Case Study

Can eLIXA® optimize paper strengthening while driving down the production cost?

This case study discusses how HABER supported a paper manufacturer in improving their paper’s internal as well as surface strength, as well as in optimizing the concentrations of Dry Strength Aid (DSA).


The internal strength defines the ability of paper to withstand the forces that are applied perpendicular to the plane of its surface, whereas the surface strength is the ability of the paper’s surface to bear the forces involved in inking during the printing process. Paper strength measured via burst or tensile strength is one of the critical end-product qualities which varies depending on the raw material used. Chemistries of strength aid help in increasing the strength and also help in improving retention and drainage and machine efficiency.

One of the leading paper manufacturers in India approached HABER and had a detailed technical discussion to understand why the paper strength hadn’t reached optimal levels. This was followed by a thorough system study and post which we were able to provide a suitable product.

The following KPIs were considered to formulate a solution:

-         Improving, as well as sustaining the strength of paper

-         Improving the surface strength

-         Reducing the fluff

-         Reducing the consumption of softwood in the process

Our Approach:

HABER’s eLIXA® platform provided real-time artificial intelligence and machine learning-based closed-loop control for DSA.

Key parameters were measured in real-time. The acquired data was incorporated by eLIXA® performing continual analysis to get the ideal chemical solution, which was adjusted and dosed in an automated manner, ensuring the improvement of Strength and Surface Properties of the paper.


Post the implementation of our approach, the following improvements were observed at the customer’s site:

-         40% reduction in softwood usage

-         15% increase in the paper’s tensile strength

-         8% reduction in the consumption of chemicals

Implementation of the AI/ML algorithm optimised the chemical dosing of strength improvement aid in the process. The real-time analysis of data ensured that the loss of raw material due to delay in solution implementation was avoided. This resulted in an increase in production quality as well as quantity without the need to increase the amount of raw material used.

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