Evaluating opportunities to improve material and energy impacts in commodity supply chains

Rebecca J. Hanes () and Alberta Carpenter ()
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Rebecca J. Hanes: National Renewable Energy Laboratory
Alberta Carpenter: National Renewable Energy Laboratory

Environment Systems and Decisions, 2017, vol. 37, issue 1, 6-12

Abstract: Abstract When evaluated at the scale of individual processes, next-generation technologies may be more energy and emissions intensive than current technology. However, many advanced technologies have the potential to reduce material and energy consumption in upstream or downstream processing stages. In order to fully understand the benefits and consequences of technology deployment, next-generation technologies should be evaluated in context, as part of a supply chain. This work presents the Materials Flow through Industry (MFI) supply chain modeling tool. The MFI tool is a cradle-to-gate linear network model of the US industrial sector that can model a wide range of manufacturing scenarios, including changes in production technology and increases in industrial energy efficiency. The MFI tool was developed to perform supply chain scale analyses in order to quantify the impacts and benefits of next-generation technologies and materials at that scale. For the analysis presented in this paper, the MFI tool is utilized to explore a case study comparing three lightweight vehicle supply chains to the supply chain of a conventional, standard weight vehicle. Several of the lightweight vehicle supply chains are evaluated under manufacturing scenarios that include next-generation production technologies and next-generation materials. Results indicate that producing lightweight vehicles is more energy and emission intensive than producing the non-lightweight vehicle, but the fuel saved during vehicle use offsets this increase. In this case study, greater reductions in supply chain energy and emissions were achieved through the application of the next-generation technologies than from application of energy efficiency increases.

Keywords: Supply chain modeling; Manufacturing; Energy efficiency; Materials (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1007/s10669-016-9622-5

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