Managing uncertainties in a safety-constrained process system for solvent selection and usage: an optimization approach with technical, economic, and risk factors

This paper addresses the problem of managing uncertainties in a safety-constrained process system for economic performance enhancement. Within such a context, a typical solvent selection problem involves a number of different solvents with nominal property values that are utilized in various process units and requires the minimization of the total operating cost while satisfying certain technical performance criteria and process safety constraints. Practically, in any process system, property values of streams are not exact; they are usually functions of operating variables and market conditions that change over time inevitably introducing irreducible uncertainties in system performance. A key aim of the present study is to systematically explore the effect of volatility in solvent prices on the economic performance of the process. Appropriate sensitivity analysis and Monte Carlo simulation work have been carried out to assist the decision maker in taking into account the continuously changing market conditions, while identifying operationally safe feasibility regions for solvents with different risk characteristics in the underlying optimization problem. The aforementioned uncertain inputs are shown to cause shifts of the associated Pareto front of optimal solutions toward feasibility regions that can be characterized in a more realistic manner. Finally, an illustrative case study that uses the permissible exposure limit as a risk factor is considered to evaluate the proposed method.