A generic method for multi-criterion decision-making problems in design for additive manufacturing
International Journal of Advanced Manufacturing Technology, ISSN: 1433-3015, Vol: 115, Issue: 7-8, Page: 2083-2095
2021
- 12Citations
- 30Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
In this paper, a generic method based on fuzzy aggregation operator for multi-criterion decision-making problems in design for additive manufacturing is proposed. Firstly, a fuzzy power weighted Maclaurin symmetric mean operator based on Hamacher T-norm and T-conorm is constructed via a combination of fuzzy numbers, power average operator, weights, Maclaurin symmetric mean operator, and operational rules of fuzzy numbers based on Hamacher T-norm and T-conorm. Based on the constructed operator, a generic method for solving the multi-criterion decision-making problems in design for additive manufacturing is then developed. After that, an example of additive manufacturing machine and material selection and an example of optimal build direction selection are introduced to illustrate the developed method. Finally, a set of numerical experiments are reported to demonstrate the effectiveness and capabilities of the method. The demonstration results suggest that the method can effectively solve a multi-criterion decision-making problem in design for additive manufacturing and has the characteristics in considering the interactions of criteria, reducing the effect of noise criterion values, and capturing the risk attitude of decision-makers.
Bibliographic Details
Springer Science and Business Media LLC
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