FMECA of extrusion–feeding system in industrial 3D printers based on AHP–fuzzy VIKOR method

Abstract

With the rapid development of additive manufacturing, its applications in medicine and aerospace have expanded significantly, placing higher demands on product performance and operational reliability. To address this issue, an improved risk assessment framework for industrial 3D printers is proposed in this study. A Quality Impact Factor (QF) is introduced based on traditional FMECA to better capture the influence of failure modes on final product quality. The Analytic Hierarchy Process (AHP) is employed to determine the weights of risk factors, and the fuzzy VIKOR method is further applied to obtain a comprehensive ranking of failure modes. The proposed method is validated through a case study of an industrial 3D printing system. Results show that the nozzle temperature sensor failure is identified as the most critical failure mode. Moreover, the proposed approach overcomes the limitation of traditional FMECA, where identical RPN values reduce ranking discrimination. The method therefore enhances the accuracy and discriminability of risk evaluation and provides effective support for reliability-oriented design and maintenance of 3D printing equipment.