Introduction and Basic Concepts SPC.ppt

for manaufactueres

1. Introduction
1
What is SPC?
SPC is not really about
statistics or control, it is
about competitiveness
Organizations compete on three
issues; Quality, Delivery and Price.
Background

2. Introduction
.
SPC is:
 a Management tool
 an Analytical tool
 a Communication tool
 a Strategic tool
2

3. 3
Introduction
 As a Management tool

SPC mitigates business threats
(mounting pressure) from globalization and
trade liberalization

4. 4
Introduction
Hence, there is a quest for;
Local & global competitiveness,
Technological dynamism,
Fast changing customer requirements on
quality and,
Stringent regulatory requirements as well
as social and legal priorities
(safety ,environmental protection, etc. )

5. 5
Introduction
As an Analytical tool
SPC ensures customer satisfaction by
aligning
voice of the process with the voice of the
customer
Control limits with specification limits
What the process is doing with what we
want the process to do

6. 6
Introduction
How?
Identification, measurement, analysis and
control of all root causes of variation in
processes and operations to maximize the
value added
Improve process efficiency and
effectiveness
Enhance professional competence
Support continual improvement

7. 7
Introduction
As a Communication tool
SPC:
Improves enterprise – wide
information system
Develops trust & partnership
Becomes resource for bench marks
and proven best practices

8. 8
Introduction
As a Strategic Tool
SPC helps in developing , implementing ,
maintaining and improving appropriate
management systems; such as:
Quality Management System
(ISO 9001:2008)
Food Safety Management System
Laboratory Management System
Environmental Management System

9. 9
Introduction
Can be used on one-time basis to solve
specific quality problems or as an
improvement initiative provided that, it
becomes a way of life in work places
Relevance
SPC is relevant to organizations of all types &
sizes.
If properly implemented:

10. 10
•Introduction
What is a Process?
A Process is the transformation
of a set of Inputs into desired
Outputs, in the form of Products,
information, services or-
generally-Results.

11. 11
Introduction

Input
Process
(Set of Value-adding activities)
Efficiency & Effectiveness
(SPC)
Output
Resources
Constraints

12. 12
Introduction
What is Statistical Process Control and
it’s purpose ?
SPC is a:
practical application of statistical principles
in management, engineering and process
control systems
statistical technique for the identification,
measurement, analysis and control of all
causes of variation in any process, that
attains an output in goods, software and
services

13. 13
Introduction
 Identifying and eliminating the
special causes of variation with
the objective of bringing a process
into a state of statistical control
Principal purpose of SPC

14. 14
Introduction
Moreover, SPC tools help to:
Measure the performance of
operations both before and after
corrective actions have been taken,
to break through to a new, improved
level of performance
predict how well the operation will
run in the future.

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Introduction
Benefits of SPC
Process stability
Powerful problem solving tool
Cost savings / Elimination of Waste
Process Selection
Process improvement
Quality Improvement
Visual management
Factual decision making

16. 16
Introduction
Process stability
The capability of a process to meet
customer specifications is
determined by the stability of the
process, the ranges of variation,
and the process aim point.

17. 17
Introduction
Powerful problem solving tool
Define an issue or problem in depth,
Brainstorm on the root causes and effects,
Identify potentials for improvement and
 Aid teams in evaluating a situation or
available alternatives through analysis of
strengths versus weaknesses,
opportunities versus threats and costs
versus benefits/risks.

18. 18
Introduction
Cost savings / Elimination of Waste
Reduced reject, rework and defects,
Reduced inspection and intensive
supervision
Overall improvement in quality.
Process Selection
select a process whose capability
matches the quality requirements of the
job.

19. 19
Introduction
Process improvement
Principle of commitment to continually
improve a process.
Quality Improvement
the transition from process control
(keeping the process under control) to
quality control (keeping the process within
the limits of customer specification) is an
improvement action.

20. 20
Introduction
Visual management
‘One picture is worth a thousand
words.’
Use statistical techniques to display
targets and performance data in a
visible place as possible and update
regularly to show achievements or
failures.

21. 21
Introduction
Factual decision making
Decisions based on facts instead of giving
opinions
Look for the root cause rather than
the immediate apparent (and often
wrong) effect.
Switch the ‘search light’ to determine the
correct action.

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BASIC CONCEPTS & PRINCIPLES
The Nature of variation
Variation is the inevitable difference that
exists among individual outputs of a
repeatable process,
It is found in many, if not all, processes.
The closer an item is examined, the more
differences are found,
No two objects are exactly alike.
It is the concept of variation that forms
the basis for statistics, probability and
process control.

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BASIC CONCEPTS & PRINCIPLES
Causes of variation
Two types of causes:
1) Special/Assignable cause
2) Common/Random cause

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BASIC CONCEPTS & PRINCIPLES
1. Special cause
They are causes that are not always
present
Wrong materials, inaccurate measuring
device, worn-out tool, sick employee,
weather conditions, accident, stage
omitted-all one-off events that can not be
predicted.
When they occur they make the shape,
spread or location of the average change.
The process is not predictable while
special cause variation is present.

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BASIC CONCEPTS & PRINCIPLES
Special cause contd.
A stable process is one with no indication
of a special cause of variation and can be
said to be in statistical control.
Special cause variation is not random, it is
unpredictable. It occurs because
something has happened, so you should
search for the cause immediately and
eliminate it.

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BASIC CONCEