KNOWLEDGE SHARING PROGRAM

TOPIC: INSTRODUCTION OF SIX SIGMA

BU : M&M
CSD : QMD
PRESENTED BY

MOHAMMAD ZULFEQUAR ALI KHAN

DY. MANAGER (QMD)
TPL ID: TPL5722
3.0 MTPY NISP, NAGARNAR
 INTRODUCTION OF SIX SIGMA

ix Sigma is a set of techniques and tools for process improvement. It was developed
by Motorola in 1986.

ngineer Bill Smith invented Six Sigma.

he term Six Sigma originated from terminology associated with manufacturing,

specifically terms associated with statistical modeling of manufacturing processes. The
maturity of a manufacturing process can be described by a sigma rating indicating its
yield or the percentage of defect-free products it creates.

he word Sigma is a statistical term that measures how far a given process deviates from
perfection.

he central idea behind Six Sigma: If you can measure how many "defects" you have in a
process, you can systematically figure out how to eliminate them and get as close to
"zero defects" as possible and specifically it means a failure rate of 3.4 parts per million
or 99.9997% perfect.
 INTRODUCTION OF SIX SIGMA

he term Sigma is used to designate the distribution or spread about the mean
(average) of any process and procedure.

SIGMA CAPABILITY Defects per Million Opportunity

s defects reduces, sigma capability improves.

σ (Sigma) PPM
2 308537
3 66807
4 6210
5 233
6 3.4
 INTRODUCTION OF SIX SIGMA
Describe SIX Sigma in Single line
• It is Measurement system
• It is Problem solving approach
• It is Disciplines change process
• It is Business stategy
• It is 18th letter in the greek alphabet
• It is measure of consistemcy
 INTRODUCTION OF SIX SIGMA
Features of Six Sigma

ix Sigma's aim is to eliminate waste and inefficiency, thereby increasing customer satisfaction by
delivering what the customer is expecting.

ix Sigma follows a structured methodology, and has defined roles for the participants.

ix Sigma is a data driven methodology, and requires accurate data collection for the processes being
analyzed.

ix Sigma is about putting results on Financial Statements.

ix Sigma is a business-driven, multi-dimensional structured approach for:

– Improving Processes
– Lowering Defects
– Reducing process variability
– Reducing costs
– Increasing customer satisfaction
– Increased profits
 INTRODUCTION OF SIX SIGMA
Benefits of Six Sigma
Six Sigma offers six major benefits that attract companies:

enerates sustained success

ets a performance goal for everyone

nhances value to customers

ccelerates the rate of improvement

romotes learning

xecutes strategic change

 It uses a set of quality management methods, mainly statistical methods, and creates a special
infrastructure of people within the organization ("Champions", "Black Belts", "Green Belts",etc.) who
are experts in these methods. Each Six Sigma project carried out within an organization follows a
defined sequence of steps and has quantified value targets, for example: reduce process cycle time,
reduce pollution, reduce costs, increase customer satisfaction, and increase profits.
 INTRODUCTION OF SIX SIGMA
Methodologies
• Six Sigma projects follow two project methodologies inspired
by Deming's (PDCA) Plan-Do-Check-Act Cycle. These methodologies, composed
of five phases each, bear the acronyms DMAIC and DMADV.
• DMAIC
The DMAIC project methodology has five phases:

-Define the system, the voice of the customer and their requirements, and the
project goals, specifically.

-Measure key aspects of the current process and collect relevant data.

-Analyze the data to investigate and verify cause-and-effect relationships.

Determine what the relationships are, and attempt to ensure that all factors have
been considered. Seek out root cause of the defect under investigation.
 INTRODUCTION OF SIX SIGMA

-Improve or optimize the current process based upon data analysis using techniques such as design
of experiments, and standard work to create a new, future state process.

