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Six Sigma projects are now a days very widely done in Advanced Innovation Group across the industry but the challenge that comes is that, projects are initiated very well but they are not lead towards successful closure due to lack of guidance. To overcome these challenges which the project leaders face, we at Advance Innovation Group have started posting huge number of Six Sigma projects on Slideshare. This project was done in a manufacturing industry to reduce the breakage while production. the leaders were concerned because during the last 8 months, rejection in biscuits due to breakage is around 297 kg against the 7064 kg of biscuits produced on monthly basis. Average of 8 months rejection breakage is around 4.25%, rejection should be around 2.0% of total biscuits processed in kgs” Reduce rejection from 4.25% to 2.0 % in sweet biscuits Due to high rejection rate of 4.25%, target of productivity is not met which is set at 98% Increase the productivity from 95.75% to 98% Goal statement of the project was to reduce rejection due to breakage in sweet biscuits at Noida location from 4.25% to 2.0% Additionally, it is advisable that you also visit and subscribe Advance Innovation Group Blog (http://advanceinnovationgroup.com/blog) for more Lean Six Sigma Projects, Case Studies on Lean Six Sigma, Lean Six Sigma Videos, Lean Six Sigma Discussions, Lean Six Sigma Jobs etc.
Citation preview
Six Sigma Black Belt Project onSix Sigma Black Belt Project onreduction in breakage in biscuits
LOCATION : NOIDAPROCESS : BISCUITS MAKINGBLACK BELT : Dipti Nayak
Understanding VOC
Customer Customer Comments Customer (CTQ's)
Champion – General Manager
“During the last 8 months, rejection in biscuits due to breakage is around 297 kg against the 7064 kg of biscuits produced on monthly basis. Average of 8 months rejection breakage is around 4.25%, rejection should be around 2.0% of total biscuits processed in kgs”
Reduce rejection from 4.25% to 2.0 % in sweet biscuits
Operations Manager “ Due to high rejection rate of 4.25%, target of productivity is not met which is set at 98%
Increase the productivity from 95.75% to 98%
Project Charterd
Define
Project Leader: Dipti Nayak
Team Members
Business Case: ABC Limited is one the leading biscuit manufacturing company with its location worldwide. Its Manufacturing facility in Noida, India is manufacturing sweet and namkeen biscuits for market leading brands, Noida unit is facing lot of rejection due to breakage in biscuits due to which the scrap /rejection has increased and needs immediate attention as it is causing loss to the A-G biscuits. Currently it is operating under 4.25% rejection against the estimated target of 2.0%. Sweet biscuits monthly production is around 7064 kg and around 297 Kg are rejected to due breakage.
Stakeholders Business Leader
Champion Vice President
Sponsor General Manager
MBB Pranay Kumar
BB Dipti Nayak
Team Member Operations Manager, supervisor, Key operators, quality executives, Engineering manager
Problem Statement: During the period from Mar’2012 to Oct’2012 the average rejection rate is 4.25% of the sweet biscuits manufactured
Goal Statement: To reduce rejection due to breakage in sweet biscuits at Noida location from 4.25% to 2.0% by Mar’2013
Project In Scope: 1. Sweet biscuits manufactured in Noida location Project Out of Scope: 1. Everything beyond as mentioned above is out of scope for this project
Timelines/Milestones/Phases Start Date End Date
Start date: 05th Nov 2012 -DEFINE 05th Nov 2012 19th Nov, 2012
MEASURE 20th Nov, 2012 30th Nov, 2012ANALYZE 03rd Dec,2012 29th Dec, 2012 IMPROVE 02nd Jan, 2013 31st Jan,2013CONTROL 01st Feb,2013 30th Apr, 2013
ARMI and Communication PlanKey Stakeholders ARMI Worksheet
Define Measure Analyze Improve Control
GM Finance, Engg I I I I ISponsor - VP I I I I I
Champion - GM I & A I & A I & A I & A I & AMBB A & I A & I A & I A & I A & I
Operation Manager I & M I & M I & M I & M I & MAshish R & M R & M R & M R & M R & M
Team Members M M M M M
A – Approval of team decisions I.e., sponsor, business leader, MBB.R – Resource to the team, one whose expertise, skills, may be needed on an ad-hoc basis.M – Member of team – whose expertise will be needed on a regular basis.I – Interested party, one who will need to be kept informed on direction, findings.
