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Deep Process Learning

Reference number
Coordinator RISE Research Institutes of Sweden AB - SICS Swedish ICT Västerås AB
Funding from Vinnova SEK 2 908 000
Project duration May 2017 - April 2019
Status Completed

Purpose and goal

This project aims to show how deep learning can be used to introduce a big leap for automation in process industry. The proposed approach will take advantage of the data already gathered in the process control system and use that to suggest the needed action to improve desired KPI:s, contributing to optimize quality of the final product.

Expected results and effects

The results of the project can in the first step be used as a decision support for operators in the pulp and paper industry. The intention and goal to completely automate the control of the process has not been achieved within the project. An important result is increased knowledge about present possibilities and limitations of deep learning and how the technique can be applied in process industry.

Planned approach and implementation

The project has been conducted in close cooperation between the parties, with a delegated responsibility for the different work packages: Data collection, Development of deep learning algorithm for process industry, User experience and visualization, and Dissemination. An important part of the project was to collect large amounts of data, especially about deviations, and to secure quality of data and to establish ways to transfer data in a robust and secure way.

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 17 June 2019

Reference number 2017-01970

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