Download - Green Belt Project V2
Hydro Cost Model – Turbine Equations Six Sigma Green Belt Project
Project ID – A112502.2Jonathan Shriqui
February 2007
2 Six Sigma Green Belt Project - Hydro Cost ModelJonathan Shriqui
D M A CI
PROBLEM STATEMENTNo set parameters for estimating turbine partsHistorical data fluctuation (FX rates, steel, copper) do not represent future fluctuationsNon standard part composition (make VS buy, SS vs non SS)
PROJECT GOALIdentify and establish set parameters for accurate cost estimation for turbine parts, other then the runner, based on GSC parameters (labor, eng, supply) and economic factors (FX rates, steel index, copper index)
BUSINESS CASESupporting MFG Finance in establishing an automated cost model
DELIVERABLESDefine statistical cost equations for turbine scope, runner excluded.
PROJECT SCOPENew TurbinesBOUNDERIESIN: Turbine scope onlyOUT: PBS 140 – RunnerCONSTRAINTSEach part is custom to a projectSame parts/PBS can have different material composition depending on the projectSome parts/PBS are combined on smaller units
TIMELINEThe goal is to have establish mathematical equations for the main turbine PBS with in a 4 months period.
RESSOURCES
Engineer: Vicent FrancouBlack Belt: Maya El-Rayes & Beverlie TaylorChampion: Serge BélangerSupport: Carl Larochelle
Mario Pelletier
Project Charter
3 Six Sigma Green Belt Project - Hydro Cost ModelJonathan Shriqui
D M A CI
Current Process Map
CustomerITO Cost Estimator
OutputCost of
component
ProcessModification of reference parameters
to meet new project parameters
InputsParameters
from previous projects
SupplierEngineering
High Level Process Map
4 Six Sigma Green Belt Project - Hydro Cost ModelJonathan Shriqui
D M A CI
• Cost estimations are based on reference projects, where the data and technology used at that time may now be outdated• Highly manual process, no standardization• Requires high product knowledge• No standard template for estimators• Limited relevant historical data
“As Is” Process Weakness
5 Six Sigma Green Belt Project - Hydro Cost ModelJonathan Shriqui
D M A I CDefine Performance Standards
What is a defect:Budget variation from Actual cost greater then 5%
What is being measured?Actual cost vs budget
Performance Standard and Specification Limit
•Type of Data: Discrete•Opportunity: All turbine components (runner excluded) •Defect Definition:
Acceptable%5costBudget
costBudget -cost Actual
DEFECT%5costBudget
costBudget -cost Actual
6 Six Sigma Green Belt Project - Hydro Cost ModelJonathan Shriqui
Current Status Actual Cost vs Budget
0
2
4
6
8
10
-10 0 10 20 30 40 50 60 70 80 90
% Deviation from EAC
Freq
uenc
y
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Frequency
Cumulative %
D M A CI
Observed: 593’750 DPMO
Target 90% Defect Reduction
Process Data
USL 5.00%Target 0LSL *Median 10.83%P5 -4.84%P95 69.58%Span (P95-P5) 74.42%Q1 1.49%Q3 25.42%Stability Factor 0.0585
Non Normal Data
Current Status
7 Six Sigma Green Belt Project - Hydro Cost ModelJonathan Shriqui
DELIVERABLEMathematical equation (transfer function) based on measurable parameter(s) delivering an accurate estimation with a 95% confidence level.
Y=F(X) where R2 < 95%
D M A CIDeliverable Definition
8 Six Sigma Green Belt Project - Hydro Cost ModelJonathan Shriqui
Performance Objectives D M A CI
Y=F(X) where R2 > 95%
Target:
To reduce all cost estimation defects, where the variation between actuals & budget would +\- 5%.
Business CTQ: Accuracy
Performance Std: Forecast a cost within 5% of its actual cost
9 Six Sigma Green Belt Project - Hydro Cost ModelJonathan Shriqui
Baseline Z D M A CI
Zone of AverageTechnology
Zone ofTypicalControl
0.0
0.5
1.0
1.5
2.0
2.5
3.0
0 1 2 3 4 5 6
Z.Shift
Z.Bench (Short-Term)
World-ClassPerformance
Report 8B: Product Benchmarks
1
10
100
1000
10000
100000
1000000
0 1 2 3 4 5 6
Z.Bench (Short-Term)
PPMReport 8A: Product Benchmarks
Z(bench) = 1.2 (593’750 DPMO)
* Product Report – Discreet Data
10 Six Sigma Green Belt Project - Hydro Cost ModelJonathan Shriqui
Sources of Variation
Actual > Budget
No automated technical input Manual Data input
Re Work Process Use of Reference project cost
EASY
OTR-ITO feedback loop non completed
Detail PBS level Cost
Data is not maintained
Incomplete Data
Suspect Data
Makes the Data subject to interpretation
No direct data feed from ENG
Multiple products Separate systems depending on product
Current Engineering practices
Need to interpret manual descriptions
Difficult to get all historical costs on time
Historical data not inflated correctly
Excel sheet reports that can be manually modified
No Standard Process
Dependent on Technical knowledge of the CE
Historical estimates don’t contain all the information
Not costs are available
OTR costs are input under incorrect PBS
Historical costs are lump summed
Evolution of technology
EASY
IMPACT
EFFO
RT 1 3
2 4
BIG LITTLE
HA
RD
1
1
1
12
22
2
2
222
3
3
34
4
4
3
3
Historical data doesn’t account for FX Impact 1
D M A CI
11 Six Sigma Green Belt Project - Hydro Cost ModelJonathan Shriqui
Proposed Solutions
Description of Vital X’s Proposed Solution
1 Cost obtained via project parameters
Identification of necessary technical parameters for costing.
