Multi-objective optimization for the incorporation of safety and reliability considerations in process design

Abstract

Abstract In the traditional process design approach, aspects such as safety and reliability are typically left for analysis once the design phase is completed. Recently, methods have been developed to include inherent safety in the early design stages. This approach allows the generation of inherently safer designs as part of the process synthesis task. The design of reliable chemical processing plants can be enhanced by adding back-up units to prevent shutting down the plant due to failure of units. In this work, we present a multi-objective optimization model for the design of chemical process systems accounting for safety, reliability, and economics. The model is formulated within a generalized disjunctive programming framework, which is then reformulated as a mixed-integer nonlinear programming model using the e-constrained method to generate pareto curves. The model includes the selection of standby units to increase the system availability and provides the optimal structure of the process flowsheet and operating parameters. The model is applied to the design of a distillation system accounting for risks due to explosion, while rating the system reliability and the process economics. The results show that the proposed optimization model yields design alternatives with optimal trade-offs among safety, reliability, and economics.