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QUALITY TOOLS AND TECHNIQUES PROJECT
TO ATTAIN CUSTOMER SATISFACTION, IMPROVE THE CREASE STIFNESS OF CIGARETTE HINGLED (HLs)
Page 1
Nazish Laraib
Page 2
TABLE OF CONTENTS
SIX SIGMA TOOLS
Define phase Project charter Deployment Map SIPOC Diagram KPIV’s KPOV’s Measure Phase Cause & Effect Diagram Sigma Level Box & Whisker Plot Process Capability Measurement System Analysis Testing Hypothesis Design Experiment Failure Mode and Effect Analysis
SIX SIGMA TOOLS FOR THE PROCESS OF FLAT CARTON CREASE STIFFNESS VALUES
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CREASE STIFFNESS: Crease stiffness is a part of Flat cartons unit’s product called Cigarette Hingled (HLs) used to store cigarettes, it is measured by sensor/transducer equipment by sensing crease bending force. There are many ups of die for paper creasing here they tested only 6 to 7 creases, Stiffness causes runnability problem on customer end. Lemanic Machine produces this problem chronically. After passing six different unit of printing, embossing, cutting and creasing units. It produce crease stiffness problem at C&C unit due to paper quality, die setting and humidity factors.
DIE SETTING: They have three plates for different HL’s product requirements counter plates, alternate counter plates and cito. Channel makes crease’s depth and grave, it also includes cutting and die ballades. A normal die setting can produce 25 million average HL’s. They manually adjust the die as per instructions. Die Crease pressure, machine speed, sheet displacement contributing elements of producing problem. According to operator, machine can produce 500 HL’s per minute.
BOARD TYPE: Usually they use three types of board but for HL’s right now they are using white coated bleech paper. Board Grammage and thickness affects paper stiffness.
DEFINE PHASE
PROJECT CHARTER DEPLOYMENT MAP SIPOC DIAGRAM KPIV’S & KPOV’S
PROJECT CHARTER
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Project Title:
To attain customer satisfaction, improve the crease stiffness of cigarette cartons, HL’s.
Business Case
Folding Carton line of Packages’ company produces Cigarette HL’s through rotogravure process by Lemanic and Riviera machines. It is being observed that Lemanic Machine produces beyond specification products that results customer objection due to runnability problem. Therefore it is required by ABC customer to improve crease stiffness specification. A single HL has seven creases, from 1 to 6 these are specified 11 Ncm/m to 18 Ncm/m and only 7 th crease has 8 Ncm/m to 14 Ncm/m.
Problem Statement:
Problem arises due to the component of paper board like grammage & thickness, and moisture of the production hall. It has to be improved that process should be lie within specification to achieve desired customer satisfaction.
Days
Cre
ase
va
lue
s
30272421181512963
20
19
18
17
16
Crease Values F1-F6April
Specification ( 11- 18) Ncm/m
Days
Cre
ase
Va
lue
s
30272421181512963
19
18
17
16
15
14
Crease Values F1-F6MARCH
Specification ( 11- 18) Ncm/m
Page 5
Days
Cre
ase
va
lue
s
30272421181512963
19
18
17
16
15
Crease Values F1-F6MAY
Specification ( 11- 18) Ncm/m
It is observed that values crossed the customer’s specification limits also indicate Process is not stable.
Object
To improve crease stiffness up to 14Ncm/m to 18 Ncm/m.
Metrics:
Primary Metric:
Crease Stiffness: Measure 6 to 7 creases of Hingled (HL’s) by using equipment of sensor or transducer unit of measure is Ncm/m.
Grammage: By using grammage balance with g/m2 unit
Thickness: Moisture %=( (A-B)/A)*100 degree centigrade.
Project Scope: Business Unit Folding Carton (BU-FC).
