Many uncertain factors affect the operation of wastewater treatment plants. These include the physical and chemical properties of wastewater streams as well as the degradation mechanisms exhibited by biological processes. Because of the rising concerns about environmental and economic impacts, improved process control algorithms, using artificial intelligence technologies, have received wide at...

This paper describes an Autoassociative Neural Network (AANN) based plant wide sensor calibration monitoring system that detects sensor drifts and replaces the faulty sensor output with a best estimate of the fault free value. A network tuning paradigm has also been implemented that allows the network to function when new plant conditions are encountered. The system was tested using data from t...

a new method is developed for a fast identification of the stability situation of industrial processes. the proposed method includes two factor ratios of the control constants for the upper and lower control limits to process these constants. an indication ratio is then defined as the ratio of the maximum data range value to the difference between the maximum and average values for individual d...

In today’s globally competitive marketplace, industrial plants are looking at new ways to increase plant efficiency, production rates, safety and reliability. Engineer education, training 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 c...

the classical method of process capability analysis necessarily assumes that collected data are independent; nonetheless, some processes such as biological and chemical processes are autocorrelated and violate the independency assumption. many processes exhibit a certain degree of correlation and can be treated by autoregressive models among which the autoregressive model of order one (ar (1)) ...