Identification of Evaluation Criteria in Industrial Robot Selection using GRA method

The selection of an optimal industrial robot is a critical decision that can significantly impact the efficiency and productivity of manufacturing processes. In this context, the Grey Relational Analysis (GRA) method provides a systematic and objective approach to evaluate and rank different robot options based on multiple criteria. This paper explores the application of the GRA method in industrial robot selection. The GRA method allows decision-makers to consider various factors simultaneously, incorporating both quantitative and qualitative criteria. By assigning appropriate weights to each criterion and calculating the grey relational grade, the GRA method facilitates the identification of the most suitable industrial robot option for a specific application. Through the GRA method, organizations can effectively assess the performance of industrial robots based on criteria such as payload capacity, reach, speed, flexibility, safety features, maintenance requirements, and cost. The interrelationships and interactions among these criteria are also taken into account, providing a holistic understanding of the robots' performance relative to each other and their alignment with the specific application requirements. Furthermore, the GRA method enables decision-makers to rank the robot options based on their grey relational grades, allowing for a clear comparison of their performance. This ranking assists in identifying the most promising robot options that warrant further consideration and evaluation. The application of the GRA method in industrial robot selection provides decision-makers with a structured framework and quantitative analysis, facilitating informed decisions that lead to the selection of an optimal industrial robot. This, in turn, can enhance productivity, efficiency, and overall success in manufacturing processes. The rapid advancements in technology have led to the widespread adoption of automation in various industries. Industrial robots have emerged as a vital component of this automation revolution, offering increased productivity, precision, and efficiency in manufacturing processes. However, with a wide range of options available in the market, selecting the optimal industrial robot for a specific application can be a complex task. The process of industrial robot selection requires careful consideration of several factors to ensure that the chosen robot meets the unique requirements of the application and delivers the desired outcomes. This introduction aims to provide an overview of the importance of optimal industrial robot selection and the key factors that need to be taken into account during the decision-making process. we will use the GRA in this study, which is a research approach that gives decision making trial and evaluation laboratory to make conclusions based on their relative relevance in a data. Alternative parameters taken as R-robot selection r1, r2, r3, r4, r5, r6, r7. Evaluation parameters taken as load capacity (LC), maximum tip speed (MTS), memory capacity (MC), manipulator reach (MR), repeatability (RE), purchase cost (PC). From the result it is seen that robot selection 1 is got the first rank where as is the robot selection 6 is having the lowest rank. The Grey Relational Analysis (GRA) method offers a systematic and objective approach for selecting the optimal industrial robot. By considering multiple criteria and their interrelationships, decision-makers can evaluate and rank different robot options. The GRA method provides valuable insights into the performance and suitability of each option, aiding in informed decision-making. It allows for a comprehensive evaluation of factors such as payload capacity, reach, speed, flexibility, safety features, maintenance requirements, and cost. By applying the GRA method, organizations can make efficient and effective choices, ultimately selecting the industrial robot that best meets their specific application requirements.