Optimizing Robotic Prosthetic Palm Design through Integration of LOPCOW, COBRA, and EDAS for Efficient 3D Printing Material Selection

This research presents a novel multi criteria decision making (MCDM) approach for optimizing material selection in the design of a robotic prosthetic palm, a critical component in assistive and rehabilitation technologies. The research addresses the urgent need for a systematic approach to improve material efficiency and design precision in affordable prosthetic solutions. This study uses LOPCOW to find weights and applies COBRA and EDAS methods to thoroughly evaluate and select the best 3D printing material based on their mechanical, physical, and economic properties. Key parameters such as tensile strength, elastic modulus, Poisson’s ratio, von misses stress, mass density, displacement, equivalent strain, and cost were considered in the analysis. Among the 11 material evaluated, Acrylic (MT-3) emerged as the most efficient alternative, followed by PET (MT-8) and PA Type 6(MT-5). The use of Copeland voting rule, spearman correlation (0.9364) and sensitivity analysis validated the consistency and reliability of the integrated MCDM process. This methodology not only ensures optimal material selection for enhanced prosthetic performance but also demonstrates practical potential in manufacturing application in in biomedical engineering.