Among the predictive maintenance technologies proposed by many scholars, the exponential-curve-fitting (ECF) model was commonly applied to predict the remaining useful life (RUL) of a target device. However, due to the algorithm’s limitations, when the target device is about to reach its end of life and the target device’s aging feature suddenly rises or becomes smooth, the ECF model may not be able to keep up with the real-time prediction. It may even falsely predict an overly long RUL. To solve the problem of inaccurate RUL prediction, the Time Series Prediction (TSP) algorithm is proposed. TSP applies the time series analysis model built from an information criterion to adapt to the highly complicated task of predicting faults of the target device. Also, the Pre-Alarm Module (PreAM) is introduced to raise an alert of immediate maintenance when a target device is likely to shut down shortly. The Death Correlation Index (DCI) is proposed to reveal the possibility if reaching the target device’s end of life. Real-world data is used to illustrate the TSP algorithm.
Time Series Prediction (TSP) Algorithm for Calculating Remaining Useful Life
Yu-Ming Hsieh (National Cheng Kung University) | TUM-Robotics Talks | 04. July 2023, 16:00 – 17:30 CEST
The lecture and discussion will take place at the Institute of Automation and Information Systems. It is a hybrid format, held simultaneously in person and online via Zoom. → Participation on site at Boltzmannstr. 15, Garching, Room MW 0150 (https://nav.tum.de/room/5501.EG.150). Please write to Jan Wilch (firstname.lastname@example.org)
→ If you would like to attend online, please use the following Zoom dial-in info: https://tum-conf.zoom.us/j/67241726272 Meeting-ID: 672 4172 6272 Code: 213563
Bio Soon after Yu-Ming Hsieh graduated from the Department of Computer Science and Information Engineering, National Cheng Kung University (NCKU), in 2015, he entered the eManufacturing Research Center (eMRC), NCKU, serving as a Postdoctoral Researcher. His main research interests include Predictive Maintenance, Yield Management, Virtual Metrology, e-Manufacturing, and Intelligent Manufacturing. Dr. Yu-Ming Hsieh is currently assistant professor in the Academy of Innovative Semiconductor and Sustainable Manufacturing, NCKU.
This talk was brought to you by the TUM Chair of Automation and Information Systems. TUM-Robotics Talks is an initiative of the Munich Institute of Robotics and Machine Intelligence (MIRMI) where international experts and pioneers in the field of Robotics and Machine Intelligence present their research.