OPTIMIZATION OF WAREHOUSE OPERATIONS THROUGH THE INTEGRATION OF ROBOTICS AND ARTIFICIAL INTELLIGENCE: ENHANCING EFFICIENCY, ACCURACY AND AUTOMATION IN MODERN SUPPLY CHAINS

Abstract

Organizations need to adapt consistently changing environmental factors for providing service to current market clients throughout all industries. The logistics sector falls under this application. Companies operating international warehouses need to provide fast order fulfillment for products moved throughout every part of the world. This research seeks to explore process optimization methods that fulfill the modern market requirements. The goal is to maximize operations with artificial intelligence and automated process optimization. The presentation includes illustrations of operational problems within a benchmark firm that could benefit from combining artificial intelligence (AI) with automated systems. This article reveals the discovery of an automated warehouse management system which improves picking efficiency. Integrating automation for storage and retrieval into the system effectively reduces waste and raises accuracy for picking and transportation processes and storage operations. The report lists down the beneficial aspects of artificial intelligence. The process of inventory planning becomes more precise while route planning at the picking stage experiences improved efficiency. The study establishes theoretical evidence to support warehouse managers making automation and AI part of their operations. The reference company will benefit from insights into its operations because the research findings supply primary advantages and remedies which match up against its current processes and demand further AI implementation