Machinery Prognostics and Prognosis Oriented Maintenance Management

This book gives a complete presentatin of the basic essentials of machinery prognostics and prognosis oriented maintenance management, and takes a look at the cutting-edge discipline of intelligent failure prognosis technologies for condition-based maintenance.

• Presents an introduction to advanced maintenance systems, and discusses the key technologies for advanced maintenance by providing readers with up-to-date technologies
• Offers practical case studies on performance evaluation and fault diagnosis technology, fault prognosis and remaining useful life prediction and maintenance scheduling, enhancing the understanding of these technologies
• Pulls togeter recent developments and varying methods into one volume, complemented by practical examples to provide a complete reference

Jihong Yan, Professor and Head of Department of Industrial Engineering, Harbin Institute of Technology, China
Professor Yan has been working in the area of intelligent maintenance for over ten years, starting at the Centre for Intelligent Maintenance Systems (IMS) funded by NSF in the US as a researcher for three years, mainly focused on prognosis algorithm development. He then joined Pennsylvania State University in 2004 to work on personnel cross training related topics. From 2005 to the present he is a Professor at Harbin Institute of Technology, China. Professor Yan's research is focused on advanced maintenance of machinery, such as online condition monitoring, signal data pre-processing, feature extraction, reliability and performance evaluation, fault diagnosis, fault prognosis and remaining useful life prediction, and maintenance scheduling.