Case Study

Haber's Strength Improvement Program: Optimizing WSR Consumption through the implementation of AI

This case study discusses how Haber supported a paper manufacturer in improving the wet-tensile strength of the produced paper while optimizing the dosing of Wet Strength Resin (WSR).


Background Information:

Wet Tensile Strength refers to the amount of stress paper can withstand, when subjected to moisture. It is critical especially in specialty-grade paper manufacturing, directly impacting the paper’s performance.

A specialty paper manufacturer was facing several issues due to inconsistent wet tensile strength during production. The customer sought the expertise of Haber and undertook detailed discussions with the team, post which the following pain points were observed:

-      Variation in Wet Tensile Strength

-      High Consumption of WSR

-      Significant Quality Rejects


Our Approach:

The main objective was to establish an effective strength improvement program that primarily helps in reducing wet tensile fluctuations.

Haber initially focused on providing the optimal dosing frequency for which an updated strength improvement program was introduced. The scientific approach adopted by the team was aimed at not only overcoming the customer's issue but also maximizing the efficiency of the process.


A real-time artificial intelligence and machine learning-based dosing device, eLIXA® controlled and maintained the addition of chemicals, ensuring the real-time adjustment of chemicals at all times.


The key process variables were measured and uploaded to the cloud in real-time on which big data analysis was carried out. Haber introduced a fully automated eLIXA®-controlled WSR program to ensure that the constituents were performing at the maximum potential.




AI's impact on WSR Consumption


The installation of eLIXA® resolved the key issues faced by the client, resulting in:

-      Decrease in the standard deviation of Wet Tensile Strength

-      Reduction in WSR consumption

-      Subsequent decline in Quality Rejects


Haber conducted in-depth technical discussions to thoroughly comprehend the existing situation. The implementation of AI/ML-optimized the strength improvement process as it helped control dosing based on real time data, resulting in a substantial reduction of 85% in wet tensile strength variation. Due to the optimization of the process, real-time changes could be incorporated resulting in improved efficiency in product delivery, along with an upgrade in paper quality. Thus, eLIXA® helped the paper manufacturer achieve quality control over their products on a consistent level, with minimum investment involved.

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