PHM-Based Fault Identification for Electronics-Rich Systems Under Uncertainty

Xu, Lei; Xu, Ming

doi:10.1007/978-1-4471-4600-1_17

Cited by 2 publications

(4 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Conceptual architecture of PHM-based fault diagnosis for electronics-rich system. [22] references regarding sensor and parameter selection for electronic system, although there are not many examples of such devices used especially to handle the system level prognostics. According to [26], monitoring the parameters is a fundamental step in oder to accurately assess the health and to predict the remaining useful life.…”

Section: Sensor and Parameter Selectionmentioning

confidence: 99%

“…Diagnostic parameters and measures can be generated using the time series [32], Bayesian network approach [22], an advanced remote intelligent diagnostic support system (RIDES) [33], self-diagnostic Automatic Test Equipment (ATE) [7], etc.…”

Section: B Fault Diagnosticsmentioning

confidence: 99%

“…In [22], Diagnostic Bayesian network based on PHM is proposed to perform available and efficient fault diagnostics for electronic system. The numerical data is gathered based on a set of radar indicators on avionics system.…”

Section: Case Studiesmentioning

confidence: 99%

“…[16] Table 3. Standard failure mechanisms in electronic systems [22], [42] Failure Mechanisms Failure sites Relevant loads…”

Section: A Pof Description and Fmmeamentioning

confidence: 99%

See 3 more Smart Citations

Prognostics and health monitoring of electronic system: A review

Prisacaru

Gromala

Jeronimo

et al. 2017

2017 18th International Conference on Thermal, Mechanical and Multi-Physics Simulation and Experiments in Microelectronics and

View full text Add to dashboard Cite

Miniaturization of electronics, reduction of time to market and new functionalities in the current context of autonomous driving, electrification and connectivity, are bringing new reliability challenges. Prognostics and Health Management (PHM) can be used effectively to address some of the key challenges, in particular new challenges associated with the transfer of consumer electronics to automotive industry. The concept of PHM is not new, but its application to electronic systems is relatively new. It is expected that the PHM demand for electronic systems would continuously increase as autonomous driving is being realized. This paper attempts to summarize the recent studies in the system-level PHM of electronic systems. Condition monitoring (CM) techniques and prognostics methods used for the PHM of electronic systems are reviewed first. Various implementation examples are followed using different system classifications. The findings from this review is expected to offer a technical summary of accomplishments and challenges during the course of applying PHM for electronic systems, and to identify future research tasks to be performed to make the PHM a more viable tool for reliability assessment of electronic systems.

show abstract

Section: Sensor and Parameter Selectionmentioning

confidence: 99%

Section: B Fault Diagnosticsmentioning

confidence: 99%

Section: Case Studiesmentioning

confidence: 99%

“…[16] Table 3. Standard failure mechanisms in electronic systems [22], [42] Failure Mechanisms Failure sites Relevant loads…”

Section: A Pof Description and Fmmeamentioning

confidence: 99%

See 2 more Smart Citations

Prognostics and health monitoring of electronic system: A review

Prisacaru

Gromala

Jeronimo

et al. 2017

2017 18th International Conference on Thermal, Mechanical and Multi-Physics Simulation and Experiments in Microelectronics and

View full text Add to dashboard Cite

show abstract

Digital Twin Technology—A Review and Its Application Model for Prognostics and Health Management of Microelectronics

Inamdar,

van Driel,

Zhang

2024

Electronics

View full text Add to dashboard Cite

Digital Twins (DT) play a key role in Industry 4.0 applications, and the technology is in the process of being mature. Since its conceptualisation, it has been heavily contextualised and often misinterpreted as being merely a virtual model. Thus, it is crucial to define it clearly and have a deeper understanding of its architecture, workflow, and implementation scales. This paper reviews the notion of a Digital Twin represented in the literature and analyses different kinds of descriptions, including several definitions and architectural models. A new fit-for-all definition is proposed which describes the underlying technology without being context-specific and also overcomes the pitfalls of the existing generalised definitions. In addition, the existing three-dimensional and five-dimensional models of the DT architecture and their characteristic features are analysed. A new simplified two-branched model of DT is introduced, which retains a clear separation between the real and virtual spaces and outlines the latter based on the two key modelling approaches. This model is then extended for condition monitoring of electronic components and systems, and a hybrid approach to Prognostics and Health Management (PHM) is further elaborated on. The proposed framework, enabled by the two-branched Digital Twin model, combines the physics-of-degradation and data-driven approaches and empowers the next generation of reliability assessment methods. Finally, the benefits, challenges, and outlook of the proposed approach are also discussed.

show abstract

PHM-Based Fault Identification for Electronics-Rich Systems Under Uncertainty

Cited by 2 publications

References 19 publications

Prognostics and health monitoring of electronic system: A review

Prognostics and health monitoring of electronic system: A review

Digital Twin Technology—A Review and Its Application Model for Prognostics and Health Management of Microelectronics

Contact Info

Product

Resources

About