Public interest in carbon and water footprints, ecosystem degradation and resource depletion, are just some of the environmental issues that drive the process industries to exercise greater responsibility for the environment in the design and operations of their manufacturing systems. This increasing emphasis on sustainability has driven a shift in process systems design and optimization from the traditional, economics-oriented methods towards methods that balance environmental protection in addition to economic profitability. This project is aimed at incorporating sustainability principles systematically and effectively into the design and optimization of process systems. Previously, such efforts were limited to the process boundary, while now, the boundary has expanded to include the life cycle. This broader perspective reduces the chance of unintended externalities by shifting the problem outside a narrow process boundary. Research challenges arise from the large size and scope of the problem, the multiscale nature of models and data, the potential presence of multiple non-cooperative decision makers, and the high degrees of uncertainty across temporal scales.
The objective of this project is to address the fundamental issues associated with multi-scale sustainability optimization of process systems design and operations decisions. This work will augment process systems engineering tools on supply chain optimization, sustainable engineering and the treatment of uncertainties. The research activities are to develop: (1) a systematic study and a novel multi-scale life cycle process systems optimization (LCPSO) framework that accounts for and optimizes the direct and indirect environmental impacts from the foreground process systems scale and from the background economy scale through the integration of process systems optimization with process-based and input-output-based models; (2) a novel and transformative LCPSO framework based on game theoretical modeling for non-cooperative supply chains with multiple individual decision-makers to account for the life cycle environmental sustainability and economic objectives of individual decision makers; and (3) a new approach for quantifying the role of uncertainties at multiple temporal scales for LCPSO.
The research has the potential to improve the economic competitiveness and environmental sustainability of the process industries. The results will offer insights to identify sustainable strategies for (re-)designing process systems and improving operational practices. The proposed optimization algorithms could result in benefits beyond the chemical engineering community and find applications in other arenas where systematic decision-making is pursued. The results will be integrated into education and outreach activities in the following areas: (1) incorporation of research findings into "Chemical Engineering Design Projects" and "Process Optimization" courses; (2) enhancing undergraduate students' participation in research; (3) working with a local, predominantly minority high school for an interactive STEM Saturdays outreach program; and (4) development of a "Distinguished Junior Researcher Seminar Series" by inviting junior research scholars in related fields to deliver seminars at the PI's institution.
