Selection of 3d printer for automobile spoilers using hybrid mcdm techniques

Abstract

newline This research examines the application of advanced Hybrid Multi Criteria Decision-Making (MCDM) techniques to improve the selection of 3D printer for fabricating automobile spoilers devised for radio-controlled (RC) cars. The paramount interest is on employing MCDM methods to identify and opt for the most suitable 3D printer and material combination, with a secondary emphasis on the practical aspects of production and testing of these materials. The research incorporated a range of sophisticated MCDM techniques to ascertain the optimal 3D printer. Initially, the Fuzzy Analytic Hierarchy Process (FAHP) was implemented to assign weights to various criteria, accommodating the inherent uncertainties and subjective judgments in the decision-making process. This was then integrated with the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), which ranked the 3D printers predicated on their closeness to an ideal solution. Additionally, FAHP was consolidated with Grey Relational Analysis (GRA) to appraise the degree of similarity between alternatives, amplifying the robustness of the ranking process. The FAHP-VIKOR method was executed to determine the best compromise solution by balancing conflicting criteria and making sure that the chosen option was the most feasible. FAHP was also paired with Elimination and Choice Expressing Reality (ELECTRE) to comprehensively rule out the less favourable options and deal with the most viable alternatives on the basis of specified criteria thresholds.