-Control the future state process to ensure that any deviations from the target are corrected before
they result in defects. Implement control systems such as statistical process control, production
boards, visual workplaces, and continuously monitor the process.

he DMADV project methodology, known as DFSs("Design For Six Sigma"),features five phases:

efine design goals that are consistent with customer demands and the enterprise strategy.

easure and identify CTQs (characteristics that are Critical To Quality), Measure product capabilities,

production process capability, and measure risks.

nalyze to develop and design alternatives

esign an improved alternative, best suited per analysis in the previous step

erify the design, set up pilot runs, implement the production process and hand it over to the process
owner(s).
 INTRODUCTION OF SIX SIGMA
Implementation roles
Six Sigma identifies several key roles for its successful implementation.

xecutive Leadership includes the CEO and other members of top management. They are responsible for
setting up a vision for Six Sigma implementation.

hampions take responsibility for Six Sigma implementation across the organization in an integrated
manner.Champions also act as mentors to Black Belts.

aster Black Belts, identified by champions, act as in-house coaches on Six Sigma. They devote 100% of
their time to Six Sigma. They assist champions and guide Black Belts and Green Belts. Apart from
statistical tasks, they spend their time on ensuring consistent application of Six Sigma across various
functions and departments.

lack Belts operate under Master Black Belts to apply Six Sigma methodology to specific projects. They
devote 100% of their valued time to Six Sigma. They primarily focus on Six Sigma project execution and
special leadership with special tasks, whereas Champions and Master Black Belts focus on identifying
projects/functions for Six Sigma.

reen Belts are the employees who take up Six Sigma implementation along with their other job
responsibilities, operating under the guidance of Black Belts.
 INTRODUCTION OF SIX SIGMA
SIX SIGMA'S PROBLEM SOLVING APPROACH

Practical Problem

Statistical Problem

Statistical Solution

Practical solution
 INTRODUCTION OF SIX SIGMA
Standard Deviation
The standard deviation (SD) (represented by the Greek letter sigma, σ) is a
measure that is used to quantify the amount of variation or dispersion of a set of
data values. A low standard deviation indicates that the data points tend to be very
close to the mean (also called the expected value) of the set, while a high standard
deviation indicates that the data points are spread out over a wider range of values.
Or
The Standard Deviation is a measure of how spread out numbers are.

The formula is: it is the square root of the Variance.

 INTRODUCTION OF SIX SIGMA
Variance
The average of the squared differences from the Mean.
Or
Variance is always non-negative: a small variance indicates that the data points tend
to be very close to the mean (expected value) and hence to each other, while a
high variance indicates that the data points are very spread out around the mean
and from each other.

To calculate the variance follow these steps:

ork out the Mean (the simple average of the numbers).

hen for each number: subtract the Mean and square the result (the squared
difference).

hen work out the average of those squared differences. 

 INTRODUCTION OF SIX SIGMA
Example
You have just measured the heights of your dogs (in millimeters): The heights (at
the shoulders) are: 600mm, 470mm, 170mm, 430mm and 300mm.
 INTRODUCTION OF SIX SIGMA
Find out the Mean, the Variance, and the Standard Deviation.
Your first step is to find the Mean:
Mean = (600 + 470 + 170 + 430 + 300)/5 = 394
so the mean (average) height is 394 mm.
 INTRODUCTION OF SIX SIGMA
Now we calculate each dog's difference from the Mean:

To calculate the Variance, take each difference, square it, and then average the result:
 INTRODUCTION OF SIX SIGMA
So, the Variance is 21,704.
And the Standard Deviation is just the square root of Variance, so:
Standard Deviation: σ = √21,704 = 147.32... = 147 (to the nearest mm)
And the good thing about the Standard Deviation is that it is useful. Now we can
show which heights are within one Standard Deviation (147mm) of the Mean:
So, using the Standard Deviation we have a "standard" way of knowing what is normal,
and what is extra large or extra small.
 INTRODUCTION OF SIX SIGMA

ur example was for a Population (the 5 dogs were the only dogs we were interested in).

ut if the data is a Sample (a selection taken from a bigger Population), then the calculation
changes!

hen you have "N" data values that are:

he Population: divide by N when calculating Variance (like we did)

Sample: divide by N-1 when calculating Variance

ll other calculations stay the same, including how we calculated the mean.
Example: if our 5 dogs were just a sample of a bigger population of dogs, we would divide by 4
instead of 5 like this:

ample Variance = 108,520 / 4 = 27,130

ample Standard Deviation = √27,130 = 164 (to the nearest mm)

Thank You