NewTech4Steel

Enhancing steel production with break-through technologies inspired by Big Data concepts

Rolling processes are the fastest processes in steel production and have a significant influence on many quality features of the final product. Although many of these are controlled online, the overall product quality is not in all cases sufficient. The reason therefore is missing information about relationships between quality features and dynamic process conditions of the rolling mill itself. Solutions will be developed based on the online evaluation of all available high resolution sensor data to improve this situation. New IT technologies to handle huge amounts of data in real-time and machine learning methods to extract automatically relevant relationships from data will allow a much better supervision and control of the involved process steps.

NewTech4Steel

Enhancing steel production with break-through technologies inspired by Big Data concepts

Rolling processes are the fastest processes in steel production and have a significant influence on many quality features of the final product. Although many of these are controlled online, the overall product quality is not in all cases sufficient. The reason therefore is missing information about relationships between quality features and dynamic process conditions of the rolling mill itself. Solutions will be developed based on the online evaluation of all available high resolution sensor data to improve this situation. New IT technologies to handle huge amounts of data in real-time and machine learning methods to extract automatically relevant relationships from data will allow a much better supervision and control of the involved process steps.

Objectives

From an industrial point of view, the general objective is to establish new methods for a better exploitation of available data and information sources by means of innovative methods and tools for data handling and processing with aim to improve production process supervision and product quality.

From the technical perspective the objectives of the project are:

  • Improve the data storage systems at the industrial sites by enhancing the existing solutions and by integrating innovative tools from Big Data technologies.
  • Establish a new methodology for data transmission to achieve highest possible data throughput rates, as this becomes necessary for the goal of online or near-online processing.
  • Develop and apply newest technologies of Data Analytics and Machine Learning for analysis and modelling, because the existing data acquisition systems supply masses of data of various structures and contents, which have to be analysed and processed together in order to give more insights of the process situation and ways to improve it.

Results

The NewTech4Steel project aims at producing the following output:

  • Selection, assessing and implementation of suitable tools/platforms for data handling with regard to the examined use cases
  • Selecting, implementing and testing promising methodologies of Data Analytics, for analysis and modelling for utilising as many as possible from the available data streams.
  • Selection of auxiliary components and preparation/development for implementation
  • Human Machine Interface (HMIs) design. The user acceptance of the new tools plays a major in the adoption of the new technologies. The design and handling of the tool UI is one of the main outputs of the project.
  • Installation of an automatic tool deployemnt enviroment for each of the use cases.
  • Test and validate the performance of the installed solutions for each use case.
  • Document the environment installation and tool deployment creating "workbooks" for the application of Big Data technologies, Data Analytics methods and other applied approaches and conclusions to their transferability.