A Study on the Equipment Data Collection and Developing Next Generation Integrated PHM System

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Published Jun 27, 2024
DEOGHYEON KIM Gun Sik Kim Ung Ho Nam Jin Woo Park

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

KIM, D., Kim, G. S. ., Nam, U. H., & Park, J. W. (2024). A Study on the Equipment Data Collection and Developing Next Generation Integrated PHM System. PHM Society European Conference, 8(1), 7. https://doi.org/10.36001/phme.2024.v8i1.4140
Abstract 204 | PDF Downloads 114

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Keywords

CBM, PHM, monitoring, CMS, AI, Robot, PLC, vibration monitoring, current monitoring, edge device, deep learning

References
Paulina Gackowiec (2019). General overview of maintenance strategies – concepts and approaches. Multidisciplinary Aspects of Production Engineering 2(1):126-139
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)
Section
Technical Papers