Development of a multi criteria process design framework for sustainable design and synthesis of processes

Abstract

A methodology is proposed to address sustainability concerns with special intention to chemical process design. Through this methodology, aspects of sustainability are evaluated with sustainability metrics which are calculated using a sustainability evaluator module. This module is part of a novel platform for selection of most sustainable alternatives of process technologies. The platform consists of a novel rigorous multi-objective optimization algorithm in tandem with a commercial process simulator for rigorous design and optimization of the processes. The platform is capable of handling a multitude of objectives and constraints. This project develops a rigorous optimization based framework in which the ultimate goal is to select most desirable process alternatives based on a multitude of criteria such as sustainability impacts. This research contributes to sustainability development assessment in process design. This study addresses a major challenge in process design as engineers will now be able to design for multiple criteria, not restricted but specifically sustainability concerns. This work will develop approaches for the optimization of chemical processing technologies with sustainability considerations. The objectives of this research are to:

Develop a modified Particle Swarm algorithm to handle a multitude of objectives

Develop a method for handling mixed integer optimization problems

Propose an effective constraint handling methodology

Formulate an algorithm that incorporates multi-objective optimization a non-dominated methodology to enable process design with several objectives especially to satisfy social, economic and environmental objectives

program a generic computer aided tool to assess process technologies in terms of sustainability

Propose a decision making procedure for selecting the most sustainable process from multiple optimum alternatives that will remain sustainable in the future

Link the proposed optimization algorithm to a process simulator for black box process optimization

Evaluate the performance of the methodology