Performance Indicators for the Robotics Engineering Operational Scheduling

This study examines multi-stage robotic production line performance via queuing analysis to enable more accurate resource planning. It is one of a select few studies of this type designed to boost the efficiency of manufacturing robots with many stages. The goal of this study is to assist managers in increasing productivity and effectiveness while choosing the best policy for assembly systems. The study utilizes an analytical methodology based on actual data from a firm that manufactures robots. The process of making a robot involves several different processes, including identifying the problem, researching and designing the solution, developing a prototype, building the robot, programming and testing the robot, and ultimately assessing the robot. The necessary information for each workstation was gathered, and the Supplementary Variable approach was used to ascertain the processing component arrival and departure distribution statistics. The queueing analysis presented in this work serves as a foundation for predicting and analyzing production systems using metrics like utilization, the proportion of idle workstations, the number of batches in the system, the number of batches in the queue, the expected time spent in the queue, and the expected time spent in the system.