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Journal articles
Open Access
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.

Journal articles
Catalyzed interstage sulfonation CTMP process of aspen wood, Solutions!, February 2002, Vol. 85(2) (189KB)

Catalyzed interstage sulfonation CTMP process of aspen wood, Solutions!, February 2002, Vol. 85(2) (189KB)

Journal articles
Effect of stripper off-gas burning on NOx emissions, Solutions!, January 2002, Vol. 85(1) (94KB)

Effect of stripper off-gas burning on NOx emissions, Solutions!, January 2002, Vol. 85(1) (94KB)

Journal articles
The Top Ten Global Paper Companie, June 2002 SOLUTIONS! [02JUNSO49.pdf]

The top ten global paper companies, Solutions!, June 2002, Vol. 85(6) (450KB)

Journal articles
ASIAN OUTLOOK: EUROPEANS EUROPEANS LOOK EAST for the long term, June 2002 SOLUTIONS! [02JUNSO59.pdf]

Europeans look east for the long term, Solutions!, June 2002, Vol. 85(6) (159KB)

Journal articles
Open Access
Metals buildup in TCF bleach plant closure: laboratory simulation, SOLUTIONS! & TAPPI JOURNAL, May 2002 (208KB)

Metals buildup in TCF bleach plant closure: laboratory simulation, SOLUTIONS! & TAPPI JOURNAL, May 2002 (208KB)

Journal articles
Four Minute Focus: Can ERP learn from DCS?, May 2002 SOLUTIONS! [02MAYSO39.pdf]

Can ERP learn from DCS?, Solutions!, May 2002, Vol. 85(5) (61KB)

Journal articles
Optimizing PMC Operations, Solutions!, October 2005, Vol. 88(10) (160 KB)

Optimizing PMC Operations, Solutions!, October 2005, Vol. 88(10) (160 KB)

Journal articles
Grade Profile: Tissue the Global Tour, SOLUTIONS! March 2004 [04MARSO28.pdf]

Tissue: a global tour, Solutions!, March 2004, Vol. 87(3) (266KB)

Journal articles
Happy, unhappy and motivated employees, Solutions!, May 2004, Vol. 87(5)

Happy, unhappy and motivated employees, Solutions!, May 2004, Vol. 87(5) (46KB)