A Process Systems Engineering Approach to Decision-Making in the Chemical Industry

Abstract

A variety of optimization tools are used in the chemical industry, but they are often embedded in inflexible, isolated, manual, and complex decision-making processes. This work proposes a decision-making framework that integrates models, data, and decision-makers into data-connected decision cells, organized within a decision graph. The framework formalizes decision processes and enables systematic and adaptive workflows across decision layers. The framework can be applied to various use cases, including supply chain optimization and process design, to address the evolving challenges of the chemical industry. It enables a shift from component-level optimizations toward system-wide optimization strategies that account for the interconnected nature of complex production systems.