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A bright idea for technology, Solutions!, May 2004, Vol. 87(5) (48KB)

A bright idea for technology, Solutions!, May 2004, Vol. 87(5) (48KB)

Predictive advisory solutions for chemistry management, control, and optimization, TAPPI Journal March 2025

ABSTRACT: Process runnability and end-product quality in paper and board making are often connected to chemistry. Typically, monitoring of the chemistry status is based on a few laboratory measurements and a limited number of online specific chemistry-related measurements. Therefore, mill personnel do not have real-time transparency of the chemistry related phenomena, which can cause production instability, including deposition, higher chemical consumption, quality issues in the end-product and runnability problems. Machine learning techniques have been used to establish soft sensor models and to detect abnormalities. Furthermore, these soft sensors prove to be most useful when combined with expert-driven interpretation. This study is aimed at utilizing a hybrid solution comprising chemistry and physics models and machine learning models for stabilizing chemistry-related processes in paper and board production. The principal idea is to combine chemistry/physics models and machine learning models in a fashion close to white box modeling. A cornerstone in the approach is to formulate explanations of the findings from the models; that is, to explain in plain text what the findings mean and how operational changes can mitigate the identified risks. The approach has been demonstrated for several different applications, including deposit control in the wet end, both raw water treatment and usage, and wastewater treatment. This approach provides mill personnel with knowledge of identified phenomena and recommendations on how to stabilize chemistry-related processes. Instead of using close to black box machine learning models, a hybrid solution including chemistry/physics models can enhance the performance of artificial intelligence (AI) deployed systems. A successful way of gaining the trust from mill personnel is by creating a plain text explanation of the findings from the hybrid models. The correlation between the likelihood of a phenomena and disturbance and the explanations are derived and validated by application and chemistry and physics experts.

Pulp and Paper Machine Healthcare, Part 1: Digitalization Solutions for Condition Monitoring, Paper360º March/April 2025

Energy Reducing AI Solutions Commissioned by Tissue SME(s), 2021 TAPPICon Live (21TAPL)

Improving Mill Productivity with Advanced Wear Protection Solutions, 2004 Engineering, Pulping, and PCE&I Conference

Improving Mill Productivity with Advanced Wear Protection Solutions, 2004 Engineering, Pulping, and PCE&I Conference

Alternative Solutions to Landfilling Paper Mill Packaging Waste, 1992 Finishing and Converting Conference Proceedings

Alternative Solutions to Landfilling Paper Mill Packaging Waste, 1992 Finishing and Converting Conference Proceedings

Practical Solutions for Trim and Waste Handling Systems, 1998 Finishing and Converting Conference Proceedings

Practical Solutions for Trim and Waste Handling Systems, 1998 Finishing and Converting Conference Proceedings

Challenges and Solutions to Film Application Issues, 1996 Metered Size Press Forum Proceedings

Challenges and Solutions to Film Application Issues, 1996 Metered Size Press Forum Proceedings

Superheater Problems, Their Causes & Solutions, 2004 International Chemical Recovery Conference

Superheater Problems, Their Causes & Solutions, 2004 International Chemical Recovery Conference

Surface Sizing with Starch Solutions at High Solids Contents, 2002 Metered Size Press Forum

Surface Sizing with Starch Solutions at High Solids Contents, 2002 Metered Size Press Forum