Nowadays, where Industry 4.0 is discussed extensively, the selection of industrial robots has become an important issue. These robots enable production companies to produce higher quality products with high efficiency and in a cost-effective manner. However, an incorrect selection of these robots can cause significant losses for companies. Various factors need to be considered for the effective selection of industrial robots. In this study, a decision model is presented for industrial robot selection. Quality function deployment (QFD), a well-known and powerful tool that converts customer requirements into final design characteristics, is used in this study, with Group Decision Making (GDM) perspective. In GDM, decision-makers who have different backgrounds or ideas can state their preferences in various formats. The Multiple Preference Relations (MPR) technique is used to combine different assessments. Therefore, this study combines QFD with MPR to handle the different forms of information while calculating the customer requirements importance. Furthermore, the Complex Proportional Assessment (COPRAS) method is used to choose the most suitable industrial robot for the proposed study. The presented method was analyzed in a case study on the robot selection problem for the assembly line of a company operating in the manufacturing industry. The alternatives evaluated with the COPRAS method were also applied with the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. The results of both methods were compared and found to be consistent.