A maintenance planning and business case development model for the application of prognostics and health management (PHM) to electronic systems

Reliability is an important issue to consider for mechanical systems. The state of art is regular checkup and maintenance to ensure normal operations. This is not good enough for safety-critical systems like gearboxes in vehicles and helicopters because the risk of system failure still exists, let alone the manpower and monetary cost required. Prognostics and health management (PHM) was first raised by the U.S. armed force, which should ideally be able to predict faults and schedule maintenance only when necessary by monitoring the system condition. In this paper, inspired by the idea of Built-In Self Test (BIST) in electronic systems, we propose a novel framework to fulfill the task of prognostics and health management with a set of smart sensors, consisting of embedded sensing elements, wireless communication modules and micro-controllers. Both the significance and challenges of the framework are discussed.

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A Survey of Sensor Technologies for Prognostics and Health Management of Electronic Systems

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.602-605.2229 ◽

2014 ◽

Vol 602-605 ◽

pp. 2229-2232 ◽

Cited By ~ 1

Author(s):

Wen Xue Yang ◽

Zhe Chen ◽

Feng Yang

Keyword(s):

Life Cycle ◽

Early Warning ◽

Health Management ◽

Life Cycle Costs ◽

Electronic Systems ◽

Sensor Systems ◽

Prognostics And Health Management ◽

Electronic Products ◽

System Failures

Recently, the field of Prognostics and Health Management (PHM) for electronic products and systems has received increasing attention due to the potentialities to provide early warning of system failures, reduce life cycle costs, and forecast maintenance as needed. This paper introduces the sensors and their sensor technologies. The required attributes of sensors for the development for PHM of electronics are discussed. Finally, their trends in sensor systems are presented.

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Editorial - Impact of Prognostics and Health Management in Systems Reliability and Maintenance Planning

Reliability Engineering & System Safety ◽

10.1016/j.ress.2019.01.016 ◽

2019 ◽

Vol 184 ◽

pp. 1

Author(s):

Joo-Ho Choi ◽

Ming J. Zuo

Keyword(s):

Health Management ◽

Maintenance Planning ◽

Prognostics And Health Management

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Prognostics and health management based refurbishment for life extension of electronic systems

2014 IEEE International Conference on Information and Automation (ICIA) ◽

10.1109/icinfa.2014.6932842 ◽

2014 ◽

Cited By ~ 1

Author(s):

Prabhakar V. Varde ◽

Jing Tian ◽

Michael G. Pecht

Keyword(s):

Health Management ◽

Life Extension ◽

Electronic Systems ◽

Prognostics And Health Management

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Power Supply Prognostics and Health Management of High Reliability Electronic Systems in Rugged Environment

Key Engineering Materials ◽

10.4028/www.scientific.net/kem.474-476.1195 ◽

2011 ◽

Vol 474-476 ◽

pp. 1195-1200 ◽

Cited By ~ 5

Author(s):

Yong Guan ◽

Sheng Zhen Jin ◽

Li Feng Wu ◽

Wei Pan ◽

Yong Mei Liu ◽

...

Keyword(s):

Power System ◽

Embedded System ◽

Power Supply ◽

Health Management ◽

High Reliability ◽

Electronic System ◽

Fixed Time ◽

Electronic Systems ◽

Prognostics And Health Management ◽

Healing Model

The high reliable embedded system in rugged environment has huge potential application value. There are 34% faults in electronic system by the cause of the fault of power system. So the prognostics mechanism and the algorithm of power health has been a core support technology in applications. the fault and the deterioration and healing model of the power system in rugged environment is constructed by analysis of FFP, DFP and healing(alleviation)for improving the reliability, the usability and the maintainability. And many questions such as fixed-time maintenance and back-down maintenance depending on conventional statistical method are solved fundamentally. Finally, the prognostics and health management methods of power health in domestic and foreign presently are contrasted and analyzed.

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