Abstract

Enterprise Resource Planning (ERP), Warehouse Management Systems (WMS), and Transportation Management Systems (TMS) are the foundation for managing contemporary supply chain, logistics, and manufacturing system operations. The dilemma is how to integrate these otherwise disparate systems harmoniously and simultaneously synchronize data real-time. This paper suggests a strong technical architecture to integrate data among ERP, WMS, and TMS systems, solving key problems such as data silos, slow information flow, and operational inefficiencies. The suggested solution employs a blend of Service-Oriented Architecture (SOA), RESTful APIs, and message queuing systems (such as Apache Kafka) to facilitate real-time, bidirectional communication between platforms. Through the use of a hybrid integration model, the architecture enables scalability, fault tolerance, and low-latency communication and hence can adapt to fluctuating transaction volumes. A canonical data model is employed to normalize information exchange across systems to ensure consistency and eliminate errors. The paper also delves into the technological stack, such as cloud-based integration platforms and middleware solutions that constitute the foundation of the system. A prototype was created and implemented in a live logistics environment, leading to dramatic gains in data accuracy, process efficiency, and decision-making speed. The integration method not only improves system interoperability but also facilitates a future-proof architecture that can evolve to meet the changing demands of digital supply chains. This study emphasizes the value of standardized integration and provides practical recommendations for organizations looking to simplify operations, eliminate manual data entry, and enhance overall system visibility.