2 Structured database for historical information
Creation of historical database
3 Budget obtained via project parameters
Creation of equation to forecast cost based on technical parameters.
D M A CI
12 Six Sigma Green Belt Project - Hydro Cost ModelJonathan Shriqui
Identification of necessary technical parameters for costing.
•Weekly brainstorming with engineers•Review of all reference projects•Agreement on technical parameters•Efficient use of PEGASUS
# Parameter Description PBS UOM1 HT-Spir_Case_press_max_mom Maximum momentary spiral casing pressure High level characteristics MPA2 HT_Runner_Throat_Dia Runner Throat Diameter High level characteristics mm3 HT_GV_circle_Dia Guide Vane Circle Diameter High level characteristics mm4 HYDT_GV_qty Guide Vanes number of vanes High level characteristics5 HYDT_Dist_height Distributor Height High level characteristics mm6 HYDT_DT_found_anch_weight Draft Tube Foundation Anchors Weight 8110 - Foundation Parts Kg7 HYDT_SC_found_anch_weight Spiral Case Foundation Anchors Weight 8110 - Foundation Parts Kg8 HYDT_PN_weight_DT Pier nose weight for draft tube 8110 - Foundation Parts Kg9 HYDT_DTCL_weight_MS Draft Tube Cone Liner Weight (Mild Steel) 8120 - Draft Tube Kg10 HYDT_DTEL_wt_MS Draft Tube Elbow Liner Weight (Mild Steel) 8120 - Draft Tube Kg11 HYDT_DT_ext_Weight Draft Tube Elbow Liner extention Weight (Mild Steel) 8120 - Draft Tube Kg12 HYDT_DTCL_weight_SS Draft Tube Cone Liner Weight (Stainless Steel) 8120 - Draft Tube Kg13 HYDT_DR_MS_weight Discharge Ring mild steel Weight 8130 - Discharge Ring Kg14 HYDT_DR_sS_weight Discharge Ring stainless steel Weight 8130 - Discharge Ring Kg15 HYDT_SC_weight Spiral Case Weight 8140 - Spiral Casing Kg16 HYDT_SR_weight Stay Ring Total Weight 8140 - Spiral Casing Kg17 HYDT_Pit_Liner_weight Pit Liner Weight 8150 - Liners Kg18 HYDT_LowPit_liner_weight Lower Pit Liner Weight 8150 - Liners Kg19 HYDT_BR_Weight_rad Bottom Ring Total Weight 8210 - Covers and Ring Gate Kg
D M A CI
13 Six Sigma Green Belt Project - Hydro Cost ModelJonathan Shriqui
Creation of historical database• Gather all cost & technical data
• Apply Inflation, escalation & FX
• Review Outliers
ProjectName ContractNumber 2006 Cost (USD)
2007 Cost (USD/Kg)
EngineeringNumber
of section
Weight (Kg)
# of WG WGCD (mm)
Design Pressure
(Mpa)
H distributor
(mm)PD3 Supplier Year
ERTAN 0222961205 1,089,628$ 7.07 0 4 154100 20 6993 2.31 1462.5 790.0 n/a 1995SANXIA 0222962201 3,235,358$ 8.47 2234 6 382000 23 11139 1.373 2832 1897.6 n/a 1999-2001SEVEN MILE 0222061501 469,074$ 5.83 1160.3 4 80430 19 7500 0.9 2013 379.7 Groupe LAR 2002SM3 0222062101 870,207$ 12.89 914.5 2 67500 19 5000 4.1 639 512.5 Québec 1998TOULNUSTOUC 0222078701 215,895$ 6.05 1327.9 1 35670 19 4882 2.22 871.875 258.3 Fabspec 2002VATNSFELL 0222972301 47,552$ 3.99 79 2 11922 20 3650 0.9 762.5 43.8 China 1999BRISAY 0226008501 2,193,951$ 9.66 1112.3 4 227000 23 10320 0.785 3010 862.8 n/a 1991
D M A CI
14 Six Sigma Green Belt Project - Hydro Cost ModelJonathan Shriqui
Creation of equation to forecast cost based on technical parameters.
