DocumentCode :
433733
Title :
Process control: potential benefits and wasted opportunities
Author :
Brisk, M.L.
Author_Institution :
Dept. of Chem. Eng., Monash Univ., Melbourne, Vic., Australia
Volume :
1
fYear :
2004
fDate :
20-23 July 2004
Firstpage :
10
Abstract :
Seventeen years ago the University of Sydney Warren Centre´s study demonstrated that introducing advanced control systems could potentially provide bottom-line benefits in the range of two to six percent of operating costs. Since then the process industry world-wide has reported many successful applications of a range of advanced control technologies which achieved, or exceeded, those benefits. There are now a plethora of multivariable predictive controls, inferential sensors, dynamic modelling tools, fuzzy logic algorithms, and neural networks, and we know how to use them. So does it follow that industry is consistently achieving the best possible process control performance and realizing all those potential benefits? The answer, unfortunately, is a depressing no! Recent studies have shown that only about a third of industrial controllers are achieving acceptable levels of performance, and this is especially true at the most basic levels of control, needed to underpin the advanced controls. Indeed, there are reported trends which suggest the gap between desired and actual controller performance is widening! This paper revisits the Warren Centre study and its benefits analysis methodology, and addresses the issues of actually achieving those benefits. This is shown to be more than just the introduction of advanced control technology. There is a need to re-focus on the humble - but vital PID controller, and the often overlooked issue of ensuring continued maintenance of the best performance of existing controls, if industry is to stop wasting the opportunities to gain those benefits.
Keywords :
process control; three-term control; PID controller; Warren Centre study; advanced control system; dynamic modelling tool; fuzzy logic algorithm; industrial controller; inferential sensor; multivariable predictive control; neural network; process control; process industry; Control systems; Costs; Electrical equipment industry; Fuzzy logic; Industrial control; Neural networks; Predictive control; Predictive models; Process control; Three-term control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Conference, 2004. 5th Asian
Conference_Location :
Melbourne, Victoria, Australia
Print_ISBN :
0-7803-8873-9
Type :
conf
Filename :
1425930
Link To Document :
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