Development of a flexible data management system, to implement predictive maintenance in the Industry 4.0 context

In recent years, the way that maintenance is carried out has evolved due to the incorporation of digital tools and Industry 4.0 concepts. By connecting to and communicating with their production system, companies can now gather information about the current and future health of the equipment, enabli...

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Published inInternational journal of production research Vol. 62; no. 6; pp. 2255 - 2271
Main Authors Ciancio, Vincent, Homri, Lazhar, Dantan, Jean-Yves, Siadat, Ali
Format Journal Article
LanguageEnglish
Published London Taylor & Francis 18.03.2024
Taylor & Francis LLC
Subjects
Automobile industry
Communication
Condition monitoring
Control equipment
Data management
Engineering Sciences
Industry 4.0
intelligent maintenance systems
Internet of Things
Predictive maintenance
Repair & maintenance
Condition monitoring
Industry 4.0
intelligent maintenance systems
Internet of Things
predictive maintenance
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Abstract In recent years, the way that maintenance is carried out has evolved due to the incorporation of digital tools and Industry 4.0 concepts. By connecting to and communicating with their production system, companies can now gather information about the current and future health of the equipment, enabling more efficient control through a process called predictive maintenance (PdM). The goal of PdM is to reduce unplanned downtimes and proactively address maintenance needs before failures occur. However, it can be challenging for industrial practitioners to implement an intelligent maintenance system that effectively manages data. This paper presents a methodology for developing and implementing a PdM system in the automotive industry, using open standards and scalable data management capabilities. The platform is validated through the presentation of two industry use cases.
AbstractList In recent years, the way that maintenance is carried out has evolved due to the incorporation of digital tools and Industry 4.0 concepts. By connecting to and communicating with their production system, companies can now gather information about the current and future health of the equipment, enabling more efficient control through a process called predictive maintenance (PdM). The goal of PdM is to reduce unplanned downtimes and proactively address maintenance needs before failures occur. However, it can be challenging for industrial practitioners to implement an intelligent maintenance system that effectively manages data. This paper presents a methodology for developing and implementing a PdM system in the automotive industry, using open standards and scalable data management capabilities. The platform is validated through the presentation of two industry use cases.
Author Dantan, Jean-Yves
Homri, Lazhar
Ciancio, Vincent
Siadat, Ali
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Issue 6
Keywords Condition monitoring
Industry 4.0
intelligent maintenance systems
Internet of Things
predictive maintenance
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Snippet In recent years, the way that maintenance is carried out has evolved due to the incorporation of digital tools and Industry 4.0 concepts. By connecting to and...
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SubjectTerms Automobile industry
Communication
Condition monitoring
Control equipment
Data management
Engineering Sciences
Industry 4.0
intelligent maintenance systems
Internet of Things
Predictive maintenance
Repair & maintenance
Title Development of a flexible data management system, to implement predictive maintenance in the Industry 4.0 context
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