Robust approach to dynamic statistical process control

Statistical Process Control (SPC) technique are well established across a wide range of industries. In particular, the plotting of key steady state variables with their statistical limit against time (Shewart charting) is a common approach for monitoring the normality of production. This paper aims with extending Shewart charting techniques to the quality monitoring of variables driven by uncertain dynamic processes, which has particular application in the process industries where it is desirable to monitor process variables on-line as well as final product. The robust approach to dynamic SPC is based on previous work on guaranteed cost filtering for linear systems and is intended to provide a basis for both a wide application of SPC monitoring and also motivate unstructured fault detection.

Improved energy efficiency in paper making through reducing dryer steam consumption using advanced process control

Over the last two or three years, the increasing costs of energy and worsening market conditions have focussed even greater attention within paper mills than before, on considering ways to improve efficiency and reduce the energy used in paper making. Arising from a multivariable understanding of paper machine operation, Advanced Process Control (APC) technology enables paper machine behaviour to be controlled in a more coherent way, using all the variables available for control. Furthermore, with the machine under better regulation and with more variables used in control, there is the opportunity to optimise machine operation, usually providing very striking multi-objective performance improvement benefits of a number of kinds. Traditional three term control technology does not offer this capability. The paper presents results from several different paper machine projects we have undertaken around the world. These projects have been aimed at improving machine stability, optimising chemicals usage and reducing energy use. On a brown paperboard machine in Australasia, APC has reduced specific steam usage by 10%, averaged across the grades; the controller has also provided a significant capacity to increase production. On a North American newsprint machine, the APC system has reduced steam usage by more than 10%, and it provides better control of colour and much improved wet end stability. The paper also outlines early results from two other performance improvement projects, each incorporating a different approach to reducing the energy used in paper making. The first of these two projects is focussed on optimising sheet drainage, aiming to present the dryer with a sheet having higher solids content than before. The second project aims to reduce specific steam usage by optimising the operation of the dryer hood.

Modelling and predictive control: Enabling technologies for reconfiguration

An approach to reconfiguring control systems in the event of major failures is advocated. The approach relies on the convergence of several technologies which are currently emerging: Constrained predictive control, High-fidelity modelling of complex systems, Fault detection and identification, and Model approximation and simplification. Much work is needed, both theoretical and algorithmic, to make this approach practical, but we believe that there is enough evidence, especially from existing industrial practice, for the scheme to be considered realistic. After outlining the problem and proposed solution, the paper briefly reviews constrained predictive control and object-oriented modelling, which are the essential ingredients for practical implementation. The prospects for automatic model simplification are also reviewed briefly. The paper emphasizes some emerging trends in industrial practice, especially as regards modelling and control of complex systems. Examples from process control and flight control are used to illustrate some of the ideas.

Thermal energy minimisation in papermaking via MD control approach

This paper reports the application of Advanced Process Control (APC) techniques for improving the thermal energy efficiency of a paperboard-making process by regulating the Machine Direction (MD) profile of the basis weight and moisture content of the paper-board. A Model Predictive Controller (MPC) is designed so that the sheet moisture and basis weight tracking errors along with variations of the sheet moisture and basis weight are reduced. Also, the drainage is maximised through improved wet-end stability which can facilitate driving the sheet moisture set-point closer to its upper specification limit over time. It is shown that the proposed strategy can result in reducing steam usage by 8-10%. A simulation study based on a UK board machine is presented to show the effectiveness of the proposed technique. © 2011 Intl Journal of Adv Mechatr.