Development of an optimization model for biofuel facility size and location and a simulation model for design of a biofuel supply chain

To mitigate greenhouse gas (GHG) emissions and reduce U.S. dependence on imported oil, the United States (U.S.) is pursuing several options to create biofuels from renewable woody biomass (hereafter referred to as “biomass”). Because of the distributed nature of biomass feedstock, the cost and complexity of biomass recovery operations has significant challenges that hinder increased biomass utilization for energy production. To facilitate the exploration of a wide variety of conditions that promise profitable biomass utilization and tapping unused forest residues, it is proposed to develop biofuel supply chain models based on optimization and simulation approaches. The biofuel supply chain is structured around four components: biofuel facility locations and sizes, biomass harvesting/forwarding, transportation, and storage. A Geographic Information System (GIS) based approach is proposed as a first step for selecting potential facility locations for biofuel production from forest biomass based on a set of evaluation criteria, such as accessibility to biomass, railway/road transportation network, water body and workforce. The development of optimization and simulation models is also proposed. The results of the models will be used to determine (1) the number, location, and size of the biofuel facilities, and (2) the amounts of biomass to be transported between the harvesting areas and the biofuel facilities over a 20-year timeframe. The multi-criteria objective is to minimize the weighted sum of the delivered feedstock cost, energy consumption, and GHG emissions simultaneously. Finally, a series of sensitivity analyses will be conducted to identify the sensitivity of the decisions, such as the optimal site selected for the biofuel facility, to changes in influential parameters, such as biomass availability and transportation fuel price. Intellectual Merit The proposed research will facilitate the exploration of a wide variety of conditions that promise profitable biomass utilization in the renewable biofuel industry. The GIS-based facility location analysis considers a series of factors which have not been considered simultaneously in previous research. Location analysis is critical to the financial success of producing biofuel. The modeling of woody biomass supply chains using both optimization and simulation, combing with the GIS-based approach as a precursor, have not been done to date. The optimization and simulation models can help to ensure the economic and environmental viability and sustainability of the entire biofuel supply chain at both the strategic design level and the operational planning level. Broader Impacts The proposed models for biorefineries can be applied to other types of manufacturing or processing operations using biomass. This is because the biomass feedstock supply chain is similar, if not the same, for biorefineries, biomass fired or co-fired power plants, or torrefaction/pelletization operations. Additionally, the research results of this research will continue to be disseminated internationally through publications in journals, such as Biomass and Bioenergy, and Renewable Energy, and presentations at conferences, such as the 2011 Industrial Engineering Research Conference. For example, part of the research work related to biofuel facility identification has been published: Zhang, Johnson and Sutherland [2011] (see Appendix A). There will also be opportunities for the Michigan Tech campus community to learn about the research through the Sustainable Future Institute.

Decentralized or centralized production : impacts to the environment, industry, and the economy

Since product take-back is mandated in Europe, and has effects for producers worldwide including the U.S., designing efficient forward and reverse supply chain networks is becoming essential for business viability. Centralizing production facilities may reduce costs but perhaps not environmental impacts. Decentralizing a supply chain may reduce transportation environmental impacts but increase capital costs. Facility location strategies of centralization or decentralization are tested for companies with supply chains that both take back and manufacture products. Decentralized and centralized production systems have different effects on the environment, industry and the economy. Decentralized production systems cluster suppliers within the geographical market region that the system serves. Centralized production systems have many suppliers spread out that meet all market demand. The point of this research is to help further the understanding of company decision-makers about impacts to the environment and costs when choosing a decentralized or centralized supply chain organizational strategy. This research explores; what degree of centralization for a supply chain makes the most financial and environmental sense for siting facilities; and which factories are in the best location to handle the financial and environmental impacts of particular processing steps needed for product manufacture. This research considered two examples of facility location for supply chains when products are taken back; the theoretical case involved shoe resoling and a real world case study considered the location of operations for a company that reclaims multiple products for use as material inputs. For the theoretical example a centralized strategy to facility location was optimal: whereas for the case study a decentralized strategy to facility location was best. In conclusion, it is not possible to say that a centralized or decentralized strategy to facility location is in general best for a company that takes back products. Each company’s specific concerns, needs, and supply chain details will determine which degree of centralization creates the optimal strategy for siting their facilities.