Communication Plan
Information Or Activity Target Audience Information Channel Who When
Project Status Sponsor, Champion, BB, Members
E-mails Dipti Nayak BI-Weekly
Tollgate Review BB,MBB, Champion E-mails or Meetings Dipti Nayak As per Project Plan
Project Deliverables or Activities Members, MBB Emails, Meetings Dipti Nayak Weekly
dDefine
Packaging
MaterialsMulti solutions
SugarMawana
MaidaKalkaji, Bikaji, Panwar
PARLEPacked BiscuitsGheeAmul, Gopal, Madhusudan
CustomersOutputProcessInputs Suppliers
SIPOC
START Mixing Dough making
Fermentation Baking cooling
packingEND
dDefine
CTQ Tree
Reduce %age rejection
Reduce %age rejection CTQs
%breakage per Month(Project Y Metric)
%breakage per Month(Project Y Metric)
<2.0% breakage per Month(Target)
<2.0% breakage per Month(Target)
2.0 % breakage per Month(Upper Specification Limit)2.0 % breakage per Month(Upper Specification Limit)
Any Month % breakage greater than 2.0%(Defect Definition)
Any Month % breakage greater than 2.0%(Defect Definition)
Project YProject Y = (breakage in Kgs/per month) * 100
Production of biscuits in Kgs/per month
mMEASURE
Data Collection Planm
MEASURE
Project-Y Operational Definition Defect Def Performance StdSpecification Limit
OpportunityLSL USL
%age breakage in a month
% breakage is the percentage calculated based upon the breakage in Kgs (say n) to
Production in kgs in a Month (say N)
% breakage in a Month greater
than 2.0%Less than 2.0% - 2.0%
Daily breakage data compiled
on Monthly basis
Project-Y Data Type Unit of Measure Formula to be used
Plan to collect Data Plan to sample
What Database or Container will be
used to record this data?
Is this an existing
database or new?
If new, When will the database be ready for use?
When is the planned start date for data collection?
%age breakage in a month Continuous Percentage
breakage in Kgs
(n/N)*100n is breakage in Kgs per Month, N is the production in Kgs
per month
Excel is being used to record the data
and this data is located in
H:Drive /Six Sigma project file
yes - - Mar’2012 to Oct’2012
Validate Measurement System – Gage R & R
mMEASURE
Scope : The Scope of this measurement system is limited to the recoding of breakages in Kg.
Purpose : The purpose of this study is to repeatability and reproducibility of the measurement system.
Procedure : 1) 10 Data samples were collected randomly of 10 days
2) These 10 days breakage were checked by 3 operators on the same weighing machine.
3) After data collection these results were analyzed in Minitab software
Validate Measurement System – R & R
mMEASURE
KPI Data Type
%breakage in Kgs Continuous
Inference: Graphical summary on R & R suggests that there is no significant variation between appraisers.
Part-to-PartReprodRepeatGage R&R
100
50
0
Per
cent
% Contribution
% Study Var
10 9 8 7 6 5 4 3 2 110 9 8 7 6 5 4 3 2 110 9 8 7 6 5 4 3 2 1
0.010
0.005
0.000
P/ N
Sam
ple
Ran
ge UCL=0.01158
LCL=0
Operator 1 Operator 2 Operator 3
_R=0.0045
10 9 8 7 6 5 4 3 2 110 9 8 7 6 5 4 3 2 110 9 8 7 6 5 4 3 2 1
16
12
8
P/ N
Sam
ple
Mea
n
__X=11.59UCL=11.59LCL=11.58
Operator 1 Operator 2 Operator 3
10987654321
16
12
8
P/ N
Operator 3Operator 2Operator 1
16
12
8
Operator
10987654321
16
12
8
P/ N
Ave
rage
Operator 1
Operator 2
Operator 3
Operator
Gage name: Date of study:
Reported by: Tolerance: Misc:
Components of Variation
R Chart by Operator
Xbar Chart by Operator
Data by P/ N
Data by Operator
P/ N * Operator Interaction
Gage R&R (Xbar/ R) for Data
Validate Measurement System – R & Rm
MEASURE
KPI Data Type
%breakage in Kgs Continuous
Inference : As gage R & R is less than 10% of the study variation, we concludes that data can be trusted and good to go.
