1.
Six SSiiggmmaa BBllaacckk BBeelltt PPrroojjeecctt oonn
reduction in breakage in biscuits
LOCATION : NOIDA
PROCESS : BISCUITS MAKING
BLACK BELT : Dipti Nayak

2.
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%

3.
Project Charter
d
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, 2012
ANALYZE 03rd Dec,2012 29th Dec, 2012
IMPROVE 02nd Jan, 2013 31st Jan,2013
CONTROL 01st Feb,2013 30th Apr, 2013

4.
ARMI and Communication Plan
Key Stakeholders ARMI Worksheet
Define Measure Analyze Improve Control
GM Finance, Engg I I I I I
Sponsor - VP I I I I I
Champion - GM I & A I & A I & A I & A I & A
MBB A & I A & I A & I A & I A & I
Operation Manager I & M I & M I & M I & M I & M
Ashish R & M R & M R & M R & M R & M
Team Members M M M M M
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
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.
d
Define

5.
Suppliers Inputs Process Output Customers
Mawana Sugar
Packaging
Materials
Multi solutions
Maida
Kalkaji, Bikaji,
Panwar
Ghee Packed Biscuits PARLE
Amul, Gopal,
Madhusudan
SIPOC
START Mixing Dough
making Fermentation Baking cooling
END packing
d
Define

6.
CTQ Tree
Reduce %age
rejection
CTQs
%breakage per Month
(Project Y Metric)
<2.0% breakage per
Month
(Target)
2.0 % breakage per Month
(Upper Specification Limit)
Any Month % breakage
greater than 2.0%
(Defect Definition)
PPrroojjeecctt YY = (breakage in Kgs/per month) * 100
Production of biscuits in Kgs/per month
m
MEASURE

7.
Data Collection Plan
m
MEASURE
Project-Y Operational Definition Defect Def Performance Std
Specification Limit
LSL USL Opportunity
%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)*100
n 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

8.
Validate Measurement System – Gage R & R
m
MEASURE
Purpose : The purpose of this study is to repeatability and reproducibility of the measurement system.
Scope : The Scope of this measurement system is limited to the recoding of breakages in Kg.
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

9.
Validate Measurement System – R & R
m
MEASURE
KPI Data Type
%breakage
in Kgs
Continuous
9
8
7
6
5
4
3
2
1
10
9
8
7
6
5
4
3
2
1
9
8
7
6
5
4
3
2
1
10
9
8
7
6
5
4
3
2
1
Operator
Inference: Graphical summary on R & R suggests that there is no significant variation between
appraisers.
Gage R&R Repeat Reprod Part-to-Part
100
50
0
Percent
% Cont ribut ion
% Study Var
10
9
8
7
6
5
4
3
2
1
10
0.010
0.005
0.000
P/ N
Sample Range
UCL=0.01158
LCL= 0
Operator 1 Operator 2 Operator 3
_
R=0.0045
10
9
8
7
6
5
4
3
2
1
10
16
12
8
P/ N
Sample Mean
__
LXUC=CL1L==11.1151.9.5589
Operator 1 Operator 2 Operator 3
1 2 3 4 5 6 7 8 9 10
16
12
8
P/ N
Operator 1 Operator 2 Operator 3
16
12
8
Operat or
1 2 3 4 5 6 7 8 9 10
16
12
8
P/ N
Average
Operator 1
Operator 2
Operator 3
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 I nteraction
Gage R&R (Xbar / R) for Dat a

10.
Validate Measurement System – R & R m
MEASURE
KPI Data Type
%breakage
in Kgs
Continuous
Gage R&R Study - XBar/R Method
Inference : As gage R & R is less than 10% of the study variation, we concludes that data can be
trusted and good to go.
%Contribution
Source VarComp (of VarComp)
Total Gage R&R 0.00001 0.00
Repeatability 0.00001 0.00
Reproducibility 0.00000 0.00
Part-To-Part 8.03352 100.00
Total Variation 8.03353 100.00
Study Var %Study Var
Source 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 0.01
Part-To-Part 2.83435 17.0061 100.00
Total Variation 2.83435 17.0061 100.00
Number of Distinct Categories = 1491

