2015•Unpublished venueRequires access

Industrial Plant Optimization and Advanced Control Application

Nenad Bolf, Ivan Mohler

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Abstract

In today’s globally competitive marketplace, industrial plants are looking at new ways to increase plant efficiency, production rates, safety and reliability. Engineer education and training, monitoring, diagnosis and plant optimization play a key role in satisfying technological, economical and environmental constraints. Furthermore, control system optimization is the basis for system improvement and advanced process control (APC) implementation. Very few plants use modern software for control quality monitoring, controller tuning, APC or optimization. The reasons are absence of engineering knowledge and unavailability of practical and robust process control software tools for system identification, parameter optimization and control quality monitoring, running plants conservatively due to fear of causing shutdowns and plant problems. Process control software tools for quick and easy system identification using available data from the plant’s historian can help tremendously improve the control quality and the plant’s profit margin. It is possible to analyze multivariable systems, complex, nonlinear and slow processes with long dead times and long time constants commonly encountered in process industry. Optimization of primary and advanced control schemes stabilizes the process and allows the plant to run closer to process, equipment and economic constraints. This increases production rates, minimizes operating costs and improves product quality. The overall control system performance is significantly improved which ultimately has a positive effect on product quality and energy consumption thus proving application of control system diagnostics and optimization usefulness.

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What this paper is about

In today’s globally competitive marketplace, industrial plants are looking at new ways to increase plant efficiency, production rates, safety and reliability. Engineer education and training, monitoring, diagnosis and plant optimization play a key role in satisfying technological, economical and environmental constraints. Furthermore, control system optimization is the basis for system improvement and advanced process control (APC) implementation. Very few plants use modern software for control quality monitoring, controller tuning, APC or optimization. The reasons are absence of engineering knowledge and unavailability of practical and robust process control software tools for system identification, parameter optimization and control quality monitoring, running plants conservatively due to fear of causing shutdowns and plant problems. Process control software tools for quick and easy system identification using available data from the plant’s historian can help tremendously improve the control quality and the plant’s profit margin. It is possible to analyze multivariable systems, complex, nonlinear and slow processes with long dead times and long time constants commonly encountered in process industry. Optimization of primary and advanced control schemes stabilizes the process and allows the plant to run closer to process, equipment and economic constraints. This increases production rates, minimizes operating costs and improves product quality. The overall control system performance is significantly improved which ultimately has a positive effect on product quality and energy consumption thus proving application of control system diagnostics and optimization usefulness.

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Available abstract

In today’s globally competitive marketplace, industrial plants are looking at new ways to increase plant efficiency, production rates, safety and reliability. Engineer education and training, monitoring, diagnosis and plant optimization play a key role in satisfying technological, economical and environmental constraints. Furthermore, control system optimization is the basis for system improvement and advanced process control (APC) implementation. Very few plants use modern software for control quality monitoring, controller tuning, APC or optimization. The reasons are absence of engineering knowledge and unavailability of practical and robust process control software tools for system identification, parameter optimization and control quality monitoring, running plants conservatively due to fear of causing shutdowns and plant problems. Process control software tools for quick and easy system identification using available data from the plant’s historian can help tremendously improve the control quality and the plant’s profit margin. It is possible to analyze multivariable systems, complex, nonlinear and slow processes with long dead times and long time constants commonly encountered in process industry. Optimization of primary and advanced control schemes stabilizes the process and allows the plant to run closer to process, equipment and economic constraints. This increases production rates, minimizes operating costs and improves product quality. The overall control system performance is significantly improved which ultimately has a positive effect on product quality and energy consumption thus proving application of control system diagnostics and optimization usefulness.

Key concepts: Unavailability, Engineering, Process control, Control system, Advanced process control, Process (computing), Quality (philosophy), Reliability engineering

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