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Journal articles
Valmet to Acquire Severn Group to Strengthen Process Performance Solutions Segment
Journal articles
Henkel Opens Upgraded Packaging Competence Center to Facilitate Future-Ready Packaging Solutions
The packaging industry is being rewritten. New sustainability regulations, rising demand for circular solutions, and the shift to digitalized manufacturing are raising the bar, requiring faster innovation and closer collaboration. Henkel Adhesive Technologies is answering that call with the inauguration of its extensively modernized Packaging Competence Center in Düsseldorf: a single hub where hands-on collaboration turns ideas into industrial reality.
Journal articles
WCP Solutions Announces Executive Leadership Promotions Across Sales, Purchasing, and IT/Operations
WCP Solutions announces several executive leadership promotions and organizational changes as part of the company’s continued growth and long-term leadership planning.
Journal articles
Mondi Strengthens Corrugated Solutions Operations in Germany Through Targeted Site Upgrades
Mondi, a global leader in sustainable packaging and paper, is strengthening its corrugated solutions operations in Germany through targeted upgrades at its plants in Greven, North Rhine-Westphalia, and Ebersdorf near Coburg, Bavaria. The measures focus on enhancing operational performance, aligning both sites with Mondi’s global safety standards and reinforcing their long-term competitiveness, while creating added value for customers and employees.
Journal articles
Magazine articles
Fiber-Based Solutions: Sustana Mill Optimization for Dry Bale Production, Paper360º March/April 2024
Journal articles
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.