Multi-level predictive maintenance for multi-component systems

Nguyen, Kim-Anh; Van, Phuc Do; Grall, Antoine

doi:10.1016/j.ress.2015.07.017

Cited by 128 publications

(81 citation statements)

References 31 publications

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“…A graph can be used for modeling functional and structural knowledge, where the nodes represent entities and the directed but unweighted arcs are either belonging relations (i.e., a component or a sub-function to a function) or a causal relationship (i.e., the failure of the upstream entity makes the downstream entity inoperative) [6]. In reliability diagrams [21,22], three types of entities are considered corresponding to frames: the components, entities in serial structures that implement what we call simple functions and entities in parallel structures that implement redundancies.…”

Section: Behavioral Knowledge Modelingmentioning

confidence: 99%

Towards a generic prognostic function of technical multi-component systems taking into account the uncertainties of the predictions of their components

Gonzalez¹,

Desforges²,

Archimède³

2017

2017 4th International Conference on Control, Decision and Information Technologies (CoDIT)

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This article presents the first elements of a generic function that assesses the capacity of technical multi-component systems to accomplish the assigned productive tasks from production planning. This assessment is based on the prognostics of their components. It must so be able to process inaccuracies and uncertainties of these prognostics. For its implementation the aimed function combines the Dempster-Shafer theory combined and Bayesian inferences. The paper presents the multicomponent system modeling and the inferences for the different identified structures as well as a general algorithm. The final aim of the proposed generic function is to compute decision supports for cooperative maintenance and production management.

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Section: Behavioral Knowledge Modelingmentioning

confidence: 99%

Towards a generic prognostic function of technical multi-component systems taking into account the uncertainties of the predictions of their components

Gonzalez¹,

Desforges²,

Archimède³

2017

2017 4th International Conference on Control, Decision and Information Technologies (CoDIT)

View full text Add to dashboard Cite

show abstract

“…(Nguyen, Do, & Grall 2015) presents a multi-level preventive maintenance decision making algorithm. At each inspection time, conditional probabilities are calculated to update the system-level reliability modelled with Reliability Block Diagrams (RBD).…”

Section: Related Workmentioning

confidence: 99%

“…Analysed parameters include inspection, renewal, and repair times and maintenance threshold. All the analysed system-level models take into account the combinatorial failure logic of the system (Nguyen, Do, & Grall 2015, Do, Vu, Barros, & Bérenguer 2015, Vu, Do, & Barros 2016. Besides, most of the reviewed approaches integrate a degradation process to model the degradation of the asset and facilitate the posterior analytical treatment (Grall, Bérenguer, & Dieulle 2002, Haddad, Sandborn, & Pecht 2012, Do, Vu, Barros, & Bérenguer 2015, Do, Voisin, Levrat, & Iung 2015.…”

Section: Related Workmentioning

confidence: 99%

A cost-benefit approach for the evaluation of prognostics-updated maintenance strategies in complex dynamic systems

Aizpurua¹,

Catterson²,

Chiacchio

et al. 2016

Risk, Reliability and Safety: Innovating Theory and Practice

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The implementation of maintenance strategies which integrate online condition data has the potential to increase availability and reduce maintenance costs. Prognostics techniques enable the implementation of these strategies through up-to-date remaining useful life estimations. However, a cost-benefit assessment is necessary to verify the scale of potential benefits of condition-based maintenance strategies and prognostics for a given application. The majority of prognostics applications focus on the evaluation of a specific failure mode of an asset. However, industrial systems are comprised of different assets with multiple failure modes, which in turn, work in cooperation to perform a system level function. Besides, these systems include time-dependent events and conditional triggering events which cause further effects on the system. In this context not only are the system-level prognostics predictions challenging, but also the cost-benefit analysis of condition-based maintenance policies. In this work we combine asset prognostics predictions with temporal logic so as to obtain an up-to-date system level health estimation. We use asset level and system level prognostics estimations to evaluate the cost-effectiveness of alternative maintenance policies. The application of the proposed approach enables the adoption of conscious trade-off decisions between alternative maintenance strategies for complex systems. The benefits of the proposed approach are discussed with a case study from the power industry.

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“…Structural health monitoring, together with advanced signal processing methods provide current status of the pipes [2]. This information leads the identification and diagnosis of the fault in ap ipe and its location [3,4], and thus, strategies can be set for predictive maintenance [5,6,7,8]. In addition, these techniques can be controlled remotely,reducing the maintenance costs, downtimes, etc.…”

Section: Introductionmentioning

confidence: 99%

New Pipe Notch Detection and Location Method for Short Distances employing Ultrasonic Guided Waves

Muñoz¹,

Márquez²,

Lev³

et al. 2017

Acta Acustica united with Acustica

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This paper presents anovelsignal processing approach that is able to automatically identify notches in pipelines in short distances. In addition, this method locates the geometric position of the notch and determines the size. The approach for fault detection and diagnosis presented look for as olution and then validates the solution by analyzing the signal which flows in the opposite direction. Micro Fiber Composite (MFC)t ransducers are used in an austenitic stainless steel pipeline, used in solar concentrators, in order to generate Ultrasonic Guided Waves. The main results presented in this paper can be summarized as: identification of edges or welds by multi-parametric analysis and comparison with the theoretical results predicted, notch location in the pipe by comparison of the position of echoes weighted with their amplitudes, and the flows izing of them by using attenuation curves of the echoes when theyp ropagate along the pipeline. This approach leads to employo nly one transmitter and one receptor for notch detection, location and diagnosis. The main advantage for the industry is the double check of presence of anotch with respect to other systems, which reduces false alarms during the inspections.

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Multi-level predictive maintenance for multi-component systems

Cited by 128 publications

References 31 publications

Towards a generic prognostic function of technical multi-component systems taking into account the uncertainties of the predictions of their components

Towards a generic prognostic function of technical multi-component systems taking into account the uncertainties of the predictions of their components

A cost-benefit approach for the evaluation of prognostics-updated maintenance strategies in complex dynamic systems

New Pipe Notch Detection and Location Method for Short Distances employing Ultrasonic Guided Waves

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