International Journal of Engineering Trends and Technology (IJETT) – Volume 21 Number 5 – March 2015
Application of Six Sigma Tool for Problem Analysis
– A Case Study in Manufacturing Industry
Mr.Amol.J.Gangai#1 Prof.G.R.Naik*2
1PG Student. 2Associate Professor, Department of Production Engineering, KIT’S College of Engineering, Kolhapur
Abstract:
Aligning Lean manufacturing by applying six sigma in
manufacturing industries gives a upper hand for the
organization to reduce cost due to scrap & non value adding
activities. Projects can be of two types 1.Problem solving
2.Process Optimization. Six Sigma is a disciplined, datadriven approach and methodology for eliminating defects in
any process – from manufacturing to transactional and from
product to service. The fundamental objective of the Six. This
paper includes a case study on Six Sigma to reduce the
rejection of EA16 engine cylinder head due to valve guide
surface roughness out of specification. This paper includes
define, measure & analyze, Improve & control phase.
Application of Paired comparison, Multi-vari analysis tool for
problem solving is used. Process capability study before and
after implementation of tool using Minitab software is also
done.
Six Sigma = TQM + Stronger Customer Focus+ Additional
Data Analysis Tools + Financial Results + Project
Management [7]
II. TERMINOLIGIES USED IN SIX SIGMA:
BIG Y = Main Response for the Problem
SSV‟s = Suspected sources of Variation for the
problem. They are also called as X‟s
Cause(s) = SSV‟s that are confirmed as cause(s)
for the problem using the DOE tools, but are not
controllable and need to be funnelled further.
They will become the intermediate Y‟s
Keywords–
Six Sigma, process improvement, DMAIC,
continual improvement, M&A, SSV‟s, TQM, DOE.
Root X‟s – Root cause(s) that are pinpointed
using DOE tools and are controllable by
implementing process improvement actions
I. INTRODUCTION
The roots of Six Sigma as a measurement standard can be
traced back to Carl Frederick Gauss (1777-1855) who
introduced the concept of the normal curve. Six Sigma as a
measurement standard in product variation can be traced back
to the 1920′s when Walter Shewhart showed that three sigma
from the mean is the point where a process requires correction
[2] . Many measurement standards (Cpk, Zero Defects, etc.)
later came on the scene but credit for coining the term “Six
Sigma” goes to a Motorola engineer named Bill Smith [6]. Six
Sigma helped MOTOROLA REALIZE powerful bottom-line
results in their organization – in fact, they documented more
than $16 Billion in savings as a result of our Six Sigma efforts
[3]. Six Sigma has evolved over time. Six Sigma can be seen
as: a vision; a philosophy; a symbol; a metric; a goal; a
methodology.” Anbari (2002) pointed out that six sigma is
more comprehensive than prior quality initiatives such as
Total Quality Management (TQM) and Continuous Quality
Improvement (CQI) [8] . The six sigma method includes
measured and reported financial results, uses additional, more
advanced data analysis tools, focuses on customer concerns,
and uses project management tools and methodology[1]. He
summarized the six sigma management method as follows:
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III. CASE STUDY UNDER OBSERVATION IS CARRIED
OUT USING DMAIC APPROACH OF SIX SIGMA:
Problem Statement: To reduce the rejection of EA16
engine cylinder head due to valve guide surface roughness out
of specification.
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FIG.1 shows Pareto analysis.
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International Journal of Engineering Trends and Technology (IJETT) – Volume 21 Number 5 – March 2015
IV. DEFINE PHASE
Problem Statement: To reduce the rejection of EA16 engine
cylinder head due to valve guide
Surface roughness out of specification.
The minimum rejection for the problem was calculated and is
0% and maximum rejection is 14.7%.The suspected problem
for the case study is Less Tool Speed, Material Hardness,
Excess tool wear. The date and shift in which the process was
observed to identify the actual physical phenomenon: General
Shift 10/11/2013. The tool and technique used to identify the
cause were checked and found o.k. Mitutoya Surface
Roughness Checking.
Monthly rejection trend was plotted down for months and
checked for any abnormal cause contributing to the problem.
No abnormal cause was identified for the problem
Part number selected for study
- D7.302.10.0.02. Last manufacturing process stage where
the Problem is generated
PUSH ROD, OIL GALLERY & VALVE SEAT CUTTING
& VALVE GUIDE FINISH
Suspected physical phenomenon‟s that can lead to the
problem
Less Tool Speed, Material Hardness , Excess tool wear.
Fig.2 shows the process mapping.
The cost of poor quality was found to be 6.26 Lakhs.
For systematic thinking purpose, the SSV‟s are listed in the
following categories and in the same order [7]
Process Parameters (Parameters that are set and can change
during processing)
Machine Parameters (Hardware characteristics)
Processing material parameters (eg: coolant, draw oil)
Tooling related parameters
Operator error related parameters
Work environment related parameters
Input material related parameters.
V. MEASURE & ANALYSE
In Measure and Analyse phase Paired Comparison was used
as a tool.
In Paired Comparison:
Ideally 6 Good and 6 Bad parts are selected based on
RESPONSE („Y‟)
When selecting Good and Bad, Best of Best (BOB) and Worst
of Worst (WOW) should be selected
When 8 Good and 8 Bad parts cannot be selected, because the
rejection is less, then at-least 6 BOB and 6 WOW should be
selected based on response
Select these 8 or 6 BOB and WOW parts from one shift‟s
production.