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DEPLOYMENT PROCESS FLOW DIAGRAM
SIPOC DIAGRAM:
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Supplier Input Process Output Customer
BSPPL Century
Wheat Straw& Waste Paper
Water Temperature
Paper board Folding Carton Unit of Packages.
Operator & Machine
Paper board Ink Solvent Varnish
Printing Sheet
Embossing Unit- 7
Operator & Machine
Pressure Embossing of requires image
Creasing& Cutting U-8
Operator & Machine
Board Creasing
Pressure Blade Cutter
HL’sXYZ Company
KPI’s and KPO’s:
Pulping Process
Ink Printing
Unit 1-6
Unit 7
Embossing
Cutting & creasing process
By setting die
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KPI’s X KPO’s YBoard Grammage X1 Crease Stiffness YBoard Thickness X2Moisture %age X3Machine Speed X4Operator X5Shifts X6
MEASURE PHASE
Cause & Effect diagram Sigma Level Box Plot Process Capability Measurement System Analysis
CAUSE & EFFECT DIAGRAM
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MEASURE SIGMA LEVEL METRIC
2013 MARCH APRIL MAYTotal Production 95996397 100239720 40498500Defects 8877180 2721600 1209600Opportunities 23 23 23DPU 0.092474096 0.027150914 0.029867773DPO 2.1269042 0.624471018 0.686958776DPOM 2126904.2 624471.0181 686958.7763
Sigma Level 0 1 1.1
Flat carton(Lemanic) required improvement to reduce product variation and cost.
BOX WHISKER’S PLOT
Cre
ase
Ranges
ShiftsY2Y1
321321
19
18
17
16
15
14
13
12
Shifts123
15.59
16.1616.085
12.955
13.64
13.21
Boxplot of Y1, Y2 vs Shifts
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Remarks: For crease values F1 to F6 shifts 3 controlled die setting accurately as compare to others. (Considered only Y1)
Cre
ase
Values
OperatorY2Y1
ZahidJawadIsrarZahidJawadIsrar
19
18
17
16
15
14
13
12
OperatorIsrarJawadZahid
16.25
15.84516.1
13.30513.413.16
Boxplot of Y1, Y2 vs Operator
Remark: Jawad and performs consistently as compare to others operator Zahid need to improvement . (Considered only Y1)
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Remarks: Paper thickness at 283 and 288 cm affect the specification of crease values that are skewed.
Remarks: Variation is observed in values, that are less than 203 g/m squares for crease stiffness value
MACHINE SPEED (hl/ h)
45000037500030000022500015000075000
Median
Mean
340000330000320000310000300000290000
Anderson-Darling Normality Test
Variance 5635154651Skewness -1.26773Kurtosis 1.48407N 165
Minimum 53760
A-Squared
1st Quartile 258949Median 3255003rd Quartile 350350Maximum 483000
95% Confidence Interval for Mean
289330
7.40
312409
95% Confidence Interval for Median
315000 338565
95% Confidence Interval for StDev
67748 84174
P-Value < 0.005
Mean 300869StDev 75068
95% Confidence Intervals
Summary for Machine Speed
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Remarks: According to standard design speed of machine has to produce 382923 hl/hr. Average value tell that the speed is 300669 hl/hr. Even shape of the distribution is skewed.
PROCESS CAPABILITY OF CREASE STIFFNESS VALUES
F1 T0 F6
AFTER APPLYING BOX COX TRANSFORMATION:
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Page 15
Comments:
There is variation in paper crease stiffness values. Thus process is not capable according to the value of Cpk and Cp.
