6 sigma awareness
TRANSCRIPT
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2Are you ready for Six sigma?
The starting point of the Six sigma journey is therealizationof the
problem, of agapbetween what you want to achieve and where you
currently are.
If your answer to any of these question is YES you are ready for six
sigma.
Do you have a sense of dissatisfaction over the present state of your
organization?Are your customers often dissatisfied with your quality / price / delivery ?
Do you face a threat from incoming competition?
Are you losing your market share?
Are your costs high?
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3What is Six sigma?
Six sigma is a problem solving technique
Six sigma is a statistical tool
Six sigma is nothing but Excellence in whatever we
do
Six Sigma means accuracy Six sigma means low variation
How it is different?
Six sigma gives more benefits
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Two Events
Industries taking up SIX SIGMA initiative
Release of ISO 9001: 2000
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Commonalities
Continual Improvement
Process Approach
Focus on excellence in current processes
Emphasis on measurement, quantification
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6Invented at Motorola
Perfected at General Electric
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SIX SIGMA AS A PHILOSOPHY
We are in the business to make money
We make money by satisfying needs
We are able to satisfy needs by doing
Every need / do pair is an interaction
The aim of customer focus is on improving need / do interactions
Repetition of the same action constitutes a process
Improvement of our business mean improvement of our processcustomers need product / service on-time, with zero defects, at the lowest cost
Suppliers create processes to generate needed products
As process capability improves, the product quality increases
As quality increases, costs & cycle-time go down
The attributes of customer satisfaction must be measured if they are to be
improved
To improve means we must be able to predict and prevent, not detect and react
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Prediction is correlated to certainty
Maximization of certainty is dependent upon the measurement of process
capabilityprocess capability is best understood & reported using statistics.
Statistics is dependent upon data
Data must be collected in the process according to a plan
Statistics is used to convert raw data into meaningful summary information
Statistical info. is used to report on, improve, and control the process
The basis of statistics is the mean & standard deviationThe mean reports on process centering
The standard deviation reports the extent of variation or scatter about the
mean
By combining the mean and standard deviation, the sigma of a process can
be calculated
The sigma of the process tells us how capable it is
The process sigma can be used to compare similar or dissimilar processes
SIX SIGMA AS A PHILOSOPHY ..contd
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Such comparison of processes is called benchmarking
Benchmarking is a competitive tool used to uncover what we do well
and not so good
Once basic competencies and deficiencies are known, corrective action
can be taken
Corrective action leads to the reduction of defects, cycle-time & cost
The reduction of defects, cycle-time, & cost leads to improved customer
satisfaction
As customer satisfaction improves, the likelihood of doing business
increases
As business increases, we (as individuals) grow and prosper
SIX SIGMA AS A PHILOSOPHY contd
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The power of measurement
WE DONT KNOW WHAT WE DONT KNOW
WE CANT ACT ON WHAT WE DONT KNOW
WE WONT KNOW UNTIL WE SEARCH
WE WONT SEARCH FOR WHAT WE DONT QUESTION
WE DONT QUESTION WHAT WE DONT MEASURE
HENCE, WE JUST DONT KNOW
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The Role of measurement
IF WE CANNOT EXPRESS WHAT WE KNOW
IN THE FORM OF NUMBERS, WE REALLY
DONT KNOW MUCH ABOUT IT
IF WE DONT KNOW MUCH ABOUT IT, WE
CANNOT CONTROL IT
IF WE CANNOT CONTROL IT, WE ARE AT THE
MERCY OF CHANCE
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Six Sigma
Gave us a measure for the performance of
even routine processes that we come
across in our daily activities
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HOW DO WE JUDGE THE EFFICACY OF
OUR PROCESSES?
