ROBOTICS: AN APPROACH TO INCREASE EFFICIENCY OFAI IN THE WORKPLACE

Abstract

The convergence of robotics and artificial intelligence in revolutionizing efficiency in the workplace, optimizing processes and enhancing innovation in industries cannot be overstated. Today, ideas in robotics that were just science fiction in years gone by have become a reality in many industries, with robots enabled with AI technology greeting customers in stores and offering them personalized information and directions. This study aims to analyze the symbiotic relationship between robots and AI, with specific reference to how robots can assist in AI processes in different industries as this study has created a programmed collaborative robot (cobot) to help in enhancing Artificial Intelligence in different industries by creating a unique robotic model to assist in AI processes and also to enable it to function independently without human intervention like cobots do in order to move slower in order to enhance human safety. Additionally, the role of collaborative robots in manufacturing, healthcare, and logistics industries was explored, with their potential for enhancing productivity, safety, and cost reduction highlighted. This is to enable the robot to think like a human as a machine and learn from data or make decisions automatically. With a review of the mixed approach of using case studies and examples from industries as Methodology, we are able to prove that with the use of robots that are artificially intelligent, it is possible to streamline workflow, improve decision-making, and increase efficiency. For training, a Recurrent Neural Network (RNN) Algorithm was used, while Python Jupyter was used for programming, with the result indicating that the average productivity gain across all industries was found to be 27.5%, whereas the average error reduction was 25%. The maximum productivity gain was found in the logistics industry, which reached 35%, whereas in the manufacturing sector, the maximum error reduction was found to be 40%. We also present the challenges and limitations in implementing robots and AI systems, which include job displacement, ethical issues, and integration complexities