(56e) Towards Safe and Reliable Eco-Industrial Parks: An Integration and Optimization Approach

The development of Eco-Industrial Parks (EIPs) has drawn much attention due to the growing concern in sustainability. The main idea of an EIP is to form an interdependent production infrastructure that combines chemical plants for integrations of materials, energy, water, utility system, and waste management. However, such highly integrated processes usually result in complex systems with a large number of connections for mass and heat transportation. Thus, a minor incident of one individual plant could lead to a potential decrease in the overall production rate or even complete shutdown of the entire production site. The economic loss due to the event could outweigh the benefits of an integrated system. Safety and reliability considerations should always be included at both design and operation phases. My research focuses on addressing those issues from different aspects within EIPs. The two major areas I have looked into are safety analysis of supply chain network and reliability analysis of water-energy nexus inside industrial parks.

Transportation of chemical plays a central role in supply chain management and multi-plant mass integration through Eco-Industrial Parks. The transported materials often include hazardous materials (HazMat) for which safety is a major concern. My work applies a systematic approach to extract and analyze historical incident data for HazMat to quantify the transportation risk. An optimization framework is then developed to integrate the risk factor into the traditional material allocation problem. The result of my work illustrates a Pareto optimal curve that shows the trade-off between transportation cost and risk, which can guide the decision-making process for optimizing supply chain network within EIPs.

Water-energy nexus analysis is another significant aspect of EIPs. It is one of the promising techniques that can help integrate wastewater into the existing infrastructure and reduce fresh water consumption. I have been working on the development of an optimization framework for the synthesis of reliable direct water recycle network inside industrial parks. My work proposes a statistical model to quantify unit and system reliability, and then integrate it into a mathematical model that represents the direct water recycle network. The model also includes various methods to improve the overall system reliability, such as parallel units and storage tanks. My work results in Pareto optimal solutions that show the trade-off between network cost and reliability. It could help the management to decide the optimal design and operating strategy of the water recycling system to ensure a reliable EIP.

I am a fifth-year PhD candidate from Dr. El-Halwagi’s group at the Artie McFerrin Department of Chemical Engineering, Texas A&M University. My research is in the area of process systems engineering, which focuses on process design and integration, mathematical modeling and optimization. I have experience in optimization theory and algorithms, mathematical programming, and supply chain optimization. I have a strong background in process safety and quantitative risk analysis, where I hold the Safety Engineering Certificate from the Mary Kay O’Connor Process Safety Center. I am also interested in data analysis and machine learning. I have performed various analysis techniques and regression studies on extensive data sets in my research. I am proficient in GAMS, R, VBA, Matlab, Aspen Plus, and Python. I received my bachelor’s degree from the University of Wisconsin – Madison with double majors in chemical engineering and mathematics.