Meets customer demands
(Process Effectiveness)
Meets business objectives
(Process Efficiency)
PROCESS
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What is sigma
Measure of variation
Data
1, 2, 3, 4, 5, 1, 1, 3, 5, 5,
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15Data
18.5
19.620.6
16.5
15.8
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THE NORMAL CURVE
Center of the barSmooth curve
interconnecting thecenter of each bar
Units of Measure
If we join the middle points of a Histogram and join it a free line
sketch then the distribution looks like as follows;
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NORMAL DISTRIBUTION -PROPERTIES
If we know the average () and variation () of normaldistribution then we can explain every thing of thedistribution or process:
68.26% of the values line within 1 from the mean AND
95.46% of the values line within 2 from the meanAND
99.73% of the values line within 3 from the mean
THEN the distribution is normal.
NORMAL DISTRIBUTION IS CHARACTERISED BY A BELLSHAPED CURVE.
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-6 -5 -4 -3 -2 -1 +1 +2 +3 +4 +5 +668. 26%
95.44%
99.73%
99.9937%
99.999943%
99.9999998%( OF ALL ITEMS )
UTILIZING
THE SIX
STEPS TOSIX SIGMA
AVG.
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19
+1-1
AVG.= 18
LSL =16 USL =20
DefectDefect
= 2.0
Yield 68.27% Defect = 317300 PPM
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20
USL = 20
AVG. = 18
-2 +2
Defect Defect
= 1.0
LSL =16
Yield 95.45% Defect = 45500 PPM
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LSL = 16 USL = 20
AVG. = 18
-3 +3
Defect Defect
= 0.6
Yield 99.73% Defect = 2700 PPM
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LSL = 16 USL = 20
AVG. = 18
-4 +4
Defect Defect
= 0.5
Yield 99.9937% Defect = 63 PPM
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LSL = 16 USL = 20
AVG. = 18
-5 +5
Defect Defect
= 0.4
Yield 99.999943% Defect = 0.57 PPM
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LSL = 16 USL = 20
AVG. = 18
-6 +6
= 0.33
Yield 99.9999996% Defect = 0.002 PPM
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WHAT IS SIX SIGMA
Six sigma is when the inherent variability of the process is half that of the
requirements
LSL USL6
33
6
A WORD OF CAUTION:It is possible to achieve six sigma by widening specs but theissue is that would the customer accept it
PICTORIALLY
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LSL = 16 USL = 20
AVG. = 18
-6 +6
= 0.33
Yield 99.9999996% Defect = 0.002 PPM
271 5
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LSL = 16 USL = 20
AVG. = 18
-6 +6
= 0.33
1.5
281 5
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LSL = 16 USL = 20
AVG. = 18
-6 +6
= 0.33
1.5
29LONG TERM AND SHORT TERM
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LONG TERM AND SHORT TERM
SIGMAS
LSL X USL LSL X USL
Cumulative
short-termcapability
Cumulative
long-termcapability
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THE CONCEPT OF Z
A CB
Z = | SL - Avg.| / std. deviation
ZuZ
L
+ -
31Improvement Scale
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308 537
66807
6210
233
Process
capability
23
Defects per million
opportunities
No. of times
improvement
45
3.46
4.6 times
11 times
68 times
26 times
Improvement Scale
32Improvement Scale
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308 537
66807
6210
233
Process
capability
23
Defects per million
opportunities
No. of times
improvement
45
3.46
4.6 times
11 times
68 times
26 times
p o e e t Sca e
Yield
69.2%
93.3%
99.4%
99.98%
99.9997%
THE IMPACT OF IMPROVEMENT
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THE DIFFERENCE BETWEEN 4SIGMA AND 6SIGMA
IS GREATER THAN HUNDREDFOLD IMPROVEMENT
100K
10K
1K
100
10
1
2 3 4 5 6 7
AVERAGECOMPANY
BEST IN CLASS
>>100X
3.4 PPM
SIGMA
34
A 4
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A 4 company Profitable and growing
Market prices declining Competitors increasing
Has a Q assurance program
Spends 10 - 20 % of sales on rework & rejection
Unaware that best-in class companies have similar
processes 100 times better
Believes Zero defect goal is neither realistic nor
achievable
Has 10 times the number of suppliers required to run
the business
5 - 10 % customers are dissatisfied
351. Why we chose Six sigma ?
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3.4
ppm
233 ppm
6210ppm
66807 ppm
308537 ppm
697672 ppm
Average
Processes
Low
Hanging
Six Sigma
World class
Five Sigma
Four Sigma
Three Sigma
Two Sigma
One Sigma
Team work, Reviews
and Problem Solving
Advanced Statistical
Analysis
Design for
manufacturability
Climbing the steps
y g
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Six Sigma
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Six Sigma
Steps followed :
Define
Measure
Analyse
Improve
Control
Continually improve
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Six Sigma
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Six Sigma
Steps followed :
Define
Measure
Analyse
Improve
Control
Continually improve
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Definethe Customer, their Critical to Quality (CTQ)issues, and the Core Business Process involved.