• Apply statistical tools
• Obtaining cost predicting equations
• Validate with commodity leaders
D M A CI
Equation 1 ($) COST = -37656+4.0132W+1.6434PD³
Projects Projects Cost Weight Pressure Throat D PD³ERTAN ERTAN Average 1,819,935.00 279,000 2.31 5,850 462,466SEVEN MILE SEVEN MILE Average 1,437,152.86 259,100 0.90 6,250 219,727SM3 SM3 Average 871,301.72 125,000 4.10 3,600 191,290TOULNUSTOUC TOULNUSTOUC Average 586,158.76 104,650 2.22 3,875 129,172VATNSFELL VATNSFELL Average 90,248.40 27,895 0.90 3,050 25,535BRISAY BRISAY Average 2,763,443.57 503,000 0.79 8,600 499,304GRANITE CANAL GRANITE CANAL Average 171,532.61 53,000 0.56 4,200 41,786
15 Six Sigma Green Belt Project - Hydro Cost ModelJonathan Shriqui
Equation Back-UpBest Subsets Regression Response is Cost P Adj. T D Vars R-Sq R-Sq C-p s W P D ³ 1 98.0 97.6 24.2 149560 X 1 92.2 90.6 103.4 295938 X 2 99.6 99.4 4.3 74155 X X 2 99.4 99.0 7.7 94766 X X Regression Analysis The regression equation isCost = - 37656 + 4.01 W + 1.64 PD³ Predictor Coef StDev T PConstant -37656 45794 -0.82 0.457W 4.0132 0.4615 8.70 0.001PD³ 1.6434 0.4066 4.04 0.016 S = 74155 R-Sq = 99.6% R-Sq(adj) = 99.4% Analysis of Variance Source DF SS MS F PRegression 2 5.57479E+12 2.78739E+12 506.89 0.000Residual Error 4 21996100073 5499025018Total 6 5.59678E+12 Source DF Seq SSW 1 5.48494E+12PD³ 1 89845101929
D M A CI
Ho: Variable is not a significant predictor of the modelHa: Variable is a significant predictor of the model
16 Six Sigma Green Belt Project - Hydro Cost ModelJonathan Shriqui
BeforeCustomerITO Cost Estimator
OutputCost of
component
ProcessModification of reference parameters
to meet new project parameters
InputsParameters
from previous projects
SupplierEngineering
D M A CI
AfterCustomerITO Cost Estimator
OutputCost of
component
ProcessFed the technical
parameters (Inputs) into
the equation
InputsTechnical
parameters of project
SupplierEngineering
High Level Process Map
17 Six Sigma Green Belt Project - Hydro Cost ModelJonathan Shriqui
Improved Z
Zone of AverageTechnology
Zone ofTypicalControl
0.0
0.5
1.0
1.5
2.0
2.5
3.0
0 1 2 3 4 5 6
Z.Shift
Z.Bench (Short-Term)
World-ClassPerformance
Report 8B: Product Benchmarks
1
10
100
1000
10000
100000
1000000
0 1 2 3 4 5 6
Z.Bench (Short-Term)
PPMReport 8A: Product Benchmarks
New Z(bench) = 2.1 (285’714 DPMO)
D M A CI
* Product Report – Discreet Data
Old Z(bench) = 1.2 (593’750 DPMO)
18 Six Sigma Green Belt Project - Hydro Cost ModelJonathan Shriqui
Prove the Improve D M A CI
• Plot ITO data with equations• Moods Median Test • Prove that there is no statistical difference between the Calculated cost and the ITO estimations
Chi-Square = 3.20 DF = 1 P = 0.074 Individual 95.0% CIsmethod N<= N> Median Q3-Q1 -+---------+---------+---------+-----Equation 3 7 933121 534832 (-----------------------+--)ITO 7 3 742813 601846 (----------------+-------------) -+---------+---------+---------+----- 400000 600000 800000 1000000Overall median = 784147A 95.0% CI for median(Equation) - median(ITO): (-478780,577841)
P > 0.05
Spiral CaseEquation Cost VS Actual Cost
GRANITE CANAL
BRISAY
VATNSFELL
TOULNUSTOUC
SM3
SEVEN MILE
ERTAN
0
500,000
1,000,000
1,500,000
2,000,000
2,500,000
3,000,000
0 1 2 3 4 5 6 7 8
Cos
t (US
) $
Total Equation Cost Actual Cost
19 Six Sigma Green Belt Project - Hydro Cost ModelJonathan Shriqui
Control Process• Kept track of all results electronically in a centralized database• Trained the cost estimators on the database and equations• Insured hand-off knowledge to a dedicated cost modeler
D M A CI
Microsoft Word Document