Application of Artificial Neural Network (ANN) in Chemical Engineering: A Review

Chemical Engineering

Many times, we encounter with some system or process where it become complex to determine the correlation between the dependent and independent variables. Chemical engineering has many such examples where we can obtain the output values for predetermined values of input parameters, experimentally. But it is quite complex to develop a mathematical model which can map the behavior and interdependency of process or system parameters. Even sometimes it is not easy to find the solution of such mathematical models. It became time consuming because the complexity increases if the system is nonlinear and requires high level of technical expertise. For such system or process, ANN is getting the attention of the technical world. ANN basically is a computational technique that has the capability to model correlation between the process variables, input and output values. Traditional approaches have some limitation in solving chemical engineering problems, like modeling of highly complex nonlinear systems. Hence for such complexity, artificial neural networks (ANN) is found to solve complicated tasks in a variety of practical applications. In this article several applications of ANN in chemical engineering is discussed.

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