A USE OF ARTIFICIAL INTELLIGENCE FOR PROCESS OPTIMIZATION IN MECHANICAL ENGINEERING OPERATIONS

Abstract

The application of Artificial Intelligence (AI) in mechanical engineering operations is transforming traditional processes, enhancing efficiency, and enabling optimization across various domains such as design, manufacturing, maintenance, and quality control. This study explores the integration of AI technologies like machine learning, deep learning, robotics, and data analytics in mechanical engineering, with a focus on their roles in process optimization. By leveraging AI, engineers can predict equipment failures, reduce downtime, optimize designs, and improve overall productivity. Despite the significant advantages, the implementation of AI also faces challenges, including technical barriers and resistance to change. The study also discusses future opportunities for AI in mechanical engineering, including advancements in reinforcement learning, quantum computing, and edge AI. As AI continues to evolve, it holds the potential to redefine the future of mechanical engineering by fostering innovation, sustainability, and greater operational efficiency.