SUSCAPE: A framework for the optimal design of SUStainable ChemicAl ProcEsses incorporating data envelopment analysis

Abstract

Developing computer aided tools for process design is of paramount importance in the transition toward a more sustainable chemical industry. In this work, we present a framework to incorporate sustainability principles in the design of chemical processes that combines a palette of tools, including life cycle assessment, surrogate modeling, objective reduction, multi-objective optimization and data envelopment analysis (DEA). The latter methodology facilitates the post-optimal analysis of the Pareto front by narrowing down the number of designs and ranking them without the need to define weights in an explicit manner. DEA provides in turn improvement targets for the suboptimal alternatives that if attained would make them optimal, thereby guiding retrofit efforts toward the most effective actions based on benchmarking them against the best technologies available. The capabilities of the framework are demonstrated in a case study based on the production of methanol from CO2 and hydrogen.