CANCELLED: PHM Approaches for Complex Engineering Systems (PACES) Workshop
Friday, April 24, 2020
8:00 a.m.-5:30 p.m.
A. James Clark School of Engineering, University of Maryland, College Park; Room Kay Boardroom
Over the past two decades, significant advances in sensing and computing have led to an explosion of new data and algorithms designed to monitor device health. There exist a variety of prognostics and health management (PHM) approaches for many types of mechanical and electrical components.
However, the methods and tools applicable at the component level are unsuitable for modeling complex engineering systems, such as power plants, chemical process facilities, transportation technologies, and infrastructure.
These systems consist of many interconnected, hardware, software and human elements and involve dynamic operations and complicated physical processes.
Furthermore, the available PHM data is of varying qualities, from multiple sources, in multiple formats, and at multiple scales.
The workshop will bring together disciplinary experts to: (1) assess the current state of the art in PHM approaches for complex engineering systems, (2) explore the types of data and methodologies could enable the complex system PHM, and (3) identify case studies which can provide a testbed for comparing different approaches.
Developing PHM capabilities for complex engineering systems requires a new perspective and clear theoretical, mathematical, and computational foundations. UMD has recently developed the PACES (PHM Approaches for Complex Engineering Systems) framework.
- Discuss the state of the art, identify gaps and offer opportunities for R&D efforts in PHM
- Discuss PHM in different disciplines of: energy, aerospace, transportation, automotive, human health & performance, smart manufacturing, and industry AI
- PHM challenges in critical mission systems; applications and solutions
- To promote interdisciplinary and international collaboration in PHM
The Center for Risk and Reliability
ASME's Safety Engineering and Risk/Reliability Division