Post-prognostics decision in cyber-physical systems

Meraghni, Safa; Terrissa, Labib Sadek; Ayad, Soheyb; Zerhouni, Noureddine; Varnier, Christophe

doi:10.1109/aset.2018.8379859

Cited by 12 publications

(7 citation statements)

References 25 publications

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“…Particularly for PHM (Pump Health Monitoring) solutions, [12] indicated critical points to be considered like, data processing and storage capability [13], asset overview, domain knowledge, and robustness for estimating the 'Remaining Useful Life (RUL)' [14]. This work also proposes computational architectures for the effective deployment of condition monitoring solutions.…”

Section: Literature Review and State Of Artmentioning

confidence: 99%

Predictive Maintenance for Axial Piston Pumps: A Novel Method for Real-Time Health Monitoring and Remaining Useful Life Estimation

Samanta,

Kulkarni,

Hande

2024

14th International Fluid Power Conference

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In this paper, a novel method to estimate and predict the condition of an open circuit piston pump is presented. We introduce the concept of the 'Pump health index' which can assess the health of the pump in real time and use it to estimate the remaining useful life of the pump. The solution is agnostic to pump size, make, and application duty cycle. The solution has been tested with different levels of degradation that were simulated on the physical pump. The algorithms were implemented on multiple embedded platforms to illustrate the agnostic nature of the developed technology.

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Section: Literature Review and State Of Artmentioning

confidence: 99%

Predictive Maintenance for Axial Piston Pumps: A Novel Method for Real-Time Health Monitoring and Remaining Useful Life Estimation

Samanta,

Kulkarni,

Hande

2024

14th International Fluid Power Conference

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“…Cloud level: cloud is a metaphor for describing the web as a space where computing has been predominant installed and exists as a service; data, operating systems, applications, storage and processing power exist on the web ready to be shared [12]. So, our contribution consists in proposing an architecture that accurately describes an intelligent monitoring method for industrial systems.…”

Section: The Different Architecturesmentioning

confidence: 99%

An Approach CPS for the Smart Monitoring of Industrial Systems

Jlassi¹,

Béler²,

Khlaief³

et al. 2022

Artificial Intelligence and Machine Learning

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Process monitoring is an important element for the long-term reliable functioning of any automated system. In fact, monitoring system is constituted of sensors installed in the physical system, in order to analyse, observe and control production systems in real time. In network, these sensors may interact with one other and with an external system via wireless communication. With recent advances in electronics, tiny sensors have appeared. Their low cost and energy consumption allow them to perform three main functions: capture data, provide information and communicate it via sensor network. In this paper, we had interested to the Cyber-Physical System (CPS) and Prognostics Health Management (PHM) domain; The CPS is one of the most important advanced technologies, it connects the physical world with the cyber using a communication layout. In other side, PHM has become a key technology for detectingfuture failures by predicting the future behaviour of the system.

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“…The intervention dates are then suggested by the perspective maintenance support system, thus allowing the operators to make the final decision. In (Meraghni, Terrissa, Ayad, Zerhouni, & Varnier, 2018), Meraghni et al developed a PHM framework based on Internet-of-Things and cloud computing and cyber physical systems to help maintenance decision-making in big industries. The framework includes maintenance resource allocations, maintenance planning, and traveling cost oriented for maintenance services based on the estimated RUL of the different machines.…”

Section: Multiple Machines Maintenance Planningmentioning

confidence: 99%

Review of Post-Prognostics Decision-Making in Prognostics and Health Management

Bougacha

Varnier

Zerhouni

2021

IJPHM

Self Cite

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Mainly, the prognostics and health management (PHM) process is based on three processes: the data acquisition and health assessment process in which sensors signals are acquired and processed, the diagnostic and prognostic process in which the source of failure is detected and the remaining useful life (RUL) is predicted and finally the decision- making process that refers to the term management in prognostics and health management. This paper reviews in the literature about the different aspects of decision-making in the context of PHM. The selected papers are subject to con- tent assessment and grouped according to the decision type. Additionally, this paper presents a synthesis of the previous works that helps identify new trends and deficiencies in the decision-making process. The synthesis can guide efforts for future work.

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Post-prognostics decision in cyber-physical systems

Cited by 12 publications

References 25 publications

Predictive Maintenance for Axial Piston Pumps: A Novel Method for Real-Time Health Monitoring and Remaining Useful Life Estimation

Predictive Maintenance for Axial Piston Pumps: A Novel Method for Real-Time Health Monitoring and Remaining Useful Life Estimation

An Approach CPS for the Smart Monitoring of Industrial Systems

Review of Post-Prognostics Decision-Making in Prognostics and Health Management

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