Leveraging SAP Data for Predictive Maintenance in Manufacturing Systems
Author(s): Ravi Kumar Perumallapalli
Publication #: 2411013
Date of Publication: 07.01.2017
Country: USA
Pages: 1-8
Published In: Volume 3 Issue 1 January-2017
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 op-erational efficiency, this article investigates using SAP data to improve predictive maintenance tech-niques inside industrial systems.In the age of Industry 4.0, when sophisticated data analytics and inte-gration with IoT platforms are revolutionizing industrial operations, traditional maintenance tech-niques are frequently reactive and inefficient, insufficient. This research offers a systematic frame-work for preventive maintenance solutions by utilizing SAP's enterprise data and fusing it with pre-dictive analytics.The research emphasizes the significance of integrating SAP data with predictive maintenance to reduce equipment failures, thus enhancing production continuity. The original con-tributions 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 ap-proach. Insights from the latest advances in machine learning and IoT technologies have been incor-porated, highlighting the relevance of predictive maintenance solutions tailored to specific manufac-turing 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
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