IEEE International Workshop on Predictive Maintenance (PM 2024)


Empowered by the advancement of smart sensing and machine learning algorithms, predictive maintenance has become one of the main value-adding schemes for industrial 4.0. Predictive maintenance goes beyond time-based preventive maintenance and condition-based maintenance. It harvests the power of industrial big data and reduces the risk of system failure in a proactive manner. To meet requirements of future industrial operations, the concept of predictive maintenance should be further explored and tested in the practical context. This workshop is organized for researchers who rally around the topic of predictive maintenance to overcome several existing challenges:

  1. Failure data is often scarce in practice. The predictive algorithm often needs to operate on the imbalanced dataset.
  2. Due to the stochastic nature of the deterioration process, algorithms only predict the remaining useful life (RUL) is insufficient. The variance/uncertainty of RUL should also be estimated.
  3. To demonstrate the comparative advantage of predictive maintenance, innovative decision-making algorithms should be further designed based on the RUL.
  4. Approaches or case studies on applying predictive maintenance in large-scale systems are still underexplored.


The list of topics includes, but is not limited to:

  • RUL prediction based on imbalanced dataset
  • Variance inference for RUL
  • Intelligent decision making based on RUL
  • Predictive maintenance in systems
  • Meta-learning for predicting RUL
  • Transfer-learning for predicting RUL
  • Predictive group maintenance
  • Prognostic Health Management
  • Best practice for predictive maintenance


Authors are invited to submit original unpublished research papers as well as industrial practice papers. Simultaneous submissions to other conferences are not permitted. Detailed instructions for electronic paper submission, panel proposals, and review process can be found at QRS submission.

Each submission can have a maximum of ten pages. It should include a title, the name and affiliation of each author, a 300-word abstract, and up to 6 keywords. Shorter version papers (up to six pages) are also allowed.

All papers must conform to the QRS conference proceedings format (PDF | Word DOCX | Latex) and Submission Guideline set in advance by QRS 2024. At least one of the authors of each accepted paper is required to pay the full registration fee and present the paper at the workshop. Submissions must be in PDF format and uploaded to the conference submission site. Arrangements are being made to publish extended version of top-quality papers in selected SCI journals.


Program Chairs

Zhenglin Liang's avatar
Zhenglin Liang

Tsinghua University

Yan-Fu Li's avatar
Yan-Fu Li

Tsinghua University

Program Committee

Name Affiliation
Bin Liu University of Strathclyde
Yiliu Liu Norwegian University of Science and Technology
Huixing Meng Beijing Institute of Technology
Rui Peng Beijing University of Technology
Hui Xiao Southwestern University of Finance and Economics
Xiujie Zhao Tianjin University

Previous PM

  • PM 2022 - Guangzhou (in conjunction with QRS 2022)
  • PM 2021 - Hainan Island (in conjunction with QRS 2021)
  • PM 2020 - Macau (in conjunction with QRS 2020)