Gage R&R Study - XBar/R Method
%ContributionSource VarComp (of VarComp)Total Gage R&R 0.00001 0.00 Repeatability 0.00001 0.00 Reproducibility 0.00000 0.00Part-To-Part 8.03352 100.00Total Variation 8.03353 100.00
Study Var %Study VarSource StdDev (SD) (6 * SD) (%SV)Total Gage R&R 0.00268 0.0161 0.09 Repeatability 0.00266 0.0159 0.09 Reproducibility 0.00034 0.0020 0.01Part-To-Part 2.83435 17.0061 100.00Total Variation 2.83435 17.0061 100.00
Number of Distinct Categories = 1491
Graphical summary - Y
mMEASURE
Inference : The summary above represents that data (our project Y) in non-normal in nature as p value is 0.038 which is less than 0.05. the measure of central tendency will be median
765432
Median
Mean
4.404.354.304.254.204.154.10
1st Quartile 3.7242Median 4.24573rd Quartile 4.8933Maximum 7.4933
4.1225 4.3752
4.1513 4.4089
0.8432 1.0228
A-Squared 0.80P-Value 0.038
Mean 4.2488StDev 0.9243Variance 0.8543Skewness 0.091904Kurtosis 0.612410N 208
Minimum 1.8074
Anderson-Darling Normality Test
95% Confidence I nterval for Mean
95% Confidence I nterval for Median
95% Confidence I nterval for StDev95% Confidence I ntervals
Summary for C1
mMEASURE
Stability analysis
Inference : Stability analysis done by run chart, p-value for mixture, oscillation are more than 0.5, suggests that there is data is stable from mixture and trend point of view, analysis needs to be carried out for existence of trends and clustering. Data is not stable as p-value for clustering and trends are below 0.05
200180160140120100806040201
20.0
17.5
15.0
12.5
10.0
7.5
5.0
Observation
Tota
l
Number of runs about median: 89Expected number of runs: 105.0Longest run about median: 7Approx P-Value for Clustering: 0.013Approx P-Value for Mixtures: 0.987
Number of runs up or down: 126Expected number of runs: 138.3Longest run up or down: 5Approx P-Value for Trends: 0.021Approx P-Value for Oscillation: 0.979
Run Chart of Total
Process Sigma Level
TOTAL OPPUTUNITIES 56515
TOTAL FAILED 2377
DPMO(TOTAL FAILED) X 106)/TOTAL OPPURTUNITIES
42059
CURRENT SIGMA LEVEL 3.22
Inference : Current process sigma level is 3.22
mMEASURE
Cause and Effect diagram from breakage
Inference : brainstorming session has identified 11 contributors (Xs) that can affect the performance of Y, these 11 contributing Xs will be analyzed using proper tools to identify & conclude whether they have significant impact on Y.
