|Researchers at Purdue University have developed a method using processing engineering models for physical input-output tables (PIOT) by implementing a collaborative cloud-based tool. PIOTs can determine economic outcomes depending on the flow of resources in an industry or market. Unlike current technologies including life cycle assessments (LCA) that use tiered data flow systems or time series approximations to fill data bandgaps, the new platform created by Purdue researchers allows for dynamic real-time changes in computer code while reviewing input and output. The algorithms in this bottom-up modular model help to manage resources with enhanced accuracy and reliability as data can be more easily reconciled through this approach. The goal of this technology is to assist manufactures to track the materials flow and supply chain demand to optimize the process and reduce waste, as well as assist in the decision-making process. This technology was tested using a PIOT for a chemical process in which nitrogen is converted into ammonia. In testing, the model precisely accounted for all parameters and resources essential for the process and used only one PIOT to make the analysis and fill in data gaps during run time; reducing processing time and increasing efficiency as compared to traditional techniques.
-Decision-Making for Sustainability and Resilience
"A Modular Bottom-Up Approach for Constructing Physical Input-Output Tables (PIOTs) Based on Process Engineering Models"
Journal of Economic Structures
This technology has been tested with a PIOT representing the nitrogen economy in the state of Illinois due to the demand for nitrogen in food, energy, and environmental industries. In comparison with a current PIOT model, the method created by Purdue researchers was able to achieve equal or higher confidence.
Jul 6, 2020
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