Precision Maintenance With PARM and Augmented Reality for Asset Optimization

Abstract

The domain of equipment maintenance and asset management faces challenges related to minimizing downtime, optimizing asset performance, and reducing maintenance costs. Traditional maintenance approaches often rely on reactive strategies, leading to costly downtime and suboptimal asset performance. Moreover, the complexity of modern equipment necessitates innovative solutions for efficient maintenance and asset management. This study aims to revolutionize equipment maintenance and asset management by introducing precision maintenance, a proactive approach that integrates predictive AR maintenance (PARM) with augmented reality (AR) technology. The authors propose the PARM framework, which leverages real-time data from IoT sensors, predictive analytics, and immersive AR interfaces to enable technicians to perform maintenance tasks with unprecedented precision and efficiency. By predicting potential failures and providing real-time guidance through AR interfaces, Precision Maintenance empowers organizations to optimize asset performance and minimize downtime.