An efficient multi criteria process optimization framework: Sustainable improvement of the Dimethyl Ether Process

• A process design framework for incorporating a multitude of objectives into design of processes is presented.
• The proposed framework reliably and efficiently accounts for sustainability concerns in process design and retrofit.
• Sustainability metrics are treated as separate objectives to obviate the problems of objective scalarization.
• A novel efficient optimization algorithm for handling conflicting design objectives is utilized.
• A fuzzy based decision making method is introduced to reduce the cognition load on decision makers.

No longer is it appropriate to evaluate processes for economic feasibility alone; social benefits and environmental impacts must also be considered. This work develops a multi criteria systematic framework for optimum process design with sustainability considerations and addresses a major challenge in process design as engineers will now be able to design for multiple criteria, specifically sustainability concerns. A novel multi objective optimization algorithm capable of handling a multitude of objectives in mixed integer nonlinear search space and a novel decision making methodology are integrated with a sequential modular process simulator to optimize processes with a multitude of objectives rigorously and efficiently. The application of this research extends well beyond sustainability considerations to the very vast area of optimum design with multi criteria. The application of the proposed framework is demonstrated through a case study for process retrofit of Dimethyl Ether production plant.