A Framework for Environmental Performance Evaluation in Green Supply Chains Gabriel Alves Jr.

Summary Motivation Objectives Proposal Case Study Links References

Objectives Provide a Framework for EPE in GSCs –Component-based Models, Metrics, Tools Single model for EPE and Performance Evaluation –Products Flow –Dynamics of LCA Compare Environment, Performance and Costs trade-offs

Introduction Exergy –Energetic Efficiency (depends on the source and the system) –Allows comparing different energy sources Global Warming Potential (GWP) –Allows comparing different resources with the CO 2 environment impacts –Covers the destination and origin of resources

Evaluation of sustainability and performance metrics in supply chains with SRNs Proposal Models Tools Metrics Framework

Environment Performance Indicators (EPI) Classification Proposal Sustainability Indicator Objective Subjective Objective Subjective Objective Subjective Environmental Economic Social Objective

Proposal Metrics –Graphical Schema –Exergy Energy Consumption –GWP Waste Energy consumption separately

Proposal Metrics (Performance) –Resources Utilization/Availability; –Stock Availability; –Pending orders; –Replenishment policies impacts; –Machine/trucks failure impacts;

Proposal Metrics (EPE) –Absolute/relative electricity consumption (kWh); –Absolute/relative fuel consumption classified by type (diesel, gas, ethanol…) (l, m 3 …); –Absolute/relative exergy consumption (J);

Proposal Metrics (EPE) –Absolute/relative waste classified by type (paper, ferrous, wood, organic…) and destination (composting, recycling, disposal); –Absolute/relative amount of CO2 emissions in transportation and manufacturing activities; –Absolute/relative amount of CO2eq (GWP) emissions.

Proposal Producer Intermediary Transport Final Consumer Models Components –Inbound, Outbound (Pull/Push) and Reverse –Manufacturing (Desrochers)

Models x Environment Parameters Proposal Element InputsOutputs Waste, CO 2 Resources, Energy Waste, CO 2 Resources, Energy WasteResources, Energy Waste, CO 2 Resources, Energy

Failures Proposal Al-JaarProposal

Case Study Model –Scenario 1: no failures Rates: tp_PRC_0= tp_PRC_1= tp_PRC_2=

Case Study Model –Scenario 3: failures and; ∞ team Rates: tMTTR_FLTR_0= tMTTR_FLTR_1= tMTTR_FLTR_2= tMTBF_FLTR_0=223.0 tMTBF_FLTR_1=45.84 tMTBF_FLTR_2= Guards tp_PRC_0=#pOk_FLTR_0>0tMTBF_FLTR_0=[tp_PRC_0> tp_PRC_1=#pOk_FLTR_1>0tMTBF_FLTR_0=[tp_PRC_1> tp_PRC_2=#pOk_FLTR_2>0tMTBF_FLTR_0=[tp_PRC_2> Weight T0= T1=0.0989

Case Study Model –Scenario 2: failures and; 1 team Guards tRepair_FLTR_0=tRepair_FLTR_1=tRepair_FLTR_2: #pRepair_FLTR_0+#pRepair_FLTR_1+#pRepair_FLTR_2<1

Production Line Indicators Case Study

Production Line Indicators Case Study

Production Line Indicators Case Study

Production Line Indicators Case Study

Production Line Indicators Case Study *Considered same machines efficiency independent of the fuel Variation (%) Same Efficiency (Brazil) Same Efficiency (Europe) Estimated Efficiency (Brazil) Estimated Efficiency (Europe) GWP Variation with Single Energy Source

Production Line Indicators Case Study GWP Using Natural Gas and Varying Exergy Output and Exergetic Efficiency Xout variation (%) η II variation (%) GWP (kgCO 2 eq)

Links Intergovernamental Panel on Climate Change (IPCC): United States Environmental Protection Agency (EPA): – Energy Information Administration (EIA, US): Department for Environment, Food and Rural Affairs (DEFRA, UK): Carbon Trust, UK: Ministério de Minas e Energia (MME, BR): Ministério de Ciência e Tecnologia (MCT, BR): World Energy Council: Green Peace: –

References D. Simchi-Levi, P. Kaminsky, and E. Simchi-Levi, Designing and managing the supply chain: concepts, strategies and case studies. McGraw-Hill, “Environmental Protection Agency – EPA”, 2007, last access 10/jan/2009. [Online]. Available: WEC, 2007 Survey of Energy Resources. World Energy Council, Ministério de Minas e Energia, “Resenha Energética Brasileira – Exercício de 2007”, Ministério de Minas e Energia, “Balanço Energético Nacional – Exercício de 2007”, Empresa de Pesquisa Energética, last access 14/mar/2009. [Online]. Available: DEFRA - Department for Environment, Food and Rural Affairs, “Environmental Key Performance Indicators – Reporting Guidelines for UK Business”, V. Veleva, M. Hart, T. Greiner, and C. Crumbley, “Indicators of sustainable production,” Journal of Cleaner Production, vol. 9, no. 5, pp. 447 – 452, B. M. Beamon, “Designing the green supply chain,” Logistics Information Management, vol. 12, no. 4, pp. 332–342, R. Cash and T. Wilkerson, “GreenSCOR: Developing a Green Supply Chain Analytical Tool,” 2003, LMI - Logistics Management Institute. J. Cascio, The Iso Handbook. ASQ Quality Press, IPCC, Climate Change 2001: The Scientific Basis. Cambridge University Press, IPCC, 2006 IPCC Guidelines for National Greenhouse Gas Inventories. Available: G. Bolch, S. Greiner, H. de Meer, and K. S. Trivedi, Queueing Networks and Markov Chains: Modeling and Performance Evaluation with Computer Science Applications, 2nd ed. New York, NY, USA: John Wiley and Sons, G. Balbo, “Introduction to Stochastic Petri Nets,” LNCS 2090, pp. 84–155, M. A. Marsan, G. Balbo, G. Conte, S. Donatelli, and G. Franceschinis, Modelling with Generalized Stochastic Petri Nets. John Wiley and Sons, A. Zimmermann and M. Knoke, TimeNET 4.0 User Manual, 2007, ∼ timenet. A. A. Desrochers and R. Y. Al-Jaar, Applications of Petri Nets in Manufacturing Systems: Modeling, Control, and Performance Analysis. Institute of Electrical & Electronics Enginee, N. Viswanadham and N. R. S. Raghavan, “Performance analysis and design of supply chains: a Petri net approach,” Journal of Operations Research Society, pp. 1158–1169, 2000.