Materials Flows through Industry (MFI) is a supply chain modeling tool created to identify and analyze opportunities to reduce the energy and carbon intensities of the U.S. industrial sector. MFI is based on a database of products, which are industrial commodities such as primary metals and bulk chemicals, and recipes, physical input-output models of production technologies. The database is combined with several user-specified scenario parameters to model commodity supply chains under different manufacturing scenarios. Key MFI outputs are fossil fuel and renewable energy consumption and greenhouse gas emissions from fuel combustion. Fossil fuel consumption is divided into fuel for electricity generation, industrial process fuel, transportation fuel, and fuel used as chemical feedstock.
A supply chain is modeled by first selecting an end product and specifying the quantity of end product quantity to produce. The manufacturing scenario for the supply chain is then defined with two sets of scenario parameters. One set of scenario parameters defines the technology mix used to produce the end product. The baseline technology mix for each product reflects the current market share of each technology in U.S. industry. Users can specify a custom technology mix for the end product. Technology mix parameters are also used to model changes in the electricity grid. The baseline electricity grid mix represents U.S. electricity generation in 2016; alternative grid mix options include increased renewables, technological improvements in generation technology, and U.S. grid mixes from past years. The second set of scenario parameters, sector efficiency potentials (SEPs), controls the energy efficiency of selected production technologies. SEPs capture increases in energy efficiency that would result from replacing current processing equipment with the most efficient equipment available. SEP data is only available for certain production technologies, but for these technologies users specify how much of the potential efficiency increase is implemented. At baseline levels, all production technologies have zero energy efficiency increase, such that the scenario represents current energy efficiency levels in industry. Along with defining custom manufacturing scenarios, users can choose to include or exclude the effects of industrial co-production, in which one production technology provides multiple useful products.
Once the supply chain model has been run, results in the form of graphics and data tables are output to a downloadable Excel file. The output file also contains a brief explanation for each set of results to aid in user interpretation and further analysis.
This work was authored by Alliance for Sustainable Energy, LLC, the manager and operator of the National Renewable Energy Laboratory for the U.S. Department of Energy (DOE) under Contract No. DE-AC36-08GO28308. Funding provided by U.S. Department of Energy Office of Energy Efficiency and Renewable Energy Advanced Manufacturing Office. The views expressed in the article do not necessarily represent the views of the DOE or the U.S. Government. The U.S. Government retains and the publisher, by accepting the article for publication, acknowledges that the U.S. Government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this work, or allow others to do so, for U.S. Government purposes.