In this chapter we present some results of the first European research project dealing with the utilisation of Big Data ideas and concepts in the Steel Industry. In the first part, it motivates the definition of a multi-scale data representation over multiple production stages. This data model is capable to synchronize high-resolution (HR) measuring data gathered along the whole flat steel production chain. In the second part, a realization of this concept as a three-tier software architecture including a web-service for a standardized data access is described and some implementation details are given. Finally, two industrial demonstration applications are presented in detail to explain the full potential of this concept and to prove that it is operationally applicable. In the first application, we realized an instant interactive data visualisation enabling the in-coil aggregation of millions of quality and process measures within seconds. In the second application, we used the simple and fast HR data access to realize a refined cause-and-effect analysis.

Applying Big Data Concepts to Improve Flat Steel Production Processes

Valentina Colla;Silvia Cateni;Antonella Vignali;
2018-01-01

Abstract

In this chapter we present some results of the first European research project dealing with the utilisation of Big Data ideas and concepts in the Steel Industry. In the first part, it motivates the definition of a multi-scale data representation over multiple production stages. This data model is capable to synchronize high-resolution (HR) measuring data gathered along the whole flat steel production chain. In the second part, a realization of this concept as a three-tier software architecture including a web-service for a standardized data access is described and some implementation details are given. Finally, two industrial demonstration applications are presented in detail to explain the full potential of this concept and to prove that it is operationally applicable. In the first application, we realized an instant interactive data visualisation enabling the in-coil aggregation of millions of quality and process measures within seconds. In the second application, we used the simple and fast HR data access to realize a refined cause-and-effect analysis.
2018
978-981-10-8475-1
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11382/521505
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