Abstract
Industrial robots are the core equipment of process automation and are becoming increasingly important in smart factories triggered by the Fourth Industrial Revolution. Therefore, if there is a problem with the core equipment of process automation, it is necessary to detect and prevent the failure of the equipment in advance, as it causes losses due to production disruption. In this study, we describe a technology that can detect abnormal conditions of robots based on artificial intelligence and ROM utilizing data collected from IoT sensors for industrial robots.
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References
Kamarul Bahrin, M.A., Othman, M.F., Nor Azli, N.H., Talib, M.F.: Industry 4.0: a review on industrial automation and robotic. Jurnal Teknologi 78, 6–13 (2016)
Berg, M.: Preventive maintenance policy for units subject to intermittent demand. Oper. Res. 32, 584–595 (1984)
Daymon, D., Bedir, T., Cagatay, C.: Predictive maintenance using digital twins: a systematic literature review. Inf. Softw. Technol. 151, 107008 (2022)
Why the Original Model of the P-F Curve Is the Correct Model. https://www.aladon.com/why-the-original-model-of-the-p-f-curve-is-the-correct-model. Accessed 9 Dec 2023
Hartmann, D., Herz, M., Wever, U.: Model order reduction a key technology for digital twins. In: Keiper, W., Milde, A., Volkwein, S. (eds.) Reduced-Order Modeling (ROM) for Simulation and Optimization, pp. 167–179. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-75319-5_8
Kingma, D.P., Welling, M.: Auto-encoding variational bayes. In: ICLR 2014 (2014)
ANSYS Motion. https://www.ansys.com/products/structures/ansys-motion. Accessed 9 Dec 2023
**ongzi, C., **song, Y., Diyin, T., Yingxun, W.: Remaining useful life prognostic estimation for aircraft subsystems or components: a review. In: 10th IEEE International Conference on Electronic Measurement & Instruments (ICEMI), vol. 2, p. 94. IEEE (2011)
ANSYS Twin Builder. https://www.ansys.com/products/digital-twin/ansys-twin-builder. Accessed 9 Dec 2023
Acknowledgment
This research was partly supported by Korea Institute of Science and Technology Information (No. (KISTI)K-22-L02-C05), and This work was partly supported by the Technology development Program (No. RS-2022–00156471) funded by the Ministry of SMEs and Startups (MSS, Korea).
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Kim, Ng., Seo, D. (2024). A Study on Predictive Maintenance System for Industrial Robot RV Reducers Based on AI and ROM. In: Pei, Y., Ma, H.S., Chan, YW., Jeong, HY. (eds) Proceedings of Innovative Computing 2024, Vol. 4. IC 2024. Lecture Notes in Electrical Engineering, vol 1217. Springer, Singapore. https://doi.org/10.1007/978-981-97-4182-3_41
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DOI: https://doi.org/10.1007/978-981-97-4182-3_41
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