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United States | Information Technology | Volume 10 Issue 5, May 2021 | Pages: 1386 - 1390
IoT and ERP Integration for Real-Time Asset Monitoring and Maintenance
Abstract: The convergence of the Internet of Things (IoT) and Enterprise Resource Planning (ERP) systems represents a major advancement in digital manufacturing and asset management. IoT enables continuous data collection from connected sensors and devices, while ERP systems integrate enterprise-wide operations and decision processes. The lack of seamless integration between these technologies often limits the ability to achieve real-time visibility and predictive maintenance capabilities. This study presents a conceptual and implementation framework for integrating IoT with ERP to enable real-time asset monitoring and maintenance optimization. The proposed architecture employs middleware and standardized communication protocols such as MQTT and REST APIs to ensure interoperability between physical assets and ERP modules. Predictive analytics and machine learning models are embedded within the system to forecast equipment failures and automate maintenance workflows within the ERP environment. A case study in an industrial manufacturing setting demonstrates tangible improvements, including reduced downtime, enhanced asset utilization, and improved operational decision-making. The integration also supports greater data transparency and organizational agility, key enablers for Industry 4.0 transformation. Despite challenges related to cybersecurity, scalability, and legacy system compatibility, the findings affirm that IoT-ERP integration offers a sustainable pathway toward intelligent asset management and operational excellence.
Keywords: Internet of Things, ERP Integration, IoT ERP, Predictive Maintenance, Asset Management
How to Cite?: Paul Praveen Kumar Ashok, "IoT and ERP Integration for Real-Time Asset Monitoring and Maintenance", Volume 10 Issue 5, May 2021, International Journal of Science and Research (IJSR), Pages: 1386-1390, https://www.ijsr.net/getabstract.php?paperid=SR21531090432, DOI: https://dx.doi.org/10.21275/SR21531090432