Sustainable technology selection in additive manufacturing: an integrated fuzzy decision analysis framework

Abstract

The selection of technologies in additive manufacturing (AM) is pivotal for advancing production systems that are economically viable, environmentally responsible, and socially beneficial. This study proposes an integrated multi-criteria decision analysis (MCDA) framework to address the technology selection problem, comparing the baseline technology of injection molding with fused deposition modeling (FDM)-based AM technologies. The framework employs the best-worst method (BWM) to determine the weights of sustainability criteria, followed by the application of the fuzzy technique for order preference by similarity to the ideal solution (FTOPSIS) to rank alternatives. A case study on healthcare components is used to demonstrate the approach. The results highlight distinct decision-making priorities among stakeholder groups: economic considerations are most important to AM experts, the AM education group prioritizes environmental factors, and healthcare professionals deem social factors the most significant. Furthermore, the rankings for different healthcare products vary across these groups, illustrating the influence of weighted criteria on technology preferences. Sensitivity analysis confirms the robustness and reliability of the findings. This study provides a valuable framework for addressing tactical-level decisions related to AM technology selection and offers insights that can serve as foundational input for optimizing AM networks involving diverse technologies.