A Study on the Equipment Data Collection and Developing Next Generation Integrated PHM System
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Abstract
This research presents an integrated PHM system for 2,000 rotating equipment units across press, car body, paint, and assembly lines in Hyundai/Kia factories. The system addresses limitations of individual monitoring systems by consolidating vibration, current, robot AI diagnostics, PLC backup status, and operational data. Vibration monitoring utilizes wired/wireless sensors, server storage, and automated analysis for trend detection and fault diagnosis. PLC data monitoring retrieves motor drive information (current, temperature, frequency, etc.) to predict equipment anomalies.
Robot monitoring integrates with various manufacturers and tracks operational status, motor load, and alarms for maintenance and lifespan management. The PLC backup solution ensures proper backup functionality. The integrated PHM architecture manages data collection, analysis, diagnostics, reporting, and visualization, enabling comprehensive equipment health monitoring and proactive maintenance.
How to Cite
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CBM, PHM, monitoring, CMS, AI, Robot, PLC, vibration monitoring, current monitoring, edge device, deep learning
DOI:10.2478/mape-2019-0013
Sudhanshu Goel (2022). A Methodical Review of Condition Monitoring Techniques for Electrical Equipment. papers.phmsociety.org
ISO 18436-2:2014 Condition monitoring and diagnostics of machines — Requirements for qualification and assessment of personnel — Part 2: Vibration condition monitoring and diagnostics
Nandi, S., Toliyat, H.A. and Li, X. (2005) Condition Monitoring and Fault Diagnosis of Electrical Motors—A Review. IEEE Transactions on Energy Conversion, 20, 719-729 Niklas Tritschler, Andrew Dugenske, Thomas Kurfess. (2021). An Automated Edge Computing-Based Condition Health Monitoring System: With an Application on Rolling Element
Bearings. Journal of Manufacturing Science and Engineering. Jul 2021, 143(7): 071006 (8ps)
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