aAnalyze
producedof 7064breakge outsuffersbiscuits297 Kgs of
Environment
Measurements
Methods
Material
Machines
Personnel
N/Y(7th to 10th )
Vendor for Ghree
Vendor for Maida
Oven Type
Ghee %
Maida %
WAP(maida) %
Oven Heat up time
Mixing Time
Baking Temperature
Baking Time
Cause-and-Effect Diagram
Operator qualification
Data collection plan for Xs that contributes to printing defects
Measure Type Operation definition
How it is measured/collected
Plan to sample
Test to be performed
% Breakage Y (Kgs of biscuits broken (n) x 100) / No. of Kgs of biscuit produced (N))
Formula( n*100)/NData for n, N is collected individually
Mar’12 to Oct’12 Run chart
Baking Time X Amount of time the contents are Baked in baking machine Timer Mar’12 to
Oct’12Regression Analysis
Baking Temperature X Temperature at which Baking is done Temperature meter Mar’12 to
Oct’12Regression Analysis
Oven Type X There are three Ovens Oven A, Oven B, Oven C in which the Baking is done Oven Identification Mar’12 to
Oct’12Mood’s Median Test
Mixing Time X Amount of Time required to mix the contents Timer
Mar’12 to Oct’12 Regression
Analysis
Oven Heat-up Time X
Pre heating time before the contents are placed for baking at certain temperature
TimerMar’12 to Oct’12 Regression
Analysis
aAnalyze
Data collection plan for Xs that contributes to Stitching defects
Measure Type Operation definition How it is measured/collected
Plan to sample
Test to be performed
WAP Maida(%) X
Water absorption percentage, is the total amount of moisture in the contents
Mo = weight w/o moistureW= weight w/moisture% = (W-Mo)*100/W
Mar’12 to Oct’12
Mood’s Median Test
Vendor for Maida X Different suppliers which supply Maida
Supplier Name on packet
Mar’12 to Oct’12
Mood’s Median Test
% Maida X %age of Maida in total contents, weight of Maida = M M*100/W Mar’12 to
Oct’12Mood’s Median Test
% Ghee X %age of Ghee in total contents, weight of Ghee = G
G*100/W Mar’12 to Oct’12
Mood’s Median Test
Vendor for Ghee X Different suppliers which supply Ghee
Supplier Name on packet
Mar’12 to Oct’12
Mood’s Median Test
Operator qualification X Qualification of operators
10th Pass (Yes)10th Failed (No)
Mar’12 to Oct’12
Mann-Whitney Test
aAnalyze
Hypothesis Testing :
Inference :P-Value observed is 0.036 which is less than 0.05, which suggests that we have sufficient evidence to reject null-hypothesis. Baking Time does significantly impacts breakage.
aAnalyze
Regression Analysis: Project Y versus Baking Time
The regression equation isProject Y = 2.70 + 0.0933 Baking Time
Predictor Coef SE Coef T PConstant 2.6962 0.7383 3.65 0.000Baking Time 0.09331 0.04421 2.11 0.036
S = 0.916668 R-Sq = 2.1% R-Sq(adj) = 1.6%
Analysis of Variance
Source DF SS MS F PRegression 1 3.7436 3.7436 4.46 0.036Residual Error 206 173.0977 0.8403Total 207 176.8413
Hypothesis Testing :
Inference :P-Value observed is 0.032 which is less than 0.05, which suggests that we have sufficient evidence to reject null-hypothesis. Baking Temperature does significantly impacts breakage.
aAnalyze
Regression Analysis: Project Y versus Baking Temper
The regression equation isProject Y = 13.6 - 0.0443 Baking Temper
Predictor Coef SE Coef T PConstant 13.646 4.343 3.14 0.002Baking Temper -0.04434 0.02049 -2.16 0.032
S = 0.916172 R-Sq = 2.2% R-Sq(adj) = 1.7%
Analysis of Variance
Source DF SS MS F PRegression 1 3.9306 3.9306 4.68 0.032Residual Error 206 172.9106 0.8394Total 207 176.8413
Hypothesis Testing :
Inference :P-Value observed is 0.007 which is less than 0.05, which suggests that we have sufficient evidence to reject null-hypothesis. Oven Type does significantly impacts breakage.
aAnalyze
Mood Median Test: Project Y versus OVEN
Mood median test for Project YChi-Square = 9.93 DF = 2 P = 0.007
Individual 95.0% CIsOVEN N<= N> Median Q3-Q1 ---------+---------+---------+-------OVEN A 56 55 4.238 1.343 (----------*--------)OVEN B 32 17 4.028 1.008 (---------*-------)OVEN C 16 32 4.475 0.837 (-------*-------) ---------+---------+---------+------- 4.00 4.25 4.50
Overall median = 4.246
Hypothesis Testing :
Inference :P-Value observed is 0.000 which is less than 0.05, which suggests that we have sufficient evidence to reject null-hypothesis. Mixing Time does significantly impacts breakage.
