Your browser doesn't support javascript. This means that the content or functionality of our website will be limited or unavailable. If you need more information about Vinnova, please contact us.

Automatic fault identification of process and sensors

Reference number
Coordinator IVL SVENSKA MILJÖINSTITUTET AB - IVL Svenska Miljöinstitutet
Funding from Vinnova SEK 403 200
Project duration September 2016 - March 2017
Status Completed
Venture Strategic innovation programme for process industrial IT and automation – PiiA

Purpose and goal

The project evaluated and validated fault detection methods to automatically identify process and sensor errors in industrial processes. A proposal for a flexible software framework which enables an iterative process for the development and evaluation of fault detection methods in full-scale was developed. The project also investigated what technology is available on the market today.

Expected results and effects

This feasibility study has provided the possibility to develop this concept into an implementable system to identify process abnormalities on a short and long time scale as well as sensor faults and errors. It has also given insight in where further development should be performed and what is available today. In the future, these results can contribute to a reduction of unforeseen production stoppages that cause substantial costs in the Swedish process industry due to loss of production and expensive repairs. This will also have impact on the environment and on the local community.

Planned approach and implementation

Data from the production process was compiled and analyzed together with the industrial partners. Existing and new fault detection methods were tested and updated based on these data. In parallel, the proposal of the software framework was developed. The results from the project have been disseminated internally to the participating partners, as well as through participation from the project at PiiA Summit 2016.

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 2016-03439

Page statistics