By-product synergy (BPS) is an industrial ecology practice that involves utilization of industrial by-products as feedstocks for other industrial processes. A novel decision support tool is developed to analyze BPS networks that involve material processing and transport among regional clusters of companies. Mathematical programming techniques are used to determine the optimal network design and the material flows that minimize total cost or environmental impacts. This methodology is incorporated into a graphical software package called EcoFlow TM . The tool has been applied to model and analyze available synergies in an existing BPS network centered in Kansas City, Missouri. A base case, which assumes no synergies, is compared with the optimal BPS solution found by Eco-Flow TM . The results for Kansas City suggest that when companies in the network cooperate to optimize the system profitability, up to $15 million per year of savings are possible. The findings also indicate that the BPS approach would result in 29% reduction in total cost, 25.8% reduction in average company cost, 30% reduction in carbon dioxide (CO 2 ) emissions, and 37% reduction in waste to landfill. The modeling approach is being extended to better represent the dynamics of industrial and ecological processes.

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A new system dynamics tool, T21-Ohio, was developed to support integrated and comprehensive development planning at the state level. Based on the Threshold 21 (T21) framework, T21-Ohio provides insights into the potential impacts of energy and environmental policies across a wide range of sectors, and reveals how different strategies interact with one another to achieve planned goals and objectives. This paper shows how T21-Ohio was used to model the broader social, economic and environmental impacts of “waste to profit” activities in Ohio, such as recycling, electricity generation from waste, and bio-fuel production. Three alternative scenarios were simulated to evaluate the impacts of biomass co-firing, government stimulus for solid waste recycling, and by-product synergy activities. The results of the three scenario analyses indicate significant potential for economic development and creation of jobs while reducing emissions and waste

Semiconductor manufacturing is a capital-extensive industry. How to utilize billions of dollars of equipment as efficiently as possible is a critical factor for a semiconductor manufacturer to succeed in stiff competition. Improving performance of manufacturing process increases overall tool throughput, reduces operating costs, and saves companies millions of dollars. In this study, we develop a methodology to analyze and improve a cluster tool's performance. A Colored Petri Net model is developed to determine internal bottleneck resource of the tool. Results conclude that the methodology improves tool efficiency and provides significant cost savings.