Artificial intelligence based modelling and multi-objective optimization of vinyl chloride monomer (VCM) plant to strike a balance between profit, energy utilization and environmental degradation

The current research focuses on the creation of a general technique that solves the key issue of any operational chemical plant, namely, how to strike a delicate balance between profit and environmental impact. As a case study, a commercial vinyl chloride monomer (VCM) production unit was used. This research produced a new modelling and optimization tool that commercial chemical plants can use to measure their environmental impact and strike a careful balance between profit and environmental damage. This paper demonstrates how to model commercial complex reactors using Aspen and ANN in an easy-to-use manner. The current study used a multi-objective hybrid ANN and genetic algorithm to find a delicate balance between profit and environmental damage. A case study of a commercial VCM manufacturing process demonstrates the efficacy of the proposed methodology. The suggested methodology creates optimal VCM reactor operating parameters, which can be used in commercial plants to increase profit. Furthermore, the suggested methodology creates a set of Pareto optimal solutions platform to acquire insight into the profit-environmental impact balance. These insights could be extremely beneficial to plant management in making educated decisions about plant operations.