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Enabling super quality electric steel through advanced use of data analytics in real time

Reference number
Coordinator RISE SICS Västerås AB - SICS Swedish ICT Västerås AB
Funding from Vinnova SEK 500 000
Project duration November 2017 - June 2018
Status Completed
Venture The strategic innovation programme for Production2030

Purpose and goal

The Electric Vehicle Revolution brings new and increased need for quality electric steel for the electrification of the fleet. In this idea project we have investigated how to gather data from and knowledge of the special steel manufacturing process and utilize this for advanced analytics. Information comes from its own process and partly from suppliers. The aim of the idea project was to describe how to utilize advanced data analytics for the steel industry and other industries that have flexible production with a varied product mix.

Expected results and effects

The project has focused on data from the steel supplier and on the final product from Cogent Surahammar and has performed data analysis to predict properties of the final product. By examining which methods of machine learning are appropriate we have been able to identify data source requirements, type of expertise from the process needed and the infrastructure needed for a functioning environment. The project has also examined the prerequisites for a major research project aimed at increasing the possibilities for flexible production based on advanced data analysis.

Planned approach and implementation

The Supersteel project has been led by RISE SICS Västerås and involved expertise in steel production from Cogent Surahammar. The focus of the project has been data collection from various sources within the Cogent Group and analysis of these data. An important part of the project has been to identify shortcomings and risks with this type of technology. The end result is an analysis of the types of models and tools that are appropriate for this type of application.

External links

The project description has been provided by the project members themselves and the text has not been looked at by our editors.

Last updated 25 November 2019

Reference number 2017-04790

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