapid investment casting that applies the weightings to a tailored AM technologies and materials database to determine the most suitable AM process.
Jun-Ki Choi (Committee Chair)
Kevin Hallinan (Committee Member)
Kellie Schneider (Committee Member)
Andrew Chiasson (Committee Member)
85 p.
Mechanical Engineering
Additive Manufacturing; Multicriteria Decision Making; Rapid Investment Casting; Process Selection Advisory System

Recommended Citations

Citations

  • Ren, D. (2021). A Multicriteria Decision-Making Method for Additive Manufacturing Process Selection [Doctoral dissertation, University of Dayton]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1638911171558197

    APA Style (7th edition)

  • Ren, Diqian. A Multicriteria Decision-Making Method for Additive Manufacturing Process Selection. 2021. University of Dayton, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=dayton1638911171558197.

    MLA Style (8th edition)

  • Ren, Diqian. "A Multicriteria Decision-Making Method for Additive Manufacturing Process Selection." Doctoral dissertation, University of Dayton, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1638911171558197

    Chicago Manual of Style (17th edition)

dayton1638911171558197
63
© 2021, all rights reserved.
This open access ETD is published by University of Dayton and OhioLINK.