6 BOB and 6 WOW parts are selected based on one shift
production quantity
The parts should be marked from 1-16 or 1-12
A tabular column is made with each SSV in the column
Each SSV is measured/verified/checked on the 8 BOB and 8
WOW components and the results are recorded as shown on
the next slide
It is important to down the serial number of the component
and the corresponding SSV values. This will help us to do
further in-depth analysis later
Do R&R study for the measurement if required.
If the SSV is attribute, then the SSV is verified on Good and
Bad and if possible scaled on a scale of 1-3. The data is
recorded in the scale
If the SSV is attribute and the SSV cannot be scaled, then the
data is recorded as just OK or Not OK.
In above problem 6 BOB and 6 WOW valve guide were
selected and concentricity, cylindricity & roundness were
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International Journal of Engineering Trends and Technology (IJETT) – Volume 21 Number 5 – March 2015
taken as suspected sources of variation and the count was
calculated for the three.
Table 3 shows selection of 6 BOB & 6 WOW valve guide
selected for project analysis.
As the count for concentricity, cylindricity & roundness was
less than 6 it was not the confirmed cause for the problem.
Below shows the paired comparison carried out for
concentricity, cylindricity & roundness.
The next tool used in measure & analyze phase was multi vary
analysis.
Is used only when the problem is generated from a
Manufacturing process.
Response (Y) is analysed in this tool
Can be used only when the response is Variable
If the response is attribute, use Concentration chart
Used to find out what sources of variation is the highest in a
process
Is applied only after the process creating the problem is
established using the other tools.
Any Process will have the following types of variation
Part to Part
Time to Time
Stream to Stream (If the process has multiple streams)
Multi-vari analysis identifies which type of variation is the
highest.In muti-vari analysis 7 time blocks were prepared and
part to part, time to time & stream to stream variation was
calculated. Out of the three variation part to part variation was
found to be more exceeding time to time & stream to stream
variation.
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International Journal of Engineering Trends and Technology (IJETT) – Volume 21 Number 5 – March 2015
Table 4 shows multivary analysis carried out
Table 5 shows calculation of variations in process.
As part to part variation was highest the equipment used was
creating the defect.
While analyzing the process the tool and process parameter
were studied.
The tool used was reamer diameter 8.012 and speed and feed
was 190 and 1950 RPM.
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International Journal of Engineering Trends and Technology (IJETT) – Volume 21 Number 5 – March 2015
VI. Improve Phase:
for exhaust and inlet valve. And shows improvement in
process capability after tool implementation.
In improve phase trials were taken with new tool Dia. 8 H7 x
Cutting length 60 x Flute Length 90 x
Oval length 130. The surface finish of valve guide was
checked and found within specification.
Table 6 shows the cylinder head surface finish reading after
tool implementation and shows within specification.
FIG. 3
FIG. 4
The tool life was calculated and was found to be for 350 jobs.
Process Variation:
FIG. 5
Fig. 3 & Fig.4 shows process capability using mintab before
multivary analysis for exhaust and inlet valve. Fig.5 & Fig.6
show process capability using Minitab after multivary analysis
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International Journal of Engineering Trends and Technology (IJETT) – Volume 21 Number 5 – March 2015
inefficiency. Focusing on those processes with greatest impact
on business performance, as defined by leadership teams, the
methodology involves statistical analysis to quantify repeated
common cause variations - which can then be reduced by the
Six Sigma team. Six Sigma becomes a continuous process for
quality improvement and cost reduction flowing throughout
the company.
I. REFERENCES:
[1] Young Hoon Kwak, Frank T. Anbari, Success Factors in Managing
Six Sigma Projects ,May– Project Management Institute Research
Conference, London, UK, July 11-14, 2004
[2] McClusky, R., 2000. The Rise, fall, and revival of six sigma.
FIG. 6
Measuring Business Excellence 4 (2), 6–17.
[3] Antony, J., Banuelas, R., 2002. Key ingredients for the effective
Control Phase:
implementation of six sigma program. Measuring Business Excellence 6
Using control chart for monitoring the tool life and surface
finish parameter.
(4), 20–27.
[4] Antony, J., Escamilla, J.L., Caine, P.,. Lean Sigma. Manufacturing
Engineer 82 (4), 40–42,2002
In future process optimization in problem solving can be
carried out.
Rolled
Throughput
Yield: A new six sigma-based performance
measure Volume 140, Issue 1, Pages 368–373,2012
Conclusion:
The above paper describes steps in Six Sigma of Define,
Measure & Analyse, Improve & control used for problem
solving. In define phase problem selection using pareto
analysis process mapping are carried out and tool used for
problem solving paired comparison & multivary analysis in
measure and analyse phase are also explained in this paper.
The cost saving achieved through successful implementation
of this project is 6.26 lac/annum. Elimination of first input
related variations using paired comparison and then using
multivary analysis for process. Process study before and after
implementation is validated using Minitab software in this
paper. Six Sigma looks at all work as a series of processes
with inherent variations, which can cause waste or
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[5] Abbas Saghaei Hoorieh Najafi Rassoul Noorossana, Enhanced
[6] Scott M. Shafera, Sara B. Moeller The effects of Six Sigma on
corporate performance: An empirical investigation Volume 30, Issues
7–8, November 2012, Pages 521–532
[7] Maha Yusr Abdul Rahim Othmanb, Sany Sanuri Mohd Mokhtarc
Assessing the Relationship among Six Sigma, Absorptive Capacity and
Innovation Performance Volume 65, 3 December 2012, Pages 570–578
[8]
Jayesh Pathak , Tushar N. Desai -SIX SIGMA Quality
Management Technique An overview. JERS/Vol.II/ Issue III/JulySeptember,2011/64-72
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