11.
Graphical summary - Y
m
MEASURE
Summar y for C1
2 3 4 5 6 7
Mean
Median
9 5% Conf idence I nt er v als
4.10 4.15 4.20 4.25 4.30 4.35 4.40
Anderson-Darling Normality Test
A-Squared 0.80
P-Value 0.038
Mean 4.2488
StDev 0.9243
Variance 0.8543
Skewness 0.091904
Kurtosis 0.612410
N 208
Minimum 1.8074
1st Quartile 3.7242
Median 4.2457
3rd Quartile 4.8933
Maximum 7.4933
95% Confidence I nterv al for Mean
4.1225 4.3752
95% Confidence I nterv al for Median
4.1513 4.4089
95% Confidence I nterv al for StDev
0.8432 1.0228
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

12.
m
MEASURE
Stability analysis
Run Char t of Total
1 20 40 60 80 100 120 140 160 180 200
20.0
17.5
15.0
12.5
10.0
7.5
5.0
Observat ion
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
Total
Number of runs about median: 89
Expected number of runs: 105.0
Longest run about median: 7
Approx P-Value for Clustering: 0.013
Approx P-Value for Mixtures: 0.987
Number of runs up or down: 126
Expected number of runs: 138.3
Longest run up or down: 5
Approx P-Value for Trends: 0.021
Approx P-Value for Oscillation: 0.979

13.
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
m
MEASURE

14.
Cause and Effect diagram from breakage
297 Kgs of
biscuits
suffers
breakge out
of 7064
Measurements
Cause-and-Ef fect Diagram
Material
Personnel
Vendor for Maida
Vendor for Ghree
WAP(maida) %
Maida %
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.
a
Analyze
produced
Environment
Methods
Machines
N/Y(7th to 10th )
Ov en Ty pe
Ghee %
Ov en Heat up time
Mixing Time
Baking Temperature
Baking Time
Operator
qualification

15.
Data collection plan for Xs that contributes to printing defects
Measure
Typ
e
Operation definition
How it is
measured/
collected
Plan to
sample
a
Analyze
Test to be
performed
% Breakage Y (Kgs of biscuits broken (n) x 100) / No.
of Kgs of biscuit produced (N))
Formula( n*100)/N
Data 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’12
Regression
Analysis
Baking
Temperature
X Temperature at which Baking is done Temperature meter
Mar’12 to
Oct’12
Regression
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’12
Mood’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
Timer
Mar’12 to
Oct’12 Regression
Analysis

16.
Data collection plan for Xs that contributes to Stitching defects
Measure Type Operation definition How it is
measured/
collected
Plan to
sample
a
Analyze
Test to be
performed
WAP
Maida(%)
X
Water absorption percentage, is the
total amount of moisture in the
contents
Mo = weight w/o moisture
W= 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’12
Mood’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

17.
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.
a
Analyze
Regression Analysis: Project Y versus Baking Time
The regression equation is
Project Y = 2.70 + 0.0933 Baking Time
Predictor Coef SE Coef T P
Constant 2.6962 0.7383 3.65 0.000
Baking 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 P
Regression 1 3.7436 3.7436 4.46 0.036
Residual Error 206 173.0977 0.8403
Total 207 176.8413

18.
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.
a
Analyze
Regression Analysis: Project Y versus Baking Temper
The regression equation is
Project Y = 13.6 - 0.0443 Baking Temper
Predictor Coef SE Coef T P
Constant 13.646 4.343 3.14 0.002
Baking 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 P
Regression 1 3.9306 3.9306 4.68 0.032
Residual Error 206 172.9106 0.8394
Total 207 176.8413

19.
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.
a
Analyze
Mood Median Test: Project Y versus OVEN
Mood median test for Project Y
Chi-Square = 9.93 DF = 2 P = 0.007
Individual 95.0% CIs
OVEN 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

20.
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.
a
Analyze
Regression Analysis: Project Y versus Mixing TIme
The regression equation is
Project Y = 7.09 - 0.338 Mixing TIme
Predictor Coef SE Coef T P
Constant 7.0874 0.5901 12.01 0.000
Mixing 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 P
Regression 1 18.030 18.030 23.39 0.000
Residual Error 206 158.811 0.771
Total 207 176.841

