Leveraging Intelligent Agents in Industrial Engineering: Use Cases in Predictive Maintenance and Supply Chain Optimization

Abstract Industrial struggle with machine breakdown, inefficient processes, and supply chain.Disupts which are regular. These issues also produce delays and increased costs. And saw decreased productivity. Also it is the case that which traditional systems react only after a problem has Already present, which in turn puts pressure on businesses to become less efficient and less competitive. This Artificial intelligence and intelligent agents is the area where. In terms of Through use of machine learning and smart automation, which is what organizations do that have success in this area, they predict problems at an early stage. Streamline operations and improve decision speed and quality. This study Presents two case studies which in the first we see how AI plays a role in predictive maintenance. Machines break down less often which in turn allowsthem to run continuously. The second case study. Explores how AI is used in supply chain logistics. Both cases saw considerable and meaningful improvements with the implementation of artificial intelligence. In predictive maintenance, for example, the AI models were very effective in identifying early symptoms of equipment failure, which would significantly reduce machine downtime and lengthen the total lifespan of the equipment. In the Supply Chain , AI agents improved the interaction between supply chain stages which in turn enabled faster. Decision on which items to stock and also in how we handle stock levels which in turn leads to faster recovery from disruptions. These results present that which AI brings to the table in terms of efficiency, cost savings, and flexibility.