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Decision Analysis Framework for the Industrial Sustainability Analysis of the Surface Finishing Industry. Cristina Piluso and Yinlun Huang Department of Chemical Engineering & Materials Science Wayne State University Detroit, MI 48202, USA. International Conference on
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Decision Analysis Framework for the Industrial Sustainability Analysis of the Surface Finishing Industry Cristina Piluso and Yinlun Huang Department of Chemical Engineering & Materials Science Wayne State University Detroit, MI 48202, USA International Conference on Sustainability Engineering and Science Auckland, New Zealand February 20-23, 2007
Outline • Need for Analysis Methodology • Ecological Input-Output Flow Analysis (EIOA) • Quantification of Environmental and Economic Sustainability Using Sustainability Metrics • Introduction of a Decision-Analysis Framework • Case Study on Zinc Plating Network Flow • Concluding Remarks
Need for Analysis Methodology • Strong interdependence among industrial entities • Efforts to satisfy triple bottom line strongly dependent on efforts of other entities • Major opportunities exist for synergistic improvements among plants • Need for general and systematic analysis methodology • Sustainable development of entity, industry, and region
Ecological Input-Output Flow Analysis (EIOA) • Mathematical core of industrial sustainability analysis • Full characterization of all direct and indirect flows that support a specific waste or product outflow • Captures big picture and detailed inter-relationships among entities in region
Ecological Input-Output Flow Analysis (EIOA) • Node – Process unit, industrial entity, etc. • Flow – Information input/output of a node (material, energy, etc.) Hi= Processing node i fij= Flow from Hjto Hi yw,0i, yp,0i = Outflow from Hi zi0 = Inflow to Hi
Ecological Input-Output Flow Analysis (EIOA) • Throughflow: Sum of all outflows from a node
EIOA Inflow Analysis • Determination of the origin of each outflow from system • Instantaneous Fractional Inflow Matrix, Q* • Calculated by dividing each element of P by throughflow of i-th row of P • An element of Q* is fraction of total flow through a nodeattributable to inflow, outflow, or internodal flow
EIOA Inflow Analysis • Transitive Closure Matrix, N* • Element of = relationship inflows have with flows to Hi • Element of = total flow through Hj needed to produce a unit of flow to Hi • Element of = amount of inflow needed to produce a unit of each outflow from Hi • Element of = total flow through Hj needed to produce a unit of each outflow from Hi • Define N* as:
EIOA Environ Analysis Traditional Environ, , (flow units/unit waste); the set of flows necessary to produce a unit of outflow Actual Environ, , (flow units); the actual flow magnitudes necessary to produce each outflow Percentage Environ, , (%); the percent of a given flow used to produce each outflow
Quantification of Sustainability Using Metrics • EIOA provides information to: • Trace industrial waste and product streams back to their origins • Determine which flows the output is most dependent on • How to quantify sustainability?
Quantification of Sustainability Using Metrics • Environmental Sustainability Metric[1] • Mass Intensity = Total Mass In / Mass of Product Sold • The smaller the better • Economic Sustainability Metric[2] • Gross Profit = Net Sales – COGS • The larger the better [1] AIChE Center for Waste Reduction Technologies (CWRT). Collaborative Projects – Focus Area: Sustainable Development, AIChE: New York, 2000 [2] IChemE. The Sustainability Metrics – Sustainable Development Progress Metrics Recommended for use in the Process Industries, IChemE: Rugby, UK, 2002
Introduction of a Decision-Analysis Framework • Second layer of analysis needed to provide meaningful sustainability decision-analysis abilities • The decision-analysis framework: • Evaluates current state of industrial sustainability • Aids in making systematic and strategic decisions
Decision-Analysis Framework – Environmental Sustainability Analysis
Decision-Analysis Framework – Economic Sustainability Analysis
Case Study on Zinc Plating Network Flow Suppliers (Chemicals) Tier I Manufacturing (Metal Plating) OEM Manufacturing (Automotive Assembly) H3 H5 H1 (Plating Shop # 1) (Automotive OEM # 1) (Chemical Supplier # 1) Product H4 H6 H2 (Plating Shop # 2) (Chemical Supplier # 2) (Automotive OEM # 2) Waste
Environmental Economic System Type Mass Intensity Gross Profit Chemical Supplier #1 1.075 $14,062 1.136 $3,514 Chemical Supplier #2 1.167 Plating Shop #1 $160,508 1.183 $18,315 Plating Shop #2 1.053 $109,783 Automotive OEM #1 Automotive OEM #2 1.031 $-1,922 1.307 $306,429 Overall System Zinc Plating Network Flow Case Study
Zinc Plating Network Flow Case Study - Results • Plating shop #1 waste generation is most dependent on: • Internal reuse (11.4%) • Raw material from both suppliers (11.4%) • Recycle from OEM #1 (11.4%) • Raw zinc to supplier #1 from environment (10.6%)
Zinc Plating Network Flow Case Study - Results • Suggested Network Modifications: • To reduce amount of waste generated by plating shop #1 • Increase the recycle from OEM #1 • Increase internal reuse • Similar analysis can be performed for remaining waste streams
Zinc Plating Network Flow Case Study - Results Environmental Economic Mass Intensity Gross Profit System Type w/o mod. w/ mod. % change w/o mod. w/ mod. % change Chemical Supplier #1 1.053 2.05 $14,062 $15,642 10.10 1.075 Chemical Supplier #2 1.087 4.31 $3,514 $4,742 25.90 1.136 Plating Shop #1 1.158 0.77 $160,508 $226,975 29.28 1.167 Plating Shop #2 1.211 -2.37 $18,315 $26,656 31.29 1.183 Automotive OEM #1 1.042 1.04 $109,783 $108,421 -1.26 1.053 Automotive OEM #2 1.031 0.00 $-1,922 $-3,656 -47.43 1.031 Overall System 1.199 8.26 $306,429 $387,236 20.20 1.307
Concluding Remarks • Through Percentage Environs we can: • Trace industrial waste and product streams back to their origins • Determine which flows the output is most dependent on • Combination of EIOA, sustainability metrics, and decision-analysis framework: • Identifies changes to be made to realize improved state of environmental and economic sustainability
Acknowledgments • National Science Foundation – DMI 0225844, and DGE 9987598 • Wayne State University – Institute of Manufacturing Research