Define who customers are, what their
requirements are for products and services,
and what their expectations areDefine project boundaries the stop and
start of the process
Define the process to be improved by
mapping the process flow
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Measurethe performance of the Core BusinessProcess involved.
Develop a data collection plan for the
process
Collect data from many sources to
determine types of defects and metrics
Compare to customer survey results to
determine shortfall
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nalyzethe data collected and process map todetermine root causes of defects and opportunities
for improvement.
Identify gaps between current performance
and goal performance
Prioritize opportunities to improve
Identify sources of variation
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Improvethe target process by designing creativesolutions to fix and prevent problems.
Create innovate solutions using technology
and discipline
Develop and deploy implementation plan
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ontrolthe improvements to keep the process onthe new course.
Prevent reverting back to the "old way"
Require the development,
documentation and implementation of anongoing monitoring plan
Institutionalize the improvements
through the modification of systems and
structures (staffing, training, incentives
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DFSS
Design For Six Sigma
45Two Types of Quality
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yp y
Type 1: Customer Quality- The features that customers
want.
Type 2: Engineered Quality- The problems customers donot want.
Customer qualityleads to the size of the market segment.
It includes items such as function, features, colors and
designs. The better the customer quality, the bigger themarket size becomes. In order to obtain the market size,
the price must be reasonable. Customer quality is
addressed primarily though customer surveys and series of
QFDs.
On the other hand, engineered qualityincludes defects,failures, noise, vibration, unwanted phenomena, lowering
the cost of manufacture, and minimizing manufacturing
problems.
46DMAD
Define the project goals and customer
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Definethe project goals and customer
(internal and external) deliverables
Measureand determine customer needs
and specifications
Analyzethe process options to meet the
customer needs
Design(detailed) the process to meet the
customer needs
Verify the design performance and ability
to meet customer needs
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Customer Satisfaction Requirements
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Customer Satisfaction Requirements
Given that product performance features are perceived
by the customer as providing fair value, the
customer has a right to expect that the:
Product/Service is delivered when promised;
Product/Service is delivered with no defects;
Product/Service does not experience early life
failures; and Product does not fail excessively in service.
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FOCUS ON TOTAL DEFECTS PER UNIT
REDUCES THE CYCLE TIME PER UNIT
REDUCES WIP INVENTORY CARRYING COSTS
REDUCES DELIVERED DEFECTS
REDUCES EARLY LIFE FAILURE RATE
REDUCES DEFECT ANALYSIS AND REPAIR COST
PER UNIT
. . . HIGHER QUALITY, LOWER COST, ON TIME
. . . INCREASES CUSTOMER SATISFACTION
REASONS FOR IMPROVING QUALITY
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BUSINESSES WHICH HAVE ACHIEVED
SIGNIFICANT QUALITY IMPROVEMENT EARN 8%HIGHER PRICES.
BUSINESSES WHICH ACHIEVE A SUPERIOR
QUALITY POSITION ARE 3 TIMES MORE
PROFITABLE AS THOSE WITH INFERIOR LEVELSOF QUALITY
BUSINESSES WHICH IMPROVED THEIR QUALITY
GAINED 4% MARKET SHARE PER YEAR
EACH SIGNIFICANT POSITIVE SHIFT IN PROCESSCAPABILITY EQUATES TO A 10 TIMES
IMPROVEMENT IN PROFITABILITY
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What is a Defect?
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What is a Defect?
