A Distribution Network Design Model for Additive Manufacturing

Ertemel, Adnan Veysel; Ertemel, Sinan; Coktug, Cemil Can; Erk, Ali Can; Görener, Ali

doi:10.1007/978-3-030-76724-2_20

Cited by 1 publication

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“…In the future, the suggested technique may be used in other projects to address a range of additional problems e.g., supply chain model evaluation [91], interval-valued Pythagorean fuzzy sets may be used to increase the fuzziness modeling capacity of the methodology; other fuzzy sets, such as neutrosophic sets, may be used with the CRITIC integrated EDAS technique; other possible variants of this technique, such as WASPAS or DEMATEL integrated CRITIC can be developed and applied to other sectors; and finally, the stability of the suggested study against rank-reversal events may be assessed by other academics using the suitable analytic techniques.…”

Section: Discussionmentioning

confidence: 99%

Additive manufacturing process selection for automotive industry using Pythagorean fuzzy CRITIC EDAS

et al. 2023

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For many different types of businesses, additive manufacturing has great potential for new product and process development in many different types of businesses including automotive industry. On the other hand, there are a variety of additive manufacturing alternatives available today, each with its own unique characteristics, and selecting the most suitable one has become a necessity for relevant bodies. The evaluation of additive manufacturing alternatives can be viewed as an uncertain multi-criteria decision-making (MCDM) problem due to the potential number of criteria and candidates as well as the inherent subjectivity of various decision-experts engaging in the process. Pythagorean fuzzy sets are an extension of intuitionistic fuzzy sets that are effective in handling ambiguity and uncertainty in decision-making. This study offers an integrated fuzzy MCDM approach based on Pythagorean fuzzy sets for assessing additive manufacturing alternatives for the automotive industry. Objective significance levels of criteria are determined using the Criteria Importance Through Inter-criteria Correlation (CRITIC) technique, and additive manufacturing alternatives are prioritized using the Evaluation based on Distance from Average Solution (EDAS) method. A sensitivity analysis is performed to examine the variations against varying criterion and decision-maker weights. Moreover, a comparative analysis is conducted to validate the acquired findings.

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Section: Discussionmentioning

confidence: 99%