Test point selection based on functional simulation and FMMEA for an electronic system on PHM

Wang, Xufei; Li, Zhongqun; Zhang, Shunong; Liu, Jiaming; Shao, Cong

doi:10.1109/icphm.2013.6621444

Cited by 4 publications

(6 citation statements)

References 3 publications

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“…These parameters are the basis for accurate the PoF models used on prognostic of life expectancy of the system, module, or component. The second FMMEA step is the risk analysis that provides the criteria for Risk Priority Number (RPN), which including estimating the de-tection capability, severity and likelihood of the failure (Pei et al 2012, Wang et al 2013.…”

Section: Fmmea Approachmentioning

confidence: 99%

“…The revelead weakness of FEMMEA is the failure mechanism identification that is hard to implement. This difficulty comes from the non-standardized analysis processes, making FMMEA inefficiency, poor reliability and reuse (Wang et al 2013, Liu et al 2014. Recently the authors Liu et al (2014) developed a new FMMEA method automation based with fuzzy cognitive map theory.…”

Section: Fmmea Approachmentioning

confidence: 99%

“…The most common sources of uncertainty are the sensors errors, uncertainty measurement on operating unplanned loading regimes, models assumptions and inconsistencies, loss of information due to the reduced amount of data and prognostics under no circumstances corresponding to the data used for tuning, data acquisition system as the amount of available data increases etc. (Pecht 2010, Sun et al 2012, Lumme & Pylvänen 2012, Wang et al 2013. For these reasons, decisions regarding the state of the system (maintenance, repair and replacement activities) should take into account the uncertainties described.…”

Section: Quantification and Uncertainty Managementmentioning

confidence: 99%

“…However the nonlinearity remains complex and difficult to modelling (Si et al 2012, Zhang & Pisu 2014. Fusion approaches are the combination of PoF and Data-driven models, but very few studies have been reported (Xing et al 2012, Wang et al 2013, Chen & Pecht 2012.…”

Section: Future Workmentioning

confidence: 99%

“…The hybrid method development should be increased with the inclusion of the uncertainty quantification, confidence levels quantification, methods, tools, metrics and standardization (Sun et al 2012, Bird & Shao 2014. The influence of uncertainty sources on the accuracy and confidence levels in the PHM metrics reliability prognostics are still a key area development (Pecht 2010, Sun et al 2012, Lumme & Pylvänen 2012, Wang et al 2013.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Prognostics Health Management: Perspectives in engineering systems reliability prognostics

Esteves¹,

Nunes²

2015

Safety and Reliability of Complex Engineered Systems

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The Prognostic Health Management (PHM) has been asserting itself as the most promising methodology to enhance the effective reliability and availability of a product or system during its life-cycle conditions by detecting current and approaching failures, thus, providing mitigation of the system risks with reduced logistics and support costs. However, PHM is at an early stage of development, it also expresses some concerns about possible shortcomings of its methods, tools, metrics and standardization. These factors have been severely restricting the applicability of PHM and its adoption by the industry.This paper presents a comprehensive literature review about the PHM main general weaknesses. Exploring the research opportunities present in some recent publications, are discussed and outlined the general guidelines for finding the answer to these issues.

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Section: Fmmea Approachmentioning

confidence: 99%

Section: Fmmea Approachmentioning

confidence: 99%

Section: Quantification and Uncertainty Managementmentioning

confidence: 99%

Section: Future Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Prognostics Health Management: Perspectives in engineering systems reliability prognostics

Esteves¹,

Nunes²

2015

Safety and Reliability of Complex Engineered Systems

View full text Add to dashboard Cite

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A Simulation Research on Gradual Faults in Analog Circuits for PHM

Xie

Zhang

Liu

2014

Lecture Notes in Mechanical Engineering

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Toward a new definition of FMECA approach

Catelani

Ciani

Cristaldi

et al. 2015

2015 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) Proceedings

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It is well known that Failure Mode Effect Analysis methodology (FMEA) allows to reduce, and if it possible eliminate, the effects of potential failure modes starting from the first stage of the product design. By means of the Criticality Analysis (CA), implemented in FMECA, it is possible to select by means of risk indexes the most potential critical failures. In this paper the authors present the pros and cons of FMECA along the product development cycle based on the existing standards, recommending the most appropriate standard for each development stage. Additionally, the concept of fault mechanisms is introduced through a new hybrid approach to avoid drawbacks of current FMECA. In this way, it will be possible to observe the evolution of the Remaining Useful Life (RUL) of the system and define the maintenance strategy using the information provided by the suitable monitoring activity

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Test point selection based on functional simulation and FMMEA for an electronic system on PHM

Cited by 4 publications

References 3 publications

Prognostics Health Management: Perspectives in engineering systems reliability prognostics

Prognostics Health Management: Perspectives in engineering systems reliability prognostics

A Simulation Research on Gradual Faults in Analog Circuits for PHM

Toward a new definition of FMECA approach

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