RESEARCH ON GRA, PSI AND MOORA METHODS FOR OPTIMAL 3D PRINTER SELECTION

Abstract

This paper presents the application of MCDM methods to optimize the selection of 3D printers based on 8 technical criteria and prices of 7 individual printer models. Three methods are used, including GRA (Grey Relational Analysis), PSI (Preference Selection Index) and MOORA (Multi Objective Optimization on the Basis of Ratio Analysis) to compare and determine the optimal choice. The results show that all three methods identify Ender 3 V3 (P3) as the most optimal solution, although there is a difference in the ranking order of the remaining solutions. This difference is mainly due to the difference in the data normalization process and the determination of the weights of each method. MOORA uses vector normalization, while PSI and GRA use max-min normalization. In addition, GRA and MOORA also consider the criteria in positive, negative and nominal directions, while PSI does not do this. The study confirms the applicability of MCDM methods in the problem of optimal machine selection.