A defect is any variation of a required characteristicof the product (or its parts) or services which is far
enough from its target value to prevent the product
from fulfilling the physical and functional
requirements of the customer, as viewed through
the eyes of your customer.
A defect is also anything that causes the processor
or the customer to make adjustments.
ANYTHING THAT DISSATISIFIES YOUR CUSTOMER
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DEFINING A UNIT
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A 'unit' may be as diverse as a: Number of equipment
Line of software / harness
Purchase Order raised
Delivery / delay made against invoice Freight cost paid
Inventory every week
Job time card punched
DEFINING A UNIT
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THE COMMON METRIC:
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THE COMMON METRIC:
DEFECTS PER UNIT (DPU)
DPU is the best measure of the overall quality of the
process.
DPU is the independent variable.
Process yields are dependent upon DPU.
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DEFINING A UNIT & Defect
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'unit Defect Number of equipment ------- Rework Type
Line of software / harness ------- Mistake
Purchase Order raised ------- Wrong / missing entry
Invoice -------------------- Payment beyond 60 days Freight cost paid -------Cost more than certain amt.
Inventory every week -- MMI beyond a target value
Job time card punched-- wrong code / missing code
DEFINING A UNIT & Defect
55
Histogram - XYZs arrival at PSW
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Histogram XYZ s arrival at PSW
2 2
3 3
87
5
4
6
2
0
1
2
3
4
5
6
7
8
9
7.55 8
8.05 8.
18.
15 8.2
8.25 8.
38.35 8.
4
56
Sigma level for XYZs arrival
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For 8.28 am ( Upper specification limit )
Defects = 08
Total cases = 42
Defects per unit ( DPU) = 08 / 42 = 0.1904
No. of opportunities (O) = 1
Defect per opportunity (DPO) = DPU / O = 0.1904
Defect per million opportunities (DPMO) = 190,400
Zlt = 0.88
Zst = 0.88+ 1.5 = 2.38 SIGMA LEVEL
57Normal Table
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Z DPO Z DPO Z DPO Z DPO
0.0 0.50
0.1 0.46 1.1 0.136 2.1 0.0179 3.1 0.000968
0.2 0.421 1.2 0.115 2.2 0.0139 3.2 0.000687
0.3 0.382 1.3 0.0968 2.3 0.0107 3.3 0.000484
0.4 0.345 1.4 0.0808 2.4 0.00820 3.4 0.0003370.5 0.309 1.5 0.0668 2.5 0.00621 3.5 0.000233
0.6 0.274 1.6 0.0548 2.6 0.00466 3.6 0.000159
0.7 0.242 1.7 0.0446 2.7 0.00347 3.7 0.000108
0.8 0.212 1.8 0.0359 2.8 0.00256 3.8 0.0000720.9 0.184 1.9 0.0287 2.9 0.00187 3.9 0.000048
1.0 0.158 2.0 0.0228 3.0 0.00135 4.0 0.000032
58Sigma level for error in PO
500 PO h k d
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500 POs are checked.
Defects ( mistakes) = 10
Total POs = 500
Defects per unit ( DPU) = 10 / 500 = 0.0200
No. of opportunities per PO (O) = 5
Total no. of opportunity (5 x500) = 2500
Defect per opportunity (DPO) = 10 / 2500= 0.0040
Defect per million opportunities (DPMO) =DPO x 106
=4000 Zlt = 2.65
Zst = 2.65+ 1.5 = 4.15 SIGMA LEVEL
59Normal Table
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Z DPO Z DPO Z DPO Z DPO
0.0 0.50
0.1 0.46 1.1 0.136 2.1 0.0179 3.1 0.000968
0.2 0.421 1.2 0.115 2.2 0.0139 3.2 0.000687
0.3 0.382 1.3 0.0968 2.3 0.0107 3.3 0.000484
0.4 0.345 1.4 0.0808 2.4 0.00820 3.4 0.0003370.5 0.309 1.5 0.0668 2.5 0.00621 3.5 0.000233
0.6 0.274 1.6 0.0548 2.6 0.00466 3.6 0.000159
0.7 0.242 1.7 0.0446 2.7 0.00347 3.7 0.000108
0.8 0.212 1.8 0.0359 2.8 0.00256 3.8 0.0000720.9 0.184 1.9 0.0287 2.9 0.00187 3.9 0.000048
1.0 0.158 2.0 0.0228 3.0 0.00135 4.0 0.000032
60Normal Table
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Z DPO
4.1 0.0000208
4.2 0.0000134
4.3 0.00000862
4.4 0.00000548
4.5 0.000003454.6 0.00000215
4.7 0.00000133
4.8 0.000000818
4.9 0.0000004195.0 0.000000300
Z DPO
5.1 0.000000180
5.2 0.000000107
5.3 0.0000000627
5.4 0.0000000366
5.5 0.00000002125.6 0.0000000122
5.7 0.00000000698
5.8 0.00000000396
5.9 0.000000002236.0 0.00000000125
6.1 0.000000000694
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No. of opportunities = No. of points checked
If you dontcheck some points then it becomes a passive
opportunity. We should take only active opportunities intoour calculation of DPO, and level.
