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IEEE Prognostics and Health Management StandardPublished by IEEE Reliability Society

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A working group, chaired by Prof. Michael Pecht, has led the development of new IEEE standard framework for prognostics and health management (PHM) of electronic systems. 

CALCE faculty members, Prof. Peter Sandborn and Dr. Michael Azarian, took part in the development along with current and former students Jordan Jameson, PhD candidate, Dr. Sony Mathew, Dr. Arvind Vasan, and Ranjit Kumar. Lou Gullo of Raytheon served as the IEEE Reliability Society sponsor for the development of the standard. Other participants in the working group included personnel Amazon, Baker Hughes, Dell, General Electric, Microsoft, Raytheon, Rolls Royce, and many more. 

IEEE 1856-2017 provides information for the implementation of PHM for electronic systems, a framework for classifying PHM capability, and a structure for planning the development of PHM for an electronic system or product. The standard will help manufacturers and end users apply appropriate PHM techniques to the associated life-cycle operations for the system of interest. 

PHM helps mitigate unforeseen operational problems that cause performance deficiencies, degradation, and adverse equipment performance. Current PHM methods and tools are useful, but applications to real-world situations have become obscured by insufficient insight into these tools, an absence of uniform application of these tools, and inadequate consistency in their demonstrated results. 

IEEE 1856-2017 will help practitioners make business cases for PHM implementation and select the correct strategies and performance metrics for evaluating PHM results. The overall goal is to provide an in-depth overview of PHM and offer significant details to help the practitioner make appropriate decisions by offering a selection of algorithms, approaches, condition-monitoring equipment, methodologies, procedures, and strategies for electronic systems PHM. By defining the normative framework for classifying PHM capability, this standard will aid practitioners in selecting PHM strategies and approaches to meet their needs. 

CALCE's Prognostics and Health Management Group researches and develops PHM applications for electronic products and systems. CALCE has worked on many PHM projects, including prognostic methods for battery management systems for NSF, remaining life assessment for space shuttle rockets for NASA, autonomous prognostics and health monitoring systems for weapons platforms for the US Army, diagnostic systems for automobile driving safety improvement for the Ministry of Trade, Industry, and Energy, South Korea, and machine learning-powered diagnostics and prognostics for semiconductor manufacturing equipment for Samsung Electronics. CALCE is pioneering the use of a fusion approach-combining physics-of-failure and data-driven methods. 

For more information, visit www.calce.umd.edu or email Prof. Michael Pecht (pecht@calce.umd.edu) or Dr. Michael Osterman (osterman@calce.umd.edu).

Published January 26, 2018