aAnalyze
Regression Analysis: Project Y versus Mixing TIme
The regression equation isProject Y = 7.09 - 0.338 Mixing TIme
Predictor Coef SE Coef T PConstant 7.0874 0.5901 12.01 0.000Mixing TIme -0.33816 0.06992 -4.84 0.000
S = 0.878025 R-Sq = 10.2% R-Sq(adj) = 9.8%
Analysis of Variance
Source DF SS MS F PRegression 1 18.030 18.030 23.39 0.000Residual Error 206 158.811 0.771Total 207 176.841
Hypothesis Testing :
Inference :P Value observed is 0.201, which is greater than 0.05, which suggests that we do not have sufficient evidence to reject null hypothesis. Oven heat up time does not significantly impacts breakage
aAnalyze
Regression Analysis: Project Y versus OVEN Heatup Time
The regression equation isProject Y = 4.44 - 0.0113 OVEN Heatup Time
Predictor Coef SE Coef T PConstant 4.4407 0.1628 27.28 0.000OVEN Heatup Time -0.011260 0.008782 -1.28 0.201
S = 0.922852 R-Sq = 0.8% R-Sq(adj) = 0.3%
Analysis of Variance
Source DF SS MS F PRegression 1 1.4003 1.4003 1.64 0.201Residual Error 206 175.4410 0.8517Total 207 176.8413
Hypothesis Testing :
Inference :P Value observed is 0.813, which is greater than 0.05, which suggests that we do not have sufficient evidence to reject null hypothesis. WAP (Maida)% does not significantly impacts breakage
aAnalyze
Mood Median Test: Project Y versus WAP(maida) %
Mood median test for Project YChi-Square = 2.26 DF = 5 P = 0.813
Individual 95.0% CIsWAP(maida) % N<= N> Median Q3-Q1 ----+---------+---------+---------+--7.0 11 6 4.17 0.87 (-------*----------------)7.1 17 18 4.34 1.41 (----------------*--------)7.2 27 25 4.21 1.12 (---------*-------)7.3 24 27 4.30 1.48 (----------------*--------)7.4 9 8 4.17 1.07 (-----------*---------------------)7.5 16 20 4.47 1.14 (------------*-----) ----+---------+---------+---------+-- 3.90 4.20 4.50 4.80
Overall median = 4.25
Hypothesis Testing :
Inference :P-Value observed is 0.003 which is less than 0.05, which suggests that we have sufficient evidence to reject null-hypothesis. Ghee (%age) does significantly impacts breakage.
aAnalyze
Mood Median Test: Project Y versus Moisture(Ghee) %
Mood median test for Project YChi-Square = 14.22 DF = 3 P = 0.003
Individual 95.0% CIsMoisture(Ghee) % N<= N> Median Q3-Q1 --+---------+---------+---------+----11 15 2 3.48 1.25 (-----------*----)12 52 48 4.21 1.34 (-*--)13 9 10 4.26 1.26 (----*----------)14 27 44 4.47 0.99 (--*-)15 1 0 3.51 * --+---------+---------+---------+---- 2.80 3.50 4.20 4.90
Overall median = 4.25
Hypothesis Testing :
Inference :P Value observed is 0.446, which is greater than 0.05, which suggests that we do not have sufficient evidence to reject null hypothesis. Vendor of Maida does not significantly impacts breakage
aAnalyze
Mood Median Test: Project Y versus Vendor for Maida
Mood median test for Project YChi-Square = 1.61 DF = 2 P = 0.446
Vendor Individual 95.0% CIsfor Maida N<= N> Median Q3-Q1 -------+---------+---------+---------Bikajee 55 57 4.270 1.143 (--------*-------)Kalkaji 26 19 4.097 1.298 (----------*------------)Panwar 23 28 4.413 1.156 (-------------*------) -------+---------+---------+--------- 4.00 4.25 4.50
Overall median = 4.246
Hypothesis Testing :
Inference : P-Value observed is 0.003 which is less than 0.05, which suggests that we have sufficient evidence to reject null-hypothesis. % of Ghee does significantly impacts breakage.
