Using Semantic Technologies for More Intelligent Steel Manufacturing

Matskanis, Nikolaos; Mouton, Stéphane; Ebel, A.; Marchiori, Francesca

doi:10.5220/0005639004240428

Cited by 3 publications

(2 citation statements)

References 5 publications

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“…The streaming data from the device as well as the details of its schema or format is only available at the cloud service layer. The mapping enables querying the data with semantic technologies such as the SPARQL language using SPARQL endpoints and ensures seamless integration of raw data with the devices' data model in the ontology (Matskanis, N., et al, 2015).…”

Section: The Data Semantics Layermentioning

confidence: 99%

Bringing Dynamics to IoT Services with Cloud and Semantic Technologies - An Innovative Approach for Enhancing IoT based Services

Dupont¹,

Achour²,

Estiévenart³

et al. 2016

Proceedings of the International Conference on Internet of Things and Big Data

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In this paper, we present an innovative software architecture that brings dynamics to the world of interconnected small devices and sensors by mixing cloud services, semantics and border router technologies. Dynamic aspects can be enabled both in the way that the devices are deployed or managed as well as in the manner in which the data can be combined or interpreted to form additional services. We got inspired from the architecture of mediators and wrappers in databases and services systems and adapt them to the IoT world. We illustrate our purposes with a use case scenario that involves different actors from the energy and smart cities domains.

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Section: The Data Semantics Layermentioning

confidence: 99%

Bringing Dynamics to IoT Services with Cloud and Semantic Technologies - An Innovative Approach for Enhancing IoT based Services

Dupont¹,

Achour²,

Estiévenart³

et al. 2016

Proceedings of the International Conference on Internet of Things and Big Data

Self Cite

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“…ArcelorMittal and other companies adopt "service-oriented architecture (SOA)" to develop an integrated intelligent manufacturing system for iron and steel industry. Semantic analysis technology is used to realize seamless cooperation and information exchange in the supply chain of the company [19,20].…”

Section: Introductionmentioning

confidence: 99%

Key Intelligent Technology of Steel Strip Production through Process

Sun

Wen

Ding

et al. 2018

Metals

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Because of the complexity of procedure interface and working conditions, the further improvement of steel strip quality and production efficiency is limited. Realizing the optimization of product quality and production process in multi-process, system-level through intelligent key technology is one of the strategic directions in steel strip production. (1) Collaborative intelligent optimization and dynamic scheduling technology for steel manufacturing supply chain oriented to customized production, reducing the cost of raw material purchase and production operations and improving production efficiency and precision service ability; (2) Online monitoring, diagnosis and optimization technology of product quality. Getting through the process information flow of product, the correlation analysis of process quality parameters, the tracing of quality anomalies, the reverse optimization of process parameters and the optimization of process route will be realized; (3) Multi-process coordination optimization and quality control based on CPS architecture. The precise control technology of process quality parameters will be developed; the structure of multi-process coordination optimization system is established and optimization of key quality parameters in the through process will be realized; and (4) Microstructure and mechanical property optimization and surface quality intelligent control technology in the hot strip rolling process. Intelligent prediction of microstructure and mechanical properties, rapid dynamic design and steel grade merging technology will be formed and green process design technology of oxide scale will be developed.

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