Board Machine: Stability, Energy Efficiency & Product Quality
Case Study Pulp and Paper - Packaging Grades
Company Smurfit Kappa Group
Challenge Improve stability and energy efficiency
Solution Board Machine Wet-End Optimisation
Results Payback within 5 months
Smurfit Kappa Group are on of the world's largest manufacturers of paper-based packaging. The group operates in 30 countries, and is the European leader in all types of paperboard production.
Smurfit Kappa's Paper Machine 4 at the UK Birmingham mill produces fluting and test liner paper from 100% recycled packaging waste.
Producing high quality recycled board is both challenging and energy intensive. The recycled feed stock tends to be variable in both quality and drainability (or freeness). These variations lead to reductions in machine stability, increased steam consumption and reduced machine efficiency.
The business challenge is succeed in an extremely competitive market by producing large volumes of high quality paper-board as efficiently as possible.
Lower energy, reduced waste, lower cost of manufacture, fast return on investment. Read more...
Board machines operate at high production rates and are often bottle-necked by their dryer's capacity. In this mode of operation stability of the "wet-end" is critical. Natural variations in feedstock freeness introduce instability in the wet-end's backwater consistency and hence machine retention. This instability often leads to paper-breaks and associated lost production.
Perceptive Engineering delivered an Advanced Process Control solution in partnership with the EPSRC and Universities of Manchester and Cambridge. The APC system's objectives are to maximise energy efficiency and machine stability using a robust model which describes the interactions between key Machine Direction (MD) and wet-end variables and their influence on sheet moisture, weight and backwater consistency. This model is used in a Model Predictive Controller to reduce wet-end variability and improve sheet quality by handling the machine interactions and dynamics. The solution also incorporates energy optimisation techniques developed in conjunction with the University partners.
RETURN ON INVESTMENT
The main deliverable of the solution is a Model Predictive Controller. The controller provides:
Closed loop control of MD basis weight and moisture. This has reduced the variability of MD weight and moisture by 55% on average.
A reduction in top and bottom layer backwater consistency variation of 62% and 42%, respectively.
The platform of reduced variability delivered by the MPC has been used as a basis for energy optimisation. This delivers the following primary business benefits:
A 3% reduction in steam consumption across all grades. This corresponds to a 1,600 t/y reduction in CO2 emissions.
A reduction in fibre cost of 0.7% per annum.
Ancillary electrical energy savings of 4% through vacuum and dryer pressure control retuning.
The benefits delivered a full return on investment within 5 months of commissioning, sustained via an ongoing support program provided by Perceptive.
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