aAnalyze
Mood Median Test: Project Y versus Ghee%
Mood median test for Project YChi-Square = 14.22 DF = 3 P = 0.003
Individual 95.0% CIsMoisture(Ghee) % N<= N> Median Q3-Q1 --+---------+---------+---------+----11 15 2 3.48 1.25 (-----------*----)12 52 48 4.21 1.34 (-*--)13 9 10 4.26 1.26 (----*----------)14 27 44 4.47 0.99 (--*-)15 1 0 3.51 * --+---------+---------+---------+---- 2.80 3.50 4.20 4.90
Overall median = 4.25
Hypothesis Testing :
Inference : P Value observed is 0.148, which is greater than 0.05, which suggests that we do not have sufficient evidence to reject null hypothesis. Vendor for Ghee does not significantly impacts breakage
aAnalyze
Mood Median Test: Project Y versus Vendor for Ghee
Mood median test for Project YChi-Square = 3.82 DF = 2 P = 0.148
Vendor for Individual 95.0% CIsGhree N<= N> Median Q3-Q1 --------+---------+---------+--------Amul 46 32 4.086 1.089 (----------*-------)Gopal 26 32 4.402 1.186 (-----------*----------)Madhusudan 32 39 4.400 1.156 (---------*-------)MD 0 1 4.554 * --------+---------+---------+-------- 4.00 4.25 4.50
Overall median = 4.246
Hypothesis Testing :
Inference :: P Value observed is 0.5641, which is greater than 0.05, which suggests that we do not have sufficient evidence to reject null hypothesis. Operator qualification does not significantly impacts breakage
aAnalyze
Mann-Whitney Test and CI: No, Yes
N MedianNo 96 3.9150Yes 112 4.4698
Point estimate for ETA1-ETA2 is -0.564195.0 Percent CI for ETA1-ETA2 is (-0.8246,-0.3031)W = 8136.0Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.0000The test is significant at 0.0000 (adjusted for ties)
Measurable Type Data Type Test Performed P-Value Inference
% Breakage Y Continuous Run chart N/A N/A
Baking Time X ContinuousRegression Analysis
0.036 Statistically, X has significant impact on Y, as P Value is less than 0.05
Baking Temperature
X ContinuousRegression Analysis
0.032 Statistically, X has significant impact on Y, as P Value is less than 0.05
Oven Type X DiscreteMood’s Median Test
0.007 Statistically, X has significant impact on Y, as P Value is less than 0.05
Mixing Time X ContinuousRegression Analysis
0.000 Statistically, X has significant impact on Y, as P Value is less than 0.05
Oven Heat-up Time
X ContinuousRegression Analysis
0.201 Statistically, X has no significant on Y, as P value is greater than 0.05
Summary on Findings on Xs contributing to Printing Defects aAnalyze
Measurable Type
Data Type
Test Performed P-Value Inference
WAP Maida(%) Y DiscreteMood’s Median Test
N/A N/A
Vendor for Maida
X DiscreteMood’s Median Test
0.446 Statistically, X has no significant on Y, as P value is greater than 0.05
% Maida X DiscreteMood’s Median Test
0.813 Statistically, X has no significant on Y, as P value is greater than 0.05
% Ghee X DiscreteMood’s Median Test
0.003 Statistically, X has significant impact on Y, as P Value is less than 0.05
Vendor for Ghee
X DiscreteMood’s Median Test
0.148 Statistically, X has no significant on Y, as P value is greater than 0.05
Operator qualification
X DiscreteMann-Whitney Test
0.564 Statistically, X has no significant on Y, as P value is greater than 0.05
Summary on Findings on Xs contributing to Stitching Defects aAnalyze
Box – plot on Baking Time, Baking Temperaturei
Improve
A5A4A3A2A1
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3
2
Baking Temperature Category
Pro
ject
Y
Boxplot of Project Y
DCBA
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Baking Time category
Pro
ject
Y
Boxplot of Project Y
DCBA
DCBA
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DCBA
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A1
Baking Time category
Pro
ject
Y
A2 A3
A4 A5
Boxplot of Project Y
Panel variable: Baking Temperature Category
Baking Time and temperature data have been categorized to facilitate to draw them in box plot .
Box plot of Baking time and Temperature does not produce any concrete information on specific contributors.
