Six Sigma is a methodology used to improve business processes through statistical analysis. It was introduced at Motorola in 1986 and made central to GE's strategy in 1995. Six Sigma seeks to reduce defects and variability in processes. The term comes from the goal of having six standard deviations between the process mean and nearest specification limit, resulting in virtually no defects. It uses methodologies like DMAIC for existing processes and DMADV/DFSS for new processes to continuously measure, analyze, control, and improve processes through organizational commitment to quality.

1. Presented by
Mr. Manish Tripathi ( I – 15-18-19)
Thakur Institute of Management Studies
&
Research
(Saturday 11 March, 2017)
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3. WHAT IS SIX SIGMA?
Six Sigma is a methodology used to improve
business processes by utilizing statistical analysis. Six
Sigma has evolved into a more general business-
management philosophy focused on meeting
customer requirements, improving customer
retention, and improving and sustaining business
products and services. Six Sigma is applicable to all
industries.
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4. INTRODUCING SIX SIGMA
• It was introduced by engineer Bill Smith while
working at Motorola in 1986
• The term Six Sigma originated from terminology
associated with statistical modeling of manufacturing
processes
• Jack Welch made it central to his business strategy at
General Electric in 1995
• It is a set of techniques and tools for process
improvement
• It seeks to improve the quality of the output of a
process by identifying and removing the causes of
defects and minimizing variability in manufacturing
and business processes 4

5. ETYMOLOGY OF "SIX SIGMA PROCESS“
• The term "six sigma process" comes from the notion
that if one has six standard deviations between the
process mean and the nearest specification limit,
practically no items will fail to meet specifications
• Process capability studies measure the number of
standard deviations between the process mean and
the nearest specification limit in sigma units,
represented by the Greek letter σ
• As process standard deviation goes up, or the mean
of the process moves away from the center of the
tolerance, fewer standard deviations will fit between
the mean and the nearest specification limit,
decreasing the sigma number and increasing the
likelihood of items outside specification 5

6. The normal distribution looks life a “bell curve”. In this
plot, the x-axis represents the variable being measured,
the y-axis is the frequency with which that variable occurs
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7. Typical Normal Distribution
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8. Concept of Variation and Defects
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9. Z-score and its relation to defects
Z-score illustrates the % of defects/defectives that can
occur when a sample of million opportunities is taken.
This number is called DPMO (Defects per million
opportunities). Higher Z-value indicates lower standard
deviation and corresponding lower probability of anything
lying outside the specification limits and hence lower
defects and vice-versa
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10. 10
Sigma
level
Sigma
(with 1.5σ
shift)
DPMO
Percent
defective
Percentag
e yield
Short-
term Cpk
Long-term
Cpk
1 −0.5 691,462 69% 31% 0.33 −0.17
2 0.5 308,538 31% 69% 0.67 0.17
3 1.5 66,807 6.7% 93.3% 1.00 0.5
4 2.5 6,210 0.62% 99.38% 1.33 0.83
5 3.5 233 0.023% 99.977% 1.67 1.17
6 4.5 3.4 0.00034%
99.99966
%
2.00 1.5
7 5.5 0.019
0.0000019
%
99.999998
1%
2.33 1.83

11. SIX SIGMA DOCTRINE
• Continuous efforts have been put in order to
achieve a stable and predictable processing
results that are of vital importance for business
success
• Manufacturing and business processes have
measured, analyzed, controlled and improved
characteristics
• To achieve a sustained quality improvement
commitment from the entire organization is
required
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12. Six Sigma Methodologies
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13. DMAIC
(For existing processes)
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14. DMADV or DFSS
(For new processes)
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