About: Towards Predictive Maintenance for Flexible Manufacturing Using FIWARE

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An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Towards Predictive Maintenance for Flexible Manufacturing Using FIWARE
Creator	Bai, Yuewei Xu, Lai De Vrieze, Paul Sang, Go
Source	PMC
abstract	Industry 4.0 has shifted the manufacturing related processes from conventional processes within one organization to collaborative processes across different organizations. For example, product design processes, manufacturing processes, and maintenance processes across different factories and enterprises. This complex and competitive collaboration requires the underlying system architecture and platform to be flexible and extensible to support the demands of dynamic collaborations as well as advanced functionalities such as big data analytics. Both operation and condition of the production equipment are critical to the whole manufacturing process. Failures of any machine tools can easily have impact on the subsequent value-added processes of the collaboration. Predictive maintenance provides a detailed examination of the detection, location and diagnosis of faults in related machineries using various analyses. In this context, this paper explores how the FIWARE framework supports predictive maintenance. Specifically, it looks at applying a data driven approach to the Long Short-Term Memory Network (LSTM) model for machine condition and remaining useful life to support predictive maintenance using FIWARE framework in a modular fashion.
has issue date	2020-04-29(xsd:dateTime)
bibo:doi	10.1007/978-3-030-49165-9_2
has license	no-cc
sha1sum (hex)	064f821839fd63230c947ef179b994556c67f70a
schema:url	https://doi.org/10.1007/978-3-030-49165-9_2
resource representing a document's title	Towards Predictive Maintenance for Flexible Manufacturing Using FIWARE
has PubMed Central identifier	PMC7225515
schema:publication	Advanced Information Systems Engineering Workshops
resource representing a document's body	covid:064f821839fd63230c947ef179b994556c67f70a#body_text
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