MEASUREMENT SYSTEM ANALYSIS
MINITAB offers several commands to help you determine how much of your process variation
arises from variation in your measurement system.May-13
Part Reference Value Crease Value
1 13 16.741 13 16.7531 13 17.6491 13 17.5251 13 19.017
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1 13 16.6471 13 18.0341 13 16.0681 13 18.2251 13 16.4372 14 16.4012 14 15.5322 14 16.8422 14 17.2162 14 16.782 14 15.6062 14 17.7522 14 15.9472 14 17.1272 14 15.1573 15 16.1953 15 15.4313 15 16.6863 15 16.263 15 18.213 15 15.6953 15 17.0363 15 16.1093 15 16.9743 15 15.2734 16 17.3814 16 16.5334 16 17.3784 16 17.9944 16 18.3444 16 16.5344 16 18.2694 16 17.064 16 18.194 16 17.2675 17 17.1165 17 15.7215 17 17.2145 17 17.475 17 17.8185 17 16.336
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5 17 18.1325 17 16.5765 17 17.8325 17 16.4616 18 18.466 18 16.0746 18 17.366 18 18.4126 18 16.9896 18 16.6856 18 19.1386 18 16.7876 18 18.3016 18 16.413
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Gage Linearity and Bias examines gage linearity and accuracy.In Gage bias section reference averages from 13 to 16 shows bias because values are less than 0.05.In Gage Linearity, slope value also less than 0.05 that shows gage is producing non linear results. (for good gage it should be linear).
GAUGE REPEATABILITY & REPRODUCIBILITY
Method for assessing repeatability and reproducibility:
One-Way ANOVA Table
Source DF SS MS F PPart 5 12.4862 2.49724 3.32420 0.011Repeatability 54 40.5664 0.75123Total 59 53.0527
Alpha to remove interaction term = 0.25
Gage R&R %Contribution Source VarComp (of VarComp)Total Gage R&R 0.751230 81.14
Repeatability 0.751230 81.14
Part-To-Part 0.174601 18.86
Total Variation 0.925832 100.00
Process tolerance = 7
Study Var %Study Var %ToleranceSource StdDev (SD) (6 * SD) (%SV) (SV/Toler)
Total Gage R&R 0.866736 5.20041 90.08 74.29
Repeatability 0.866736 5.20041 90.08 74.29
Part-To-Part 0.417853 2.50712 43.43 35.82
Total Variation 0.962201 5.77321 100.00 82.47
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%contribution Between 1% and 9% the measurement system is not acceptable and according to action group definition for gage acceptance it is considered poor.
Similarly % study variation Between 10% and 30% the measurement system is not acceptable according to action group definition for gage acceptance it is considered poor.
The percent contribution from Gage R&R ia larger than that of part to part, telling you that much of the variation is due to difference between gage R&R.
ANALYZE PHASE:
Testing Hypothesis
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Correlation & Regression Analysis
TESTING HYPOTHESIS
Crease values V’s Operator:
Comment: Less variation in Jawad performance.
Test for Equal Variances: Y versus Operator
95% Bonferroni confidence intervals for standard deviations
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Operator N Lower StDev Upper Israr 31 0.87415 1.14684 1.64223 Jawad 63 0.80205 0.97581 1.23806 Zahid 56 1.00041 1.23059 1.58710
Bartlett's Test (Normal Distribution)Test statistic = 3.18, p-value = 0.204
Levene's Test (Any Continuous Distribution)Test statistic = 0.26, p value = 0.770
One-way ANOVA: Y versus Operator
Null Hypothesis: Hο
µ(zahid)= µ(jawad) = µ(Israr)
Alternate Hypothesis: Ha
µ(zahid)≠µ(jawad)≠ µ(Israr)
One-way ANOVA: Y versus Operator
Source DF SS MS F POperator 2 1.00 0.50 0.41 0.668Error 147 181.78 1.24Total 149 182.78
S = 1.112 R-Sq = 0.55% R-Sq(adj) = 0.00%
Individual 95% CIs For Mean Based on Pooled StDevLevel N Mean StDev --+---------+---------+---------+-------Israr 31 16.701 1.147 (---------------*---------------)Jawad 63 16.505 0.976 (----------*----------)Zahid 56 16.493 1.231 (-----------*----------) --+---------+---------+---------+------- 16.25 16.50 16.75 17.00
Pooled StDev = 1.112
Inferential statistics results tell us that operators performance are almost equal because p-value is 0.668 that is greater than 0.05.
