Simulation and optimisation of the controls of the stock preparation area of a paper machine.

Abstract

At Mondi Paper Ltd, Merebank, South of Durban, Paper Machine 2 has recently been transferred onto a Distributed Control System (DCS). This was seen as a good opportunity to enhance the control of the pulp feed to the machine. A prime concern in operating a paper machine is to ensure consistent set-point paper properties in the Cross-Direction (CD: ie. across the paper width) and in the Machine-Direction (MD: ie. along the paper length). Sophisticated adjustments are available to ensure an even feed of the stock (consistencies around 2% m/m wood fibres in water) from the head-box across the receiving width of the paper machine. The properties of prime interest as the pulp is pumped through the head-box distributor onto the receiving belt of the machine are the basis weight (fibre mass per unit area) and moisture content (per unit area). However, the distribution system is highly dependent on the properties of the stock as it arrives at the head-box. Variations in upstream chest levels, the supplied pressure, flow-rate and fibre/water ratio, all cause MD and even CD variations. The problems of maintaining steady conditions at the head-box are well known, and are understood to arise from sub-optimal control in the preceding section involving a blend chest and machine chest, amongst other items, where several pulp streams and dilution water are combined. A number of control loops are involved, but appear to require different tuning for different paper grades. Often individual loops are taken off-line. In this study, an understanding of the controller interactions in the stock preparation section has been developed by detailed dynamic modelling, including all of the existing control loops. The model is built up in a modular fashion using a basic element, having one input (which can collect multiple streams originating elsewhere) and four outputs, linked through a vessel of variable volume. Several basic elements are linked together to form the overall system. All of the necessary properties can be defined so that the model allows the simulation of all features of the network: vessels, pipes, junctions, valves, levels and consistencies. A set of first order differential equations is solved which includes total water balance, species mass balances, derivatives of flow controller action, and derivatives of supervisory controller action. Supervisory controllers for consistency or level cascade onto flow controllers. Flow controllers manipulate valves which give a first-order dynamic response of actual flow. Where valves are manipulated directly by the supervisory level, the flow controller is effectively bypassed. This study involves a constraint problem around the blend chest, resulting in a loss of specification at the paper machine. This was solved by the implementation of a static optimiser. Its objective function penalizes deviations from setpoint of five parameters (ratios, consistency and level) using respective weight factors. Both the model and its optimiser were included in a simulator designed with the graphical user interface (GUI) of Matlab. The simulator has then been used to explore control performance over the operating range, by means of a set of scenarios.