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View article: Hypotheses in Opportunistic Maintenance Modeling: A Critical and Systematic Literature Review
Hypotheses in Opportunistic Maintenance Modeling: A Critical and Systematic Literature Review Open
Because they account for realistic effects in opportunistic maintenance modeling, dependency hypotheses are extremely diverse in the literature. Despite recent reviews, a clear view of the dependency hypotheses is currently missing in the …
View article: Predictive maintenance optimization for manufacturing systems considering perfect and imperfect inspections: application to injection molding machine
Predictive maintenance optimization for manufacturing systems considering perfect and imperfect inspections: application to injection molding machine Open
International audience
View article: Data-driven drift detection and diagnosis framework for predictive maintenance of heterogeneous production processes: Application to a multiple tapping process
Data-driven drift detection and diagnosis framework for predictive maintenance of heterogeneous production processes: Application to a multiple tapping process Open
International audience
View article: Modular manufacturing and distributed control via interoperable digital twins
Modular manufacturing and distributed control via interoperable digital twins Open
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View article: Opportunistic condition-based maintenance for sea water pumps in a nuclear power plant
Opportunistic condition-based maintenance for sea water pumps in a nuclear power plant Open
International audience
View article: A study on data augmentation optimization for data-centric health prognostics of industrial systems
A study on data augmentation optimization for data-centric health prognostics of industrial systems Open
Published in IFAC-PapersOnLine 56(2):1270-1275, 2023
View article: Data-driven drift detection and diagnostic for heterogeneous production process
Data-driven drift detection and diagnostic for heterogeneous production process Open
International audience
View article: Towards interpreting deep learning models for industry 4.0 with gated mixture of experts
Towards interpreting deep learning models for industry 4.0 with gated mixture of experts Open
International audience
View article: Deep Learning Representation Pre-training for Industry 4.0
Deep Learning Representation Pre-training for Industry 4.0 Open
Deep learning (DL) approaches have multiple potential advantages that have been explored in various fields, but for prognostic and health management (PHM) applications, this is not the case due to the lack of data in particular application…
View article: Weighted-QMIX-based Optimization for Maintenance Decision-making of Multi-component Systems
Weighted-QMIX-based Optimization for Maintenance Decision-making of Multi-component Systems Open
It is well-known that maintenance decision optimization for multi-component systems faces the curse of dimensionality. Specifically, the number of decision variables needed to be optimized grows exponentially in the number of components ca…
View article: Coupling Prognostics and Decision Making (P&DM) Processes in PHM: A literature review and proposal of a Residual Performance Lifetime concept
Coupling Prognostics and Decision Making (P&DM) Processes in PHM: A literature review and proposal of a Residual Performance Lifetime concept Open
Nowadays, several industries are digitizing their factories in the objective of creating smart factory as advocated by industry 4.0 paradigm. Prognostics and Health Management (PHM) concept is one of the main pillars of this transformation…
View article: Digital continuity to improve the performance of the Industry 4.0
Digital continuity to improve the performance of the Industry 4.0 Open
This article aims at solving a problem raised by the paradigms of Industry 4.0 and certain manufacturing companies with a consequent number of production lines. The main problem is about the deployment of predictive maintenance of producti…
View article: A Short Review on the Integration of Expert Knowledge in Prognostics for PHM in Industrial Applications
A Short Review on the Integration of Expert Knowledge in Prognostics for PHM in Industrial Applications Open
International audience
View article: Reliability analysis of systems with discrete event data using association rules
Reliability analysis of systems with discrete event data using association rules Open
With the popularization of big data, an increasing number of discrete event data have been collected and recorded during system operations. These events are usually stored in the form of event logs, which contain rich information of system…
View article: Learning representations with end-to-end models for improved remaining useful life prognostic
Learning representations with end-to-end models for improved remaining useful life prognostic Open
International audience
View article: Learning representations with end-to-end models for improved remaining useful life prognostics
Learning representations with end-to-end models for improved remaining useful life prognostics Open
The remaining Useful Life (RUL) of equipment is defined as the duration between the current time and its failure. An accurate and reliable prognostic of the remaining useful life provides decision-makers with valuable information to adopt …
View article: Learning representations with end-to-end models for improved remaining\n useful life prognostics
Learning representations with end-to-end models for improved remaining\n useful life prognostics Open
The remaining Useful Life (RUL) of equipment is defined as the duration\nbetween the current time and its failure. An accurate and reliable prognostic\nof the remaining useful life provides decision-makers with valuable information\nto ado…
View article: Stochastic Filtering Approach for Condition-Based Maintenance Considering Sensor Degradation
Stochastic Filtering Approach for Condition-Based Maintenance Considering Sensor Degradation Open
International audience
View article: Editorial: August Special Issue on Advanced Maintenance Engineering, Services, and Technology (AMEST)
Editorial: August Special Issue on Advanced Maintenance Engineering, Services, and Technology (AMEST) Open
International audience
View article: A priori indicator identification to support predictive maintenance: application to machine tool
A priori indicator identification to support predictive maintenance: application to machine tool Open
Predictive maintenance requires the identification of the parameters to be monitored and sensors to be implemented on a system. In industrial companies, usually such goal is tackled by implementing sensor and after see if one can extract s…