Prognostics and health management: Utilizing the life cycle knowledge to reduce life cycle cost

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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PHM Survey : Implementation of Diagnostic Methods for Monitoring Industrial Systems

International Journal of Prognostics and Health Management ◽

10.36001/ijphm.2019.v10i2.2733 ◽

2019 ◽

Vol 10 (2) ◽

Author(s):

Abdenour Soualhi ◽

Bilal Elyousfi ◽

Yasmine Hawwari ◽

Kamal Medjaher ◽

Guy Clerc ◽

...

Keyword(s):

Life Cycle ◽

Health Management ◽

Fault Isolation ◽

Diagnostic Methods ◽

Condition Based Maintenance ◽

Prognostics And Health Management ◽

Isolation And Identification ◽

Industrial Systems ◽

Industrial Sectors ◽

Processing Step

The modernization of industrial sectors involves the use of complex industrial systems and therefore requires condition based maintenance. This one aims at increasing the operational availability and reducing the life-cycle while increasing the reliability and life expectancy of industrial systems. This maintenance also called predictive maintenance is a part of an emerging philosophy called PHM ‘Prognostics and Health Management’. In this paper, the PHM will be emphasized on the existing diagnostic methods used for fault isolation and identification. This depicts an important part of the PHM as it exploits the data given by the signal-processing step and its output is treated by the prognostic part. The diagnostic is mainly classified in three categories that will be highlighted in this paper.

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Prognostics and Health Management System for Electric Vehicles with a Hierarchy Fusion Framework: Concepts, Architectures, and Methods

Advances in Civil Engineering ◽

10.1155/2021/6685900 ◽

2021 ◽

Vol 2021 ◽

pp. 1-11

Author(s):

Cheng Wang ◽

Tongtong Ji ◽

Feng Mao ◽

Zhenpo Wang ◽

Zhiheng Li

Keyword(s):

Life Cycle ◽

Fault Diagnosis ◽

Real Time ◽

Electric Vehicle ◽

Electric Vehicles ◽

Health Management ◽

Research Progress ◽

Prognostics And Health Management ◽

Time Data ◽

Real Time Data

The prognostics and health management (PHM) of electric vehicles is an important guarantee for their safety and long-term development. At present, there are few studies researching about life cycle PHM system of electric vehicles. In this paper, we first summarize the research progress and key methods of PHM. Then, we propose a three-level PHM system with a hierarchy fusion architecture for electric vehicles based on the structure, data source of them. In the PHM system, we introduce a database consisting of the factory data, real-time data, and detection data. The electric vehicle's factory parameters are used for determining the life curve of the electric vehicle and its components, the real-time data are used for predicting the remaining useful lifetime (RUL) of the electric vehicle and its components, and the detection data are used for fault diagnosis. This health management database is established to help make condition-based maintenance decisions for electric vehicles. In this way, a complete electric vehicle PHM system is formed, which can realize the whole-life-cycle life prediction and fault diagnosis of electric vehicles.

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Life cycle cost impact of using prognostic health management (PHM) for helicopter avionics

Microelectronics Reliability ◽

10.1016/j.microrel.2007.02.014 ◽

2007 ◽

Vol 47 (12) ◽

pp. 1857-1864 ◽

Cited By ~ 65

Author(s):

E. Scanff ◽

K.L. Feldman ◽

S. Ghelam ◽

P. Sandborn ◽

M. Glade ◽

...

Keyword(s):

Life Cycle ◽

Life Cycle Cost ◽

Health Management ◽

Cost Impact ◽

Prognostic Health Management

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Testability Design of the PHM System for Aero-Engines

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.544.94 ◽

2012 ◽

Vol 544 ◽

pp. 94-98

Author(s):

Zhen Hua Wen ◽

Yuan Peng Liu ◽

Xin Yin

Keyword(s):

Life Cycle ◽

Health Management ◽

Management Strategies ◽

Prognostics And Health Management ◽

Technical Approach ◽

Test Program ◽

Fusion Methods ◽

Aero Engines ◽

Total Life ◽

Monitoring Information

PHM (Prognostics and Health Management) for Aero-engines is an effective technical approach to balance the economy and safety of the flight in the total life cycle. In this paper, we mainly analyze the popular issues in the process of designing PHM system for aero-engines including the testability design concept, the scheme of condition monitoring and the utilization extent of condition information. Then presents some useful solutions and advices for the testability design respectively; and analyzes the influence of testability on health management strategies and the main source of uncertainty; then propose a roadmap for making test program based on the PHM requirements and evaluating test program, for improve the utilizing degree of monitoring information, we lastly presented common data fusion methods and some typical examples is illustrated.

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Supporting Business Cases for PHM

Diagnostics and Prognostics of Engineering Systems ◽

10.4018/978-1-4666-2095-7.ch014 ◽

2013 ◽

pp. 268-290

Author(s):

Peter Sandborn ◽

Taoufik Jazouli ◽

Gilbert Haddad

Keyword(s):

Return On Investment ◽

Life Cycle Cost ◽

Health Management ◽

New Technology ◽

Wind Farms ◽

Cost Models ◽

Prognostics And Health Management ◽

Critical Systems ◽

Management Processes ◽

Business Cases

The development and demonstration of innovative prognostics and health management (PHM) technology is necessary but not sufficient for widespread adoption of PHM concepts within systems. Without the ability to create viable business cases for the insertion of the new technology into systems and associated management processes, PHM will remain a novelty that is not widely disseminated. This chapter addresses two key capabilities necessary for supporting business cases for the inclusion and optimization of PHM within systems. First, the chapter describes the construction of life-cycle cost models that enable return on investment estimations for the inclusion of PHM within systems and the valuation of maintenance options. Second, the chapter addresses the support of availability-centric requirements (e.g., availability contracts) for critical systems that incorporate PHM, and the resulting value that can be realized. Examples associated with avionics, wind turbines, and wind farms are provided.

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Challenges in Reliability Assessment for Electronics

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.118-120.419 ◽

2010 ◽

Vol 118-120 ◽

pp. 419-423 ◽

Cited By ~ 1

Author(s):

Qing Chuan He ◽

Wen Hua Chen ◽

Jun Pan ◽

Shi Jiao Wang

Keyword(s):

Life Cycle ◽

Failure Mechanism ◽

Health Management ◽

Reliability Assessment ◽

Model Identification ◽

Catastrophic Failure ◽

Prognostics And Health Management ◽

Enabling Technology ◽

Actual Application ◽

Reliability Of Electronics

There has been a growing interest in assessing the ongoing reliability of electronics and systems in order to predict failures and provide warning to avoid catastrophic failure. Methods based on prognostics and health management shows an enabling technology to assess the reliability of electronics and systems under its actual application conditions. However, many challenges in implementation of methods based on PHM still remain including: environmental and usage profiles for life-cycle loads, identification of failure mechanism, identification of failure PoF model, identification of parameters to be monitored, approaches to anomaly detection. These challenges were presented and discussed, and would be carried out by developing methodologies and techniques.

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