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Here histogram makes a bell shape curve pattern and residual follow a straight line thus normality assumption fulfilled.
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Test for Equal Variances: Y versus SHIFT
95% Bonferroni confidence intervals for standard deviations
SHIFT N Lower StDev UpperShift1 52 0.79187 0.98111 1.27930Shift2 55 1.00179 1.23441 1.59621Shift3 43 0.86764 1.09622 1.47390
Bartlett's Test (Normal Distribution)Test statistic = 2.73, p-value = 0.255
Levene's Test (Any Continuous Distribution)Test statistic = 0.53, p-value = 0.589
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One-way ANOVA: Y versus SHIFT
In Shift analysis, histogram makes a bell shape curve pattern and residual follow a straight line thus normality assumption fulfilled.
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Null Hypothesis: Hο
µ(shift 1)= µ(shift 2) = µ(shift 2)
Alternate Hypothesis: Ha
µ(shift 1)≠µ(shift 2)≠ µ(shift 2)
One-way ANOVA: Y versus SHIFT
Source DF SS MS F PSHIFT 2 0.94 0.47 0.38 0.685Error 147 181.85 1.24Total 149 182.78
S = 1.112 R-Sq = 0.51% R-Sq(adj) = 0.00%
Individual 95% CIs For Mean Based on Pooled StDevLevel N Mean StDev -------+---------+---------+---------+--Shift1 52 16.590 0.981 (------------*-----------)Shift2 55 16.592 1.234 (-----------*-----------)Shift3 43 16.417 1.096 (-------------*------------) -------+---------+---------+---------+-- 16.25 16.50 16.75 17.00
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Pooled StDev = 1.112
Accept Null hypothesis There isn’t any difference between shifts.
REGRESSION ANALYSIS
To find out the relationship between variables we apply multiple regression analysis technique and observe that which variable part huge effect on response value.
Y = Response variable (dependent variable) – crease value
X1 =Independent variable – Moisture
X2 = Board Grammage
X3 = Paper thickness
Regression Analysis: Y versus Moisture, Board Grammage, Paper Thickness1
The regression equation isY = 35.3 - 0.533 Moisture - 0.0564 Board Grammage - 0.0135 Paper Thickness1
Predictor Coef SE Coef T PConstant 35.324 7.073 4.99 0.000Moisture -0.5331 0.5400 -0.99 0.325Board Grammage -0.05635 0.02503 -2.25 0.026Paper Thickness1 -0.01345 0.01468 -0.92 0.361
S = 1.09139 R-Sq = 4.9% R-Sq(adj) = 2.9%
Analysis of Variance
Source DF SS MS F PRegression 3 8.881 2.960 2.49 0.063Residual Error 146 173.904 1.191Total 149 182.784
Source DF Seq SSMoisture 1 1.553Board Grammage 1 6.327Paper Thickness1 1 1.001
Unusual Observations
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Obs Moisture Y Fit SE Fit Residual St Resid 28 6.25 18.6800 16.3965 0.1094 2.2835 2.10R 55 6.10 19.5800 16.9273 0.1781 2.6527 2.46R 56 6.14 19.5800 16.9060 0.1707 2.6740 2.48R 58 6.40 19.0700 16.7674 0.1870 2.3026 2.14R 75 6.32 16.9000 16.9300 0.8389 -0.0300 -0.04 X 84 6.21 14.7200 16.9359 0.1773 -2.2159 -2.06R 95 5.70 16.2700 16.5072 0.3384 -0.2372 -0.23 X100 5.70 16.6400 16.8697 0.3089 -0.2297 -0.22 X102 6.06 18.8100 16.4094 0.2131 2.4006 2.24R103 5.68 16.6400 16.8265 0.3145 -0.1865 -0.18 X105 5.65 15.0100 16.8745 0.3445 -1.8645 -1.80 X120 6.79 15.5800 16.0145 0.3221 -0.4345 -0.42 X134 6.31 13.2400 16.0744 0.2050 -2.8344 -2.64R141 6.40 13.6100 16.2762 0.1413 -2.6662 -2.46R
R denotes an observation with a large standardized residual.X denotes an observation whose X value gives it large leverage.
