Application of pareto optimization under uncertainty in chemical process design for sustainability

The development of a sustainable chemical processes aims at optimizing its economic, environmental and societal sustainability simultaneously. This can be solved as a multi-objective optimization (MOO) problem. However, in real systems, there are many uncertainties that affect the performance of a process. These include market fluctuation, changes in material properties, manufacturing variations, errors in model prediction etc. In order to generate a more robust solution, it is essential to develop a multi-objective optimization methodology including uncertainty. This would facilitate the design for sustainability.
In this paper, the authors use the Pareto optimization methodology to identify the optimal design specifications and operating conditions of chemical processes under uncertainties. The objective of this MOO problem is to maximize the overall sustainability of the process. The utility of this methodology is demonstrated by a case study based on the design of a condensate treatment unit in an ammonia plant.