Industrial SBR Process: Computer Simulation Study for Online Estimation of Steady-State Variables Using Neural Networks
نویسندگان
چکیده
This work investigates the industrial production of styrene-butadiene rubber in a continuous reactor train, and proposes a soft sensor for online monitoring of several processes and polymer quality variables in each reactor. The soft sensor includes two independent artificial neural networks (ANN). ThefirstANNestimatesmonomer conversion, solid content, polymer production, average particle diameter, and average copolymer composition; the second ANN estimates average molecular weights and average branching degrees. The required ANN inputs are: (i) the reagent feed rates into the first reactor and (ii) the reaction heat rate in each reactor. The proposed ANN-based soft sensor proved robust to several measurement errors, and is suitable for online estimation and closedloop control strategies.
منابع مشابه
Step change point estimation in the multivariate-attribute process variability using artificial neural networks and maximum likelihood estimation
In some statistical process control applications, the combination of both variable and attribute quality characteristics which are correlated represents the quality of the product or the process. In such processes, identification the time of manifesting the out-of-control states can help the quality engineers to eliminate the assignable causes through proper corrective actions. In this paper, f...
متن کاملEstimation of Products Final Price Using Bayesian Analysis Generalized Poisson Model and Artificial Neural Networks
Estimating the final price of products is of great importance. For manufacturing companies proposing a final price is only possible after the design process over. These companies propose an approximate initial price of the required products to the customers for which some of time and money is required. Here using the existing data of already designed transformers and utilizing the bayesian anal...
متن کاملOnline Monitoring and Fault Diagnosis of Multivariate-attribute Process Mean Using Neural Networks and Discriminant Analysis Technique
In some statistical process control applications, the process data are not Normally distributed and characterized by the combination of both variable and attributes quality characteristics. Despite different methods which are proposed separately for monitoring multivariate and multi-attribute processes, only few methods are available in the literature for monitoring multivariate-attribute proce...
متن کاملConfidence Interval Estimation of the Mean of Stationary Stochastic Processes: a Comparison of Batch Means and Weighted Batch Means Approach (TECHNICAL NOTE)
Suppose that we have one run of n observations of a stochastic process by means of computer simulation and would like to construct a condifence interval for the steady-state mean of the process. Seeking for independent observations, so that the classical statistical methods could be applied, we can divide the n observations into k batches of length m (n= k.m) or alternatively, transform the cor...
متن کاملDynamic Performance Analysis and Simulation of a Full Scale Activated Sludge System Treating an Industrial Wastewater Using Artificial Neural Network
Due to changeable nature of the industrial wastewaters, proper operation of an industrial wastewater treatment plant is of prior importance in order to keep the process stability at the desired conditions. In this mean, simulation of the treatment system behavior using artificial neural network (ANN) can be an effective tool. This paper evaluates long term performance and process stability of ...
متن کامل