Chairholder Profile

Sirish Lalji Shah

Department of Chemistry and Materials Engineering
University of Alberta

Chair Title

NSERC-Matrikon-ASRA Industrial Research Chair in Computer Process Control

Chair Program

Industrial Research Chairs Program

Role

Senior Chairholder since 2000

Summary

In most process plants, unit operators are responsible for monitoring several hundred or even thousands of variables. With such a wide span of control, operator responsibility forces them to work in an "alarm-driven" mode, principally depending on the plant control systems to inform them when problems occur. It is well known that many common faults are not detected early enough and in fact may go undetected until the situation becomes serious or a fault occurs. We believe it is important to develop an information-based decision support system for early and preventative detection of faults before they lead to unexpected disruptions or failures.

A recent study conducted in the United States showed that unexpected disruptions to normal operations are estimated to cost the economy at least US$20 billion per year in the petrochemical industry alone. The majority of these unexpected disruptions are due to common faults such as instrument failures, plugged lines, compressor imbalances or fouled process equipment. The reason for such disruptive process faults is that many of the symptoms or indicators that could be used to predict impending problems are seldom detected early enough or were simply lost in the vast files of available data. In fact, often a shutdown or fault occurs before the operators or engineers become aware of the actual problem. However, if the available data is carefully scrutinized in real time, i.e., while the data is being collected, then one can anticipate and detect impending process malfunctions and thus prevent costly process disruptions, off-grade product or environmental damage.

The major thrust of this Chair project then is to develop an information-based decision support (IBDS) system via:

• ongoing and intensive interaction with industrial users to identify user needs and requirements;
• the development of techniques for efficient data preprocessing involving outlier detection, data reconciliation, sensor fault detection and filtering;
• the development and refinement of a suitable set of multivariable statistical process control (MSPC) algorithms for on-line process performance monitoring, knowledge extraction and decision support via intelligent audit/surveillance of process variables;
• the rapid transfer of this technology to industry by translating these algorithms into object-based modules that can be easily implemented at local field levels or on higher-level supervisory computer systems by vendor developers;
• the implementation, testing, and evaluation and trials of these algorithms at several industrial sites on many industrial processes; and
• the dissemination of information at the university, continuing education, technical and user levels.

The development of information-based decision support systems for the process industries will produce direct economic advantages to a wide variety of process industries in the form of smoother, safer process operation, improved product quality, reduced down time, significant assistance for the operation and maintenance personnel, reduced environmental pollution, etc.

Dr. Sirish Shah is an internationally recognized researcher, educator and industrial consultant specializing in process control, with over 25 years experience in industry and academia.

Partners

• Alberta Innovation and Science
• Matrikon Inc.

Contact Information

Department of Chemistry and Materials Engineering
University of Alberta
714 Chemical and Materials Engineering Building
Edmonton, Alberta
T6G 2G6

Tel.: 780-492-3321
Fax: 780-492-8960
E-mail: sirish.shah@ualberta.ca

Web site:
 http://www.ualberta.ca/~slshah