21.
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
a
Analyze
Regression Analysis: Project Y versus OVEN Heatup Time
The regression equation is
Project Y = 4.44 - 0.0113 OVEN Heatup Time
Predictor Coef SE Coef T P
Constant 4.4407 0.1628 27.28 0.000
OVEN 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 P
Regression 1 1.4003 1.4003 1.64 0.201
Residual Error 206 175.4410 0.8517
Total 207 176.8413

22.
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
a
Analyze
Mood Median Test: Project Y versus WAP(maida) %
Mood median test for Project Y
Chi-Square = 2.26 DF = 5 P = 0.813
Individual 95.0% CIs
WAP(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

23.
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.
a
Analyze
Mood Median Test: Project Y versus Moisture(Ghee) %
Mood median test for Project Y
Chi-Square = 14.22 DF = 3 P = 0.003
Individual 95.0% CIs
Moisture(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

24.
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
a
Analyze
Mood Median Test: Project Y versus Vendor for Maida
Mood median test for Project Y
Chi-Square = 1.61 DF = 2 P = 0.446
Vendor Individual 95.0% CIs
for 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

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. % of Ghee does significantly impacts breakage.
a
Analyze
Mood Median Test: Project Y versus Ghee%
Mood median test for Project Y
Chi-Square = 14.22 DF = 3 P = 0.003
Individual 95.0% CIs
Moisture(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

26.
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
a
Analyze
Mood Median Test: Project Y versus Vendor for Ghee
Mood median test for Project Y
Chi-Square = 3.82 DF = 2 P = 0.148
Vendor for Individual 95.0% CIs
Ghree 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

27.
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
a
Analyze
Mann-Whitney Test and CI: No, Yes
N Median
No 96 3.9150
Yes 112 4.4698
Point estimate for ETA1-ETA2 is -0.5641
95.0 Percent CI for ETA1-ETA2 is (-0.8246,-0.3031)
W = 8136.0
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at
0.0000
The test is significant at 0.0000 (adjusted for ties)

28.
Summary on Findings on Xs contributing to Printing Defects a
Measurable Type Data Type
Test
Performed
P-Value Inference
% Breakage Y Continuous Run chart N/A N/A
Baking Time X Continuous
Regression
Analysis
0.036
Analyze
Statistically, X has significant impact on Y,
as P Value is less than 0.05
Baking
Temperature
X Continuous
Regression
Analysis
0.032
Statistically, X has significant impact on Y,
as P Value is less than 0.05
Oven Type X Discrete
Mood’s
Median
Test
0.007
Statistically, X has significant impact on Y,
as P Value is less than 0.05
Mixing Time X Continuous
Regression
Analysis
0.000
Statistically, X has significant impact on Y,
as P Value is less than 0.05
Oven Heat-up
Time
X Continuous
Regression
Analysis
0.201
Statistically, X has no significant on Y, as P
value is greater than 0.05

29.
Summary on Findings on Xs contributing to Stitching Defects a
Measurable
Typ
e
Data
Type
Test
Performed
P-Value Inference
WAP Maida(%) Y Discrete
Mood’s
Median Test
N/A N/A
Vendor for
Maida
X Discrete
Mood’s
Median Test
0.446
Analyze
Statistically, X has no significant on Y, as P
value is greater than 0.05
% Maida X Discrete
Mood’s
Median Test
0.813
Statistically, X has no significant on Y, as P
value is greater than 0.05
% Ghee X Discrete
Mood’s
Median Test
0.003
Statistically, X has significant impact on Y,
as P Value is less than 0.05
Vendor for
Ghee
X Discrete
Mood’s
Median Test
0.148
Statistically, X has no significant on Y, as P
value is greater than 0.05
Operator
qualification
X Discrete
Mann-
Whitney Test
0.564
Statistically, X has no significant on Y, as P
value is greater than 0.05

