A Robotic Process Automation-Based System for Intelligent Work Order Management with Active Service in Power System

With the accelerated digital transformation of power systems, the efficiency and quality of work order processing have emerged as critical factors impacting power supply reliability and user satisfaction. Current workflows, heavily reliant on manual operations, suffer from redundant processes, delayed responses, and insufficient real-time monitoring, leading to risks of order timeouts and repeated complaints. To address these challenges, this study proposes a closed-loop work order management system driven by Robotic Process Automation (RPA). Leveraging screen data scraping, Optical Character Recognition (OCR), and image processing technologies, the solution integrates automated modules, including system auto-reconnection, intelligent order dispatching, and supervision entry. The experimental results demonstrate significant improvements: single-order processing time is reduced from 8 minutes to 2 minutes with 99.7^% accuracy, while 24/7 real-time monitoring decreases manual intervention by 80%. Additionally, a proactive alert mechanism transforms grid services from “reactive response” to “proactive governance”. This research systematically validates the feasibility of RPA in complex work order scenarios and provides a replicable technical framework for advancing digital transformation in the power industry.