Box plot of time versus temperature shows that with Baking time category A and Temperature category A3 there is some scope of improvement
Box Plot on Oven Type and Mixing Time iImprove
OVEN COVEN BOVEN A
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OVEN
Pro
ject
Y_1
Boxplot of Project Y_1
10987
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Mixing Time
Pro
ject
Y_1
Boxplot of Project Y_1
10987
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10987
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OVEN A
Mixing Time
Pro
ject
Y_1
OVEN B
OVEN C
Boxplot of Project Y_ 1
Panel variable: OVEN
Box Plot for Oven type and Mixing time has beenPlotted
With oven type it is hard to conclude which Oven plays roleIn reduced breakage, but with Mixing time, “10” time is playing role in breakage
Box plot for Mixing time and Oven type shows that If mixing time is “10” and Oven Type is “C” combination of these two contributes to reduction in breakage
Box Plot on Ghee Percentage iImprove
1514131211
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% Ghee
Pro
ject
Y_1
Boxplot of Project Y_1
Box plot on ghee percentage concludes that breakage is low, when the ghee percentage used is 11%
QFD-House of Quality (process requirements-Production Methods)i
Improve
FMEA for Biscuit Manufacturing Processi
Improve
Implementing Solutions and Time Lines – Pilot Lot Runi
Improve
221199177155133111896745231
8
6
4
2
0
Observation
Indiv
idual V
alu
e
_X=2.048
UCL=3.800
LCL=0.295
1 2
221199177155133111896745231
4
3
2
1
0
Observation
Movin
g R
ange
__MR=0.659
UCL=2.154
LCL=0
1 2
1
11111
I-MR Chart of % age breakage by C12
Evaluation of the Improvement in Pilot Lot Run
Process after improvement is marked in dotted circle, shows that improvement is there in the pilot lot. No points is falling beyond control limits suggests that the process is in statistical control
iImprove
Hypothesis Test to validate statistically significant improvement
Inference: Two sample proportion test was conducted to test whether there was statistically significant improvement during pilot run, p value observed is 0.000 which is less than 0.05, thus we can
conclude that there is significant improvement.
iImprove
Two-Sample T-Test and CI: Before, After
Two-sample T for Before vs After
N Mean StDev SE MeanBefore 208 4.249 0.924 0.064After 15 2.048 0.492 0.13
Difference = mu (Before) - mu (After)Estimate for difference: 2.20195% CI for difference: (1.905, 2.497)T-Test of difference = 0 (vs not =): T-Value = 15.48 P-Value = 0.000 DF = 21
Hypothesis Test to validate whether the target is met or not
Inference: Hypothesis test was conducted to check whether pilot results proportion is meeting the target proportion of 0.015, P-value observed is 0.714 which is greater than 0.05 which shows that there is no significant difference in proportion of the pilot lot and the target, which means the target
is met.
iImprove
One-Sample T: After
Test of mu = 2 vs not = 2
Variable N Mean StDev SE Mean 95% CI T PAfter 15 2.048 0.492 0.127 (1.775, 2.320) 0.37 0.714
2512262011761511261017651261
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0
Observation
Indiv
idual V
alu
e
_X=2.034
UCL=3.322
LCL=0.746
1 2 3
2512262011761511261017651261
4
3
2
1
0
Observation
Movin
g R
ange
__MR=0.484
UCL=1.583
LCL=0
1 2 3
1
11111
I-MR Chart of % age breakage by C12
Control chart for checking the sustainability over a period of time
Post pilot monitoring of the process over one month
Pilot lot monitoring
Inference: Post pilot monitoring of process shows that process is still in statistical control.
cControl
CONTROL PLAN cControl
IMPROVED PROCESS HANDOVERING – PROJECT CLOSURE cControl
1. Process is being handed over to the process owner with the status of improvement shown in the above control chart
2. Control chart should be in place for monitoring the process
3. Revised Process documents, auditing checklist, control plan handed over to operating personnel with changes that were done during pilot run.
4. Out of control action plan for control chart developed and handed over to operations manager
2512262011761511261017651261
8
6
4
2
0
Observation
Individual Value
_X=2.034
UCL=3.322
LCL=0.746
1 2 3
2512262011761511261017651261
4
3
2
1
0
Observation
Moving R
ange
__MR=0.484
UCL=1.583
LCL=0
1 2 3
1
11111
I-MR Chart of % age breakage by C12