AN APPLICATION OF SIX SIGMA METHODOLOGY FOR IMPROVING THE
FIRST PASS YIELD OF A GRINDING PROCESS
Group –
1.
Piyush Singh (PGP/23/159)
2.
Archit Shukla
3.
Utkarsh Gupta
4.
Paarth Hebbalkar
5.
Anand Busam
Define
Measure
Analyse
Improve
Control
Element
Description
1. Problem Statement
The first pass yield of the match grinding process was as low as 85 per cent on
average and there was a large number of customer complaints every month from
the field.
2. Process
Match Grinding Process
3. Objective/Goal
To improve the first pass yield of the match grinding process from its current level
of 85 per cent on average to 95 per cent.
1. Production Manager – Team
Leader
2. Maintenance manager
3. Production Planning Engineer
4. Production Supervisor
5. Quality Control Inspector
6. Two operators ( both had over 10
years of experience and good
understanding of the process)
Designation
Role
Responsibilities
The Business Head
Project Champion Selection and approval of the project
and monitoring and execution of the
project
Mentor
Master Black Belt
Conducts training for the team and
provides guidelines for the project
for its successful completion
Production Manager
Team Leader
Completion of the project within the
given timescale
Define
Measure
Analyse
Selection of appropriate product
characteristics
Evaluating the accuracy of the
measurement system
Making necessary measurements
Recording the data and establishing a
baseline of the process capability or
sigma quality for the process
Improve
Control
Selection of appropriate product characteristics
• The CTQ for this project was the clearance
between the barrel and plunger measured in
millimetres.
Barrel
Plunger
• The specification limits for the clearance was
between 0.0030 and 0.0045mm.
Evaluating the accuracy of the measurement system
• In order to validate and justify a capable measurement
system in place, a gauge repeatability and reproducibility
study was performed.
• Number of Operators – 2
• Number of Parts - 10
The Variation due to measurement system was estimated to be less
than 20 percent.
If the % Gage R&R is under 10%, the measurement system is generally
considered to be an adequate measurement system. If the % Gage R&R
is between 10 % to 30%, the measurement system may be acceptable
for some applications. If the % Gage R&R is over 30%, the
measurement system is considered to be unacceptable.
Making necessary measurements
• A Data collection strategy was developed which
includes the sample size required as well as
frequency of data collection from the process.
Number of
Observations –
1300
• A total of 1300 observations on clearance were
collected for a period of eight weeks
Period of
collection – 8
weeks
Recording the data and establishing a baseline of the
process capability or sigma quality for the process
• The Data was tested for normality using the
Anderson – Darling test
• P value < 5% - thus the data do not follow a
normal distribution
• Data was not following any of the known
distribution – the Box-Cox transformation was
tried and the Ppk value was estimated.
•
Ppk – is a performance index
that measures how close the
current
process
mean’s
proximity
is
to
the
specification limits.
• Ppk = [ USL – x(bar) ] / 3 s
• Ppk = 0.22
• Ppk should be greater than 1.5
DPMO – 160,000 defects for million
opportunities
Sigma Level is 2.5
2.5 Sigma process
Define
Measure
Analyse
Improve
Control
Brainstorm all the
possible causes of
the problem
Write sub-causes
branching off the
causes
Objective To uncover the root causes of the problem and
to generate the improvement ideas
Tool – Cause and Effect Analysis
Agree on a problem
statement (effect)
Brainstorm the major
categories of causes
of the problem
Write the categories
of causes as
branches from the
main arrow
A thorough brainstorming session was
carried out in conjunction with cause
and effect analysis
Cause validation plan
To validate the causes, the type of data that could be
collected on each cause was identified.
It was found that some of these causes can only be
validated by Gemba and different type of statistical analysis
can be performed on data collected for the remaining
causes
Those causes where Gemba is identified as the method of
validation, the process was observed with respect to those
causes and a decision was taken whether it is a root cause
or not.
The causes related to input characteristics need to be
validated
About 60 components in a batch were selected and data
were collected on barrel and plunger characteristics
Continuous Variables
• barrel size
• barrel roundness
• barrel taper
• barrel bore straightness
• plunger size
• plunger run out
• plunger taper
• ground plunger taper with
corresponding clearance values
As all these variables are continuous,
the effect of these input dimensional
characteristics on the clearance value needs
to be validated by a multiple regression
analysis.
Results The results of the regression
analysis revealed that the pvalues for barrel roundness,
barrel taper and ground plunger
taper were appeared to be less
than 0.05
Hence the team concluded that
these variables significantly
affect the clearance
There were few causes related to the machine parameters of the process. The team
has decided to use a scientific approach using design of experiments to identify the
optimum conditions for the machine parameters.
The other causes listed in the
cause and effect diagram were
validated by Gemba analysis
Define
Measure
Analyse
Improve
Control
Results
Methodology
Optimization of machine
parameters and
identification of
interaction effect among
parameters
Setting up and carrying out
experiment to study interaction
effect using Taguchi parameter
design. Level for each parameter
was determined that would lead
to maximum signal to noise ratio
Factors and their level for experiment
Final Selection of levels of parameters
Solutions for all the root
causes was determined
and risk assessment was
carried out for each
proposed solution
Metric
Before
After
DPMO
16000
6000
Yield
85%
99.5%
Solution for root causes
Define
Measure
Analyse
Improve
• Aim of this phase is to sustain the improvements made
• Difficult to maintain the changes because of reasons like human resource attrition, obsolescence of
equipment
• Different tools are utilized to ensure that the improvements are sustained
The changes in procedure were documented in quality management system of organization for
future references and standardizing improvements from this project
The audit checklist used by internal auditors was updated and CTQs discovered during the
project were added. If deviations were found, they were reported and corrected
Control charts were introduced to adopted for monitoring the process in addition to control
plan and to take corrective action against any special causes for variation
Training was provided to people working in the process for the new operational methods and to
build confidence among them
Control