case study on 6sigma

1. PRESENTED BY SHANKHA SHUBHRA GOSWAMI
M.TECH 1ST YEAR
SEMINAR
ROLL-17101203011

2. INTRODUCTION
-Six sigma is a business statistical Strategy and is to
identifying defects and removing them from the process
of products to improve quality.
-The Six sigma was founded by Motorola in the 1970s.
-A six sigma process is one in which 99.9999966% of the
products manufactured are statistically expected to be
free of defects (3.4 defects per million).
-Sir Bill Smith,“the Father of six sigma” introduce this
quality improvement Methodology to Motorola.

3. CASE STUDY….
Application of Six Sigma Methodology to Reduce
Defects of a Grinding Process of Distance piece in
common rail direct injection (CRDI) system.

4.  The current project was undertaken in the distance
piece fine grinding process, which is done by fine
grinding machine.
 It finishes both faces of distance pieces in batches
precisely with sub-micron flatness values.
 After fine grinding, distance pieces were inspected
visually to find various defects.

5. DEFINE PHASE
 This phase of the DMAIC methodology aims
to define the scope and goals of the
improvement project in terms of customer
requirements and to develop a process that
delivers these requirements.
 The goal statement was defined as the
reduction in rejection of distance pieces by
50% from the existing level, which should
result in large cost saving for the company
in terms of reduction in rework and scrap
cost.

6. MEASURE PHASE
 Measure the problem
 collect the baseline data to determine where the
process stands as compare to where it needs to
be.
 It also see the critical to quality characteristics an
estimate current process capability. Then find out
the current sigma level according to those
identified characteristic that are mostly important
to the customer.
 These rejections were mainly due to the
occurrence of different types of defects, such as
burr, shades, deep lines, patches and damage,
on the component after machining.

7.  During the defined period of data collection, 368 219
components were inspected and 61 198 components
were rejected due to various defects. Each one of the
rejected components was having one or more defects.
The collected data shows that the rejection in the
process was 166 200 PPM. The corresponding sigma
rating of the process can be approximated to 2.47.

8. ANALYSE PHASE
 Analyze data and process to determine root cause
of defects and opportunities.
 A cause and effect diagram was prepared after
conducting a brain storming session with all the
concerned people

9.  After getting the detailed picture of availability of data
on causes, the team discussed with MBB to identify
the type of analysis possible on these causes.

10. IMPROVE PHASE
 Improve the process by finding solutions to fix,
diminish, and prevent future problems.
 This phase of the Six Sigma project is aimed at
finding solutions for all the root causes identified
during the Analyse phase.

11. CONTROL PHASE
 The last phase of DMAIC is control, which is the phase
where we ensure that the processes continues to work
well, produce desired output results, and maintain quality
levels.
 To monitor the process improvements, basically use tools
like statistically process control charts. These charts have
three limits, the center line for the average. Monitor the
process to ensure that the process is in the control limits.

12. CALCULATIONS
BEFORE APPLYING 6σ
Parts inspected-368219
Parts rejected-61198
DPMO=(61198/368219)*1000000
=166200PPM
Defect percentage=(61198/368219)*100
=16.62%
Yield=83.38%
The sigma rating lies between 2σ and 3σ
From the table the corresponding sigma rating is approx 2.47

13. AFTER APPLYING 6σ
Parts inspected-368219
Parts rejected-4382
DPMO=(4382/368219)*1000000
=11900PPM
Defect percentage=(4382/368219)*100
=1.19%
Yield=98.8%
The sigma rating lies between 3σ and 4σ
From the table the corresponding sigma rating is
approx 3.76

14. CONCLUSION
 Hence, as a result of this project, the rejection
percentage of the distance pieces at the fine
grinding process reduced from 16.6 to 1.19%. The
corresponding approximate sigma level was
estimated as 3.76. Thus, the sigma level of the
process has improved from 2.47 to 3.76.

15. GREETINGS…