30.
Box – plot on Baking Time, Baking Temperature
i
Improve
A1 A2 A3 A4 A5
8
7
6
5
4
3
2
Baking Temperat ure Cat egor y
Project Y
Boxplot of Project Y
A B C D
8
7
6
5
4
3
2
Baking Time cat egor y
Project Y
Boxplot of Project Y
Boxplot of Project Y
A B C D
A B C D
8
6
4
2
A B C D
8
6
4
2
A1
Baking Time cat egory
Project Y
A2 A3
A4 A5
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

31.
Box Plot on Oven Type and Mixing Time i
Improve
OVEN A OVEN B OVEN C
8
7
6
5
4
3
2
OVEN
Project Y_1
Boxplot of Pr oject Y_ 1
7 8 9 10
8
7
6
5
4
3
2
Mixing Time
Project Y_1
Boxplot of Project Y_ 1
7 8 9 10
8
6
4
2
7 8 9 10
8
6
4
2
OVEN A
Mixing Time
Project Y_1
OVEN B
OVEN C
Boxplot of Project Y_ 1
Panel variable: OVEN
Box Plot for Oven type and Mixing time has been
Plotted
With oven type it is hard to conclude which Oven plays role
In 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

32.
Box Plot on Ghee Percentage i
Improve
11 12 13 14 15
8
7
6
5
4
3
2
% Ghee
Project Y_1
Boxplot of Project Y_ 1
Box plot on ghee percentage concludes
that breakage is low, when the ghee
percentage used is 11%

33.
QFD-House of Quality (process requirements-Production Methods)
i
Improve

34.
FMEA for Biscuit Manufacturing Process
i
Improve

35.
Implementing Solutions and Time Lines – Pilot Lot Run
i
Improve

36.
Evaluation of the Improvement in Pilot Lot Run
1
1 23 45 67 89 111 133 155 177 199 221
8
6
4
2
0
Obser v at ion
I ndiv idual Value
UCL= 3.800
_
X= 2.048
LCL= 0.295
1 2
1 23 45 67 89 111 133 155 177 199 221
4
3
2
1
0
Obser v at ion
Mov ing Range
UCL= 2.154
__
MR= 0.659
LCL= 0
1 2
1 1 1 1
1
I -MR Char t of % age breakage by C12
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
i
Improve

37.
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.
i
Improve
Two-Sample T-Test and CI: Before, After
Two-sample T for Before vs After
N Mean StDev SE Mean
Before 208 4.249 0.924 0.064
After 15 2.048 0.492 0.13
Difference = mu (Before) - mu (After)
Estimate for difference: 2.201
95% CI for difference: (1.905, 2.497)
T-Test of difference = 0 (vs not =): T-Value = 15.48 P-Value = 0.000 DF =
21

38.
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.
i
Improve
One-Sample T: After
Test of mu = 2 vs not = 2
Variable N Mean StDev SE Mean 95% CI T P
After 15 2.048 0.492 0.127 (1.775, 2.320) 0.37 0.714

39.
Control chart for checking the sustainability over a period of time
1
1 26 51 76 101 126 151 176 201 226 251
8
6
4
2
0
Obser v at ion
I ndiv idual Value
UCL= 3.322
_
X= 2.034
LCL= 0.746
1 2 3
1 26 51 76 101 126 151 176 201 226 251
4
3
2
1
0
Obser v at ion
Mov ing Range
UCL= 1.583
__
MR= 0.484
LCL= 0
1 2 3
1 1 1 1
1
I -MR Char t of % age breakage by C12
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.
c
Control

40.
CONTROL PLAN c
Control

41.
IMPROVED PROCESS HANDOVERING – PROJECT CLOSURE c
Control
1
1 26 51 76 101 126 151 176 201 226 251
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
8
6
4
2
0
Obser v at ion
Individual Value
UCL= 3.322
_
X= 2.034
LCL= 0.746
1 2 3
1 26 51 76 101 126 151 176 201 226 251
4
3
2
1
0
Obser v at ion
Moving Range
UCL= 1.583
__
MR= 0.484
LCL= 0
1 2 3
1 1 1 1
1
I -MR Char t of % age breakage by C12