Endüstriyel Robot Seçiminde Hibrit Çok Kriterli Karar Yaklaşımı

Abstract

Numerous manufacturing companies worldwide have widely adopted industrial robots due to their advantages, such as increased efficiency and profitability. Robots with numerous features and abilities are available for a wide variety of applications. They can handle numerous tasks in various industrial applications, including welding, assembly, material handling, loading, and painting. The selection of a robot for a particular application is a multifaceted task due to its complexity, advanced features, and facilities. The decision-maker needs to choose the most suitable robot, taking into account the various features, maximizing benefits, and minimizing costs. In this context, the main objective of this study is to present an integrated multiple criteria decision analysis (MCDA) approach for industrial robot selection. The selection of the optimal robot is conducted based on three weighting methods, namely standard deviation (SD), mean weight (MW), and Shannon entropy, and three MCDA methods, namely additive ratio assessment (ARAS), simple additive weighting (SAW), and weighted product method (WPM). The objective weighting methods, SD, MW, and Shannon entropy, are adopted to eliminate subjective evaluations while determining attribute weights. Using the output of each weighting method as the input of each MCDA method, nine different ranking models are developed. The correlation between all models is examined through Kendall’s correlation coefficients. The results of all method pairs are integrated through the Borda method to reach a final consensus ranking. The results indicate that the proposed hybrid approach can be utilized successfully for the purpose of the present study, and ARAS is the most robust method.