Leveraging SAP Data for Predictive Maintenance in Manufacturing Systems

Abstract

Leveraging data-driven insights has become vital for optimizing maintenance procedures in today's continuously changing manufacturing market. To minimize unscheduled downtime and maximize operational efficiency, this article investigates using SAP data to improve predictive maintenance techniques inside industrial systems.In the age of Industry 4.0, when sophisticated data analytics and integration with IoT platforms are revolutionizing industrial operations, traditional maintenance techniques are frequently reactive and inefficient, insufficient. This research offers a systematic framework for preventive maintenance solutions by utilizing SAP's enterprise data and fusing it with predictive analytics.The research emphasizes the significance of integrating SAP data with predictive maintenance to reduce equipment failures, thus enhancing production continuity. The original contributions include a practical methodology for leveraging SAP systems in predictive maintenance and presenting case studies from the manufacturing sector that demonstrate the effectiveness of this approach. Insights from the latest advances in machine learning and IoT technologies have been incorporated, highlighting the relevance of predictive maintenance solutions tailored to specific manufacturing challenges. This paper contributes to the broader field of smart manufacturing and sets the stage for future developments in intelligent asset management and predictive maintenance systems.

Keywords: Predictive Maintenance, SAP Data Integration, Manufacturing Systems, Real-time Data Processing, SAP Predictive Analytics