Abstract
Additive Manufacturing (AM) is an umbrella term encompassing numerous processes altogether. Each AM technology has its benefits and limitations, and each one can be more fitting for specific applications than others. Evolution of supply chains by the AM technologies delivers companies competitive advantages and substantial benefits. From lower risks and costs to greater agility and flexibility are some of the potential values to be explored. AM technology has evolved with rapid development in recent years. While the choices are in abundance, the selection of a suitable choice is a nontrivial task. In this study, an easy to use Multi-Criteria Decision Making (MCDM) methodology is proposed to assist selection of the right 3D printing (AM) technology and evaluate their suitability for the needs of supply chains. In order to improve the reliability and validate the evaluation method, this paper develops a decision-making model based on the Combinative Distance-Based Assessment (CODAS) under Pythagorean Fuzzy (PF) setting and carries out a case study with a sensitivity analysis. First of all, a new approach has been proposed to support the claim; the supply chains for the evaluation system is analyzed. Moreover, then, a selection criterion for AM technology selection is established to create a model based on PF CODAS approach and prospect theory. Finally, the pros and cons and the limitations of the proposed method are discussed. This study is one of the first studies to offer an empirical contribution to the vastly conceptual discussion.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
