Hybrid Decision-Making Program for Optimal Robot Selection Using MCDM

Robotics and automation have evolved rapidly, and sophisticated techniques are needed to choose the best robots for different tasks. This study introduces a hybrid decision-making process using multiple criteria to select robots. The proposed method evaluates robots based on performance, cost, reliability, and customization using multicriteria decision making (MCDM) and artificial intelligence (AI) algorithms System uses weight management for standard several types to assess the suitability of each robot for a particular application. Proving the effectiveness and reliability of the implementation required a robust algorithmic design, an easy-to-use interface, and extensive testing. The case studies and simulations show that the program's optimal selection outcomes improve industrial decision-making efficiency and effectiveness. This hybrid decision-making program is a major leap in robotics selection, providing corporations and researchers with a diverse and powerful tool to choose the best robots.