Regression equation shows that there is relation between board grammage and crease value.
Thus board grammage affects crease value.
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IMPROVE PHASE:
Design of Experiment.
Failure Mode and Effect Analysis
DESIGN OF EXPERIMENT
DOE tell us that which input(variable) has effect on the crease values
Factors: Factors setting values.
Levels
1. Board Grammage: 204, 210 gram2. Paper Thickness: 285, 2913. Moisture: 6%-7%
Replicate=3
Response: Crease value
Full Factorial Design
Factors: 3 Base Design: 3, 8Runs: 24 Replicates: 3Blocks: 1 Center pts (total): 0
Generated data in minitab:
StdOrder
RunOrder
CenterPt
Blocks
Board Grammag
e
Paper Thicknes
sMoistur
e
Crease
value10 1 1 1 210 284 6 17.0018 2 1 1 210 284 6 17.4511 3 1 1 204 291 6 16.45
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4 4 1 1 210 291 6 15.5423 5 1 1 204 291 7 17.45
7 6 1 1 204 291 7 15.8721 7 1 1 204 284 7 18.0020 8 1 1 210 291 6 16.0014 9 1 1 210 284 7 15.0012 10 1 1 210 291 6 14.54
8 11 1 1 210 291 7 14.003 12 1 1 204 291 6 16.005 13 1 1 204 284 7 18.002 14 1 1 210 284 6 16.21
24 15 1 1 210 291 7 15.0019 16 1 1 204 291 6 14.2513 17 1 1 204 284 7 15.35
6 18 1 1 210 284 7 17.9517 19 1 1 204 284 6 16.00
1 20 1 1 204 284 6 15.0015 21 1 1 204 291 7 18.0022 22 1 1 210 284 7 15.0016 23 1 1 210 291 7 15.00
9 24 1 1 204 284 6 14.33
Factorial Fit: Crease value versus Board Gramma, Paper Thickness,Moisture
Estimated Effects and Coefficients for Crease value (coded units)
Term Effect Coef SE Coef T P
Constant 15.9746 0.2260 70.69 0.000
Board Grammage -0.5008 -0.2504 0.2260 -1.11 0.284
Paper Thickness -0.5992 -0.2996 0.2260 -1.33 0.204
Moisture 0.4875 0.2438 0.2260 1.08 0.297
Board Grammage*Paper Thickness -0.8225 -0.4113 0.2260 -1.82 0.088
Board Grammage*Moisture -1.2858 -0.6429 0.2260 -2.84 0.012
Paper Thickness*Moisture -0.0642 -0.0321 0.2260 -0.14 0.889
Board Grammage*Paper Thickness* 0.1692 0.0846 0.2260 0.37 0.713 Moisture
S = 1.10714 PRESS = 44.127 R-Sq = 49.55% R-Sq(pred) = 0.00% R-Sq(adj) = 27.48%
Page 30
It is being observed that paper grammage and moisture have impact on crease value of HLs
Main effect plot for crease value
Paper grammage and thickness have negative relation with crease value as both values increases crease values decreases. While moisture value increase crease value also increases.
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Interaction plot for crease value
Main effect plot for crease values shows interaction between paper grammage &paper thickness and Board grammage and moisture on the other side paper thickness and moisture are independent.
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Pareto chart shows that the main effect on the curl values is being caused by Paper grammage and moisture combination
.
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FALIURE MODE AND EFFECT ANALYSIS
Please adjust the excel layout.
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References:
Packages Limited company (Quality control department)
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