Efficient control for a multi-product quasi-batch process via stochastic dynamic programming

This article considers a quasi-batch process where items are continuously processed while they move on a conveyor belt. In addition, the products arriving into the processor require variable amounts of processing, which translate into different processor levels. Keeping the processing level constant in such a system results in severe inefficiency in terms of consumption of energy and resources with high production costs and a poor level of environmental performance. A stochastic dynamic programming model is formulated that strikes a balance between consumption of energy and material, processor performance, and product quality. The model minimizes total system-wide cost, which is essentially a unified measure across all the objectives. The structural properties of the optimal policy and value functions are analyzed taking into account high-dimensionality of the state space. Based on some of these results, efficient heuristic methodologies are developed to solve large instances of the problem. It is shown using several numerical experiments that a significant amount of energy or material resources can be saved and total costs can be reduced considerably compared to the current practices in the process industry. Insights on the sensitivity of results with respect to the cost parameters are provided.