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Resource efficiency benchmarking of the Russia Ferrous Foundry Industry:
Key findings of the studyImplemented under IFC Russia Cleaner Production Program
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GOAL: to identify the ferrous foundry sector resource efficiency potential and develop practical tools for foundries to implement it
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Benchmarking study time line*
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Stakeholder consultations at every important stage:MethodologyQuestionnaire for data collectionSelf diagnostic guideMatrix of casting types
Advisory board included over 20 representatives from industry, R&D, officials and policy makers.
Consultation processWritten comments on all key documentsMeetings of Advisory board Workshops in smaller teams*What made our study successful : Stakeholder consultations process
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7 Key performance indicators (KPIs)What is being benchmarked? *
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7 KPIs methodology tailored to foundry processSelected KPIs and methodology tailored to foundry processes*
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*32 category matrix developed to cover diversity of foundry productionGrey Iron Product Categoriesautomatic mouldingGABH= automotive engine blocks and cylinder headsGAAO = automotive otherGAAG = agricultureGAMI = mining
mechanized mouldingGMBH = medium size engine blocks and heads (energy generation)GMAG = agricultureGMMI = miningGMGE = general engineering
manual (hand) mouldingGHBH = large size engine blocks and heads (energy generation)GHMI = miningGHGE = general engineering
Ductile Iron Product CategoriesSteel Product Categoriesautomatic mouldingDAAU = automotive otherDAGE = general engineering
mechanized mouldingDMAU= automotiveDMGE = general engineering
manual (hand) mouldingDHEN = energy generation componentsDHCO = compressor componentsDHGE = general engineering
automatic mouldingSARC = railway components (c)SAMM = mining components (m)SAAC = commercial vehicles (c)SAGC = general engineering (c)
mechanized mouldingSMRC = railway components (c) SMMM = mining components (m)SMPC = pumps & valves (c)SMPS = pumps & valves (s)SMGC = general engineering (c) SMAC = commercial vehicles (c)
manual (hand) mouldingSHMM = mining components (m) SHPC = pumps & valves (c)SHEA = energy components (a)SHGC = general engineering (c)
c: carbon steel, s: stainless steel, m: manganese; a: high alloy steel
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215 foundries(first long list; 25% of all legally registered ferrous foundries in Russia)
55 sets of independent data for foundriesStudy based on real data from enterprises*Coverage :Period : 3 years (2007-2009)Total # of data sets: 150Categories covered: 27 out of 32 (85%) Industry: 478 kt (14% of market)
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*KEY FINDINGS OF THE STUDY
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Russian foundryEuropean foundry Russia foundries significantly lag behind EuropeanRussian ferrous foundry us per tone of good casting:Energy: 3 times moreSand: 3,6 times moreWater: 161 times moreLabor : 3,6 times more man-hours*4.5 mln t CO2e
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Costs:EURussiaRussia at EU efficiency level -36% Inefficiencies eliminate Russian foundries competitive advantage in low prices Prices for major resources in Russia are less than in the EU:
Energy: 54% lessLabor: 92% lessOverheads: 71% less*
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1000
960
6436
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96 %
64 %
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100012
96016
643648
071
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4 times Average defect rate in Russia is 4 times higher than in EU Effect export: Russia exports less than 1% of casting Low quality threat for internal markets as customers require certain quality (eg. automotive producers)High levels of defect rate*EURussia
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0.034
0.134
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3.4%0.0%2
13.4%6.7%3
Category 44.52.85
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- 26% Cost structure index for ferrous foundry (materials, labor, energy, equipment maintenance, overheads, water and sand)How much can Russia ferrous foundry industry gain via resource efficiency?$ 3.3 bln USD$2.13 bln USD $ 3 bln USD- 29% *
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8119
7426
7129
-19%
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100 %
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Series 1Series 2Series 3
Russia average10000
Russia best81190
Europe average74260
Europe best7129
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- 43% Low cost and management practicesCapital investmentOver 50% of the potential can be implemented via low-cost measures and management practices $3.3 bln USD Costs*
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71290
83.516.50
7112.50
071Europe best
- 57%
Series 1
Series 2
Series 3
71 %
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Series 1Series 2Series 3
Russia average71290
83.516.50
7112.50
Europe best071
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16.5
12.5
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Capital investmentLow cost and management practicesKPIs and resource efficiency potential:*
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0.680.32
0.70.3
0.70.3
0.750.25
0.50.5
0.250.75
0.250.75
Low cost and management
Capital investment
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Low cost and managementCapital investmentSeries 3
Yeild68%32%2
Production efficiency70%30%2
Capacity utilisation70%30%3
Labor75%25%5
Water50%50%
Energy25%75%
Sand25%75%
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Materials (metal)EnergyLaborEquipment relatedOverheads4,2%43,3%9,4%4,4%9,7%$ 3.3 bln USD12,8%7,1%21,4%13,4%45,2%-3.1%-2.7%-12%-9.2%-1.9%Benchmarking of KPIs is a tool to priorities interventions to achieve maximum impactRussia average levelLevel of best practicesCost structure*
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45.213.421.47.112.80
000
000
43.34.29.44.49.729
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Series 1Series 2Series 3Series 4Series 5Series 6
45.213.421.47.112.80
000
000
43.34.29.44.49.729
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*Next steps:
Toolkit: Self diagnostic guide, Compendium of KPIs, Best practice guide, Benchmarking study reportPilot program with 5-7 companies with foundriesResource efficiency finance directly and via FIs
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Information available in public domainhttp://www.ifc.org/ifcext/eca.nsf/Content/Russia_Foundry_Russian*http://www.ifc.org/rcpp
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IFC contactsIFC Russia Cleaner Production (IFC RCPP) Yana Gorbatenko, Program [email protected]
Study team IFC RCPP: Kristina Turilova, Task leader [email protected] Boris Nekrasov, Technical expert [email protected] Maria Sigutina, PR and [email protected]
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***Quantity of data: We aim for having a data base of some 25 companies. We will extend the period of data collection until end of March as a still considerable number of companies announced to deliver. Up to now we have received probably half of the responses12 companies have returned a questionnaire filled inthe returned questionnaires provide data for 18 foundries as some of the companies have more than one foundryalmost all of the responses include data for the performance for three years (2007-2008-2009) so together including the average result over the 3 years we have some 70 sets of foundry data. We are positive that another 10-15 companies will provide another 80-100 sets of performance data with similar quality until we close the data collect period.
