Paper quality improvements and production cost reduction by using new Phys-AI technology (PAIT)

Purpose and goal:

The aim is to develop new technology with a focus on data analysis in process industrial value chains to increase the level of data analysis in the paper industry; This will be done by achieving the following sub-goals:

Develop an automated AI based decision support tool supported by physical models to predict the paper quality of the paper produced by paper manufacturing companies.

Develop a model with support from physical models to estimate the optimal replacement time for critical parts of the production machines that can affect paper quality. Expected results and effects:

Paper production companies will be able to optimize the maintenance of their paper production machines and control the paper quality produced by these machines. They will also be able to optimize the service life of critical parts of their paper production machines by determining the optimal replacement time of these machines. The project result is reflected in the tool to be developed which can be used not only by the industrial project partners but also by other paper production companies in Sweden.

Approach and implementation: The work of this project will consist of the following parts:

assembly of condition control equipment, data collection, pre-processing of data, development of physical and experimental models to support prognostic using AI, Development of AI decision support tool and optimal replacement time model, development of software used in the project and demonstrator development, data visualization and computer services and storage.