NEWS    Jianlin Guo recently delivered an invited talk at 2022 6th International Conference on Intelligent Manufacturing and Automation Engineering

Date:

December 15, 2022 - December 17, 2022

Description:

The performance of manufacturing systems is heavily affected by downtime – the time period that the system halts production due to system failure, anomalous operation, or intrusion. Therefore, it is crucial to detect and diagnose anomalies to allow predictive maintenance or intrusion detection to reduce downtime. This talk, titled "Anomaly detection and diagnosis in manufacturing systems using autoencoder", focuses on tackling the challenges arising from predictive maintenance in manufacturing systems. It presents a structured autoencoder and a pre-processed autoencoder for accurate anomaly detection, as well as a statistical-based algorithm and an autoencoder-based algorithm for anomaly diagnosis.

External Link:

http://www.icima.org/

Research Areas:

Artificial Intelligence, Data Analytics, Machine Learning

• Related Publications

   Liu, B., Guo, J., Koike-Akino, T., Wang, Y., Kim, K.J., Parsons, K., Orlik, P.V., Hashimoto, S., Yuan, J., "Anomaly Detection and Diagnosis Using Pre-Processing and Time-Delay Autoencoder", IEEE International conference on emerging technologies and factory automation, September 2021.

  BibTeX TR2021-107 PDF

  • @inproceedings{Liu2021sep,
  • author = {Liu, Bryan and Guo, Jianlin and Koike-Akino, Toshiaki and Wang, Ye and Kim, Kyeong Jin and Parsons, Kieran and Orlik, Philip V. and Hashimoto, Shigeru and Yuan, Jinhong},
  • title = {Anomaly Detection and Diagnosis Using Pre-Processing and Time-Delay Autoencoder},
  • booktitle = {IEEE International conference on emerging technologies and factory automation},
  • year = 2021,
  • month = sep,
  • url = {https://www.merl.com/publications/TR2021-107}
  • }

   Liu, J., Guo, J., Orlik, P.V., Shibata, M., Nakahara, D., Mii, S., Takac, M., "Anomaly Detection in Manufacturing Systems Using Structured Neural Networks", IEEE World Congress on Intelligent Control and Automation, DOI: 10.1109/​WCICA.2018.8630692, July 2018, pp. 175-180.

  BibTeX TR2018-097 PDF

  • @inproceedings{Liu2018jul2,
  • author = {Liu, Jie and Guo, Jianlin and Orlik, Philip V. and Shibata, Masahiko and Nakahara, Daiki and Mii, Satoshi and Takac, Martin},
  • title = {Anomaly Detection in Manufacturing Systems Using Structured Neural Networks},
  • booktitle = {IEEE World Congress on Intelligent Control and Automation},
  • year = 2018,
  • pages = {175--180},
  • month = jul,
  • doi = {10.1109/WCICA.2018.8630692},
  • url = {https://www.merl.com/publications/TR2018-097}
  • }