Process modelling is an important branch of mechanical engineering and is required for optimizing control parameters. This is of great significance to the industry in improving their production efficiency. Process modelling is based on the basic principles of heat and mass transport. Because of improved computational facilities, present day process modelling involves implementation of an algorithm aided by modern computers to predict the behavior of a process under certain control parameters, which can be tuned to study their effects on overall efficiency and output enhancement. The main goal is to optimize process parameters within minimum number of actual experiments. Both forward and inverse models are commonly used. Forward modelling is used to predict the output by tuning the control parameters. On the other hand, real plant data can be collected and analysed via inverse modelling to predict the control parameters. Shop floor automation is another important aspect of process modelling, where the ultimate aim is to design an intelligent system capable of automatically controlling the process parameters based on some internal feedback mechanism.
Propagate the use of process modelling tools amongst academics and industries through continuing education programmes, research and consultancy.