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Histogram - GR clearance time
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g
195215
151
52
16 10 9 81 3 4 1 2 1
0
50
100
150
200
250
1 2 3 4 5 6 7 8 9 10 11 12 13 14
63sigma level - calculation Target = 4 days
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Target = 4 days
From June 2000 data, out of 668 GRs 55 GRs werecleared in 5 or more days
Number of defects (D) = 55
Number units (U) = 668
Defects per unit (DPU) = 55 / 668 = 0.0823
Opportunities for defects (O) = 1
Defects per opportunity(DPO) = (0.0823 / 1) = 0.0823 Defect per million opportunities (DPMO) = 82300
64Normal Table
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Z DPO Z DPO Z DPO Z DPO
0.0 0.50
0.1 0.46 1.1 0.136 2.1 0.0179 3.1 0.000968
0.2 0.421 1.2 0.115 2.2 0.0139 3.2 0.000687
0.3 0.382 1.3 0.0968 2.3 0.0107 3.3 0.000484
0.4 0.345 1.4 0.0808 2.4 0.00820 3.4 0.0003370.5 0.309 1.5 0.0668 2.5 0.00621 3.5 0.000233
0.6 0.274 1.6 0.0548 2.6 0.00466 3.6 0.000159
0.7 0.242 1.7 0.0446 2.7 0.00347 3.7 0.000108
0.8 0.212 1.8 0.0359 2.8 0.00256 3.8 0.0000720.9 0.184 1.9 0.0287 2.9 0.00187 3.9 0.000048
1.0 0.158 2.0 0.0228 3.0 0.00135 4.0 0.000032
65
Sigma value
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ZLT = 1.4,
ZST = 1.4+1.5 = 2.9 (Current Sigma level)
The target can be to achieve ZST = 4.4 byJanuary 2001.
66Improvement Scale
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308 537
66807
6210
233
Process
capability
23
Defects per million
opportunities
No. of times
improvement
45
3.46
4.6 times
11 times
68 times
26 times
67How Six sigma is different?
Its a systematic & structured way of problem solving that involves measurement
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It s a systematic & structured way of problem solving that involves measurement,analysis & monitoring of performance of a system or a process by using provenstatistical techniques. Some of them are -
1Estimating sigma level 8 Graphical Analysis
2 Rolled through put yield 9 Multi-vari charts
3 Measurement System Analysis 10 Central Limit Theorem
4 Process capability Indices 11 Confidence Interval5 Hypothesis testing 12 Control Charts
6 Correlation and Regression and
7 Design of Experiment 13 Control Plan
THE FOCUS OF SIX SIGMA
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Y = f (X)
TO GET RESULTS , SHOULD WE FOCUS OUR BEHAVIOUR
ON Y OR X ?
Y X1 .............................. XN
DEPENDENT INDEPENDENT
OUTPUT INPUT- PROCESS
EFFECT CAUSE
SYMPTOM PROBLEM
MONITOR CONTROL
IF WE ARE SO GOOD AT X , WHY DO WE CONSTANTLY TEST AND
INSPECT Y ?
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