Conferences

PHM18

Philadelphia, Pennsylvania
24 - 27 September 2018

Key Dates

  • Paper Submission Due: 30 Apr 2018 14 May 2018
  • Doctoral Symposium Submission Due: 7 May 2018
  • Paper Review Feedback: 1 Jul 2018
  • Final Papers Due: 1 Aug 2018

PHME18

Utrecht, The Netherlands
3 - 6 July 2018

Performance Assessment of a Wind Turbine Using SCADA based Gaussian Process Model
Ravi Pandit, David Infield    Read
Traffic sensor health monitoring using spatiotemporal graphical modeling
Linjiang Wu, Chao Liu, Tingting Huang, Anuj Sharma, Soumik Sarkar    Read
Verification of Prognostic Algorithms to Predict Remaining Flying Time for Electric Unmanned Vehicles
Edward F. Hogge, Brian M. Bole, Sixto L. Vazquez, Chetan S. Kulkarni, Thomas H. Strom, Boyd L. Hill, Kyle M. Smalling, Cuong C. Quach    Read
Selecting Suitable Candidates for Predictive Maintenance
Wieger Tiddens, Jan Braaksma, Tiedo Tinga    Read
  

In Memoriam

Dr. Myeongsu (Kay) Kang

Dr. Myeongsu Kang passed away unexpectedly Saturday, July 28, at his home. He was 38 years old. Dr. Kang was a member of the Center for Advanced Life Cycle Engineering (CALCE) at the University of Maryland.

Dr. Kang received B.E. and M.S. degrees in computer engineering and information technology and a Ph.D. in electrical, electronics, and computer engineering from the University of Ulsan, South Korea. When he joined CALCE in September 2015, he brought expertise in data analytics, machine learning, system modeling, and statistics that he applied to research in prognostics and health management (PHM). Dr. Kang published more than 60 journal papers in the field of PHM and high-performance multimedia signal processing. He recently finished editing a book on electronics PHM that will be published shortly. He also developed and taught a course on PHM.

Kay is survived by his wife Yeoung-Seon and two sons, Matthew and Mark.

  

INRIA, APSYS-AIRBUS and NOKIA Germany are working together for a European funding project "EIT Digital- Industry 4.0"dedicated to predictive maintenance et more precisely to Root Cause Analysis.

The goal of the project is to develop a set of data-science methods, algorithms and plugins to enable manufacturers identify why and where a failure or anomaly occurred and ease dysfunctional goods reparation.

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An Inria spin-off, PAM is a software publisher dedicated to predictive maintenance for industry. On the strength of several collaborative ventures with large-scale industrial firms, we wish to continue developing a solution that integrates the latest R&D technologies and meets the needs of experts in the field.

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Company: 
NIO
Date Posted: 
June 1, 2018

The next generation computing platform will be the autonomous driving electric vehicle. With data from in-car sensors, a mobile internet connected car, increased computing power, and new user interfaces that support a seamless autonomous driving experience, they will dramatically improve our lives. After home and work, the car is where we spend the most time, and we will be working on making that experience pleasurable. NIO is much more than a car company.

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GIS conducts applied research in the area of sustainable manufacturing, and also provides technical assistance in a wide variety of areas to industry. We are looking for an engineer or scientist with a strong experimental and analytical background to support existing research programs in prognostics and health management (PHM), and data analytics. Our two primary application areas are transportation systems, including DoD systems, manufacturing equipment and processes, and embedded product monitoring.

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Company: 
PARC, a Xerox Company
Date Posted: 
March 5, 2018

Senior Researcher with PhD in Electrical, Mechanical Engineering or related fields with experience in prognostics, predictive analytics, diagnostics, image/data

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