(118a) Optimal Synthesis and Planning of Sustainable Processes

Sustainability has recently emerged as a key issue in process systems engineering (PSE). Mathematical programming techniques offer a general modeling framework for including environmental concerns in the synthesis and planning of chemical processes. Including environmental issues in the synthesis and planning of chemical processes poses significant challenges that have not yet been fully solved, and hence merit further attention. One major critical issue is how to systematize the search for alternatives leading to reductions in environmental impact. Furthermore, aside from anticipating the effect of uncertainties, which are quite pronounced in this area, there is the issue on how to cope with competing economic and environmental objectives. Hence, there is a clear need to develop sophisticated optimization and decision-support tools to help in exploring and analyzing diverse process alternatives under uncertainty, and so as to yield optimal trade-offs between environmental performance and profit maximization. These methods should be employed to improve the environmental performance at different hierarchical levels, covering both single-site and multi-site industrial applications. The aim of this paper is to summarize major contributions made in these fields, paying special attention to those based on mathematical programming. We center our discussion on two specific areas of PSE that can potentially help to identify and establish for environmental improvements: process synthesis and supply chain management (SCM).

While perhaps obvious, it is clear that the area of sustainability offers a great opportunity to renew the interest in process synthesis since it appears that many of the new biofuel plants have not had the benefit of being subjected to more systematic and thorough optimizations as their petrochemical counterparts. This can lead to flawed analyses when comparing energy content or life cycle analysis of competing energy technologies. However, as will be illustrated in a bioethanol example, it is not sufficient to simply apply the known synthesis techniques to improve the design of these new processes. Furthermore, a major challenge not encountered in conventional process synthesis is that many of the biofuel plants are rather small and therefore cannot benefit of the economies of scale. In the area of supply chain management it will be shown that progress has been made in terms of incorporating models for environmental impact within a multiobjective optimization framework. However, the greatest challenge still lies in properly accounting for the uncertainties associated with the parameters of these models (e.g. emissions, potential harm, etc.). Finally, although one can in principle formulate the associated optimization problems discussed above, it is clear that models are often very large, potentially defeating current computational capabilities. Hence, we also briefly discuss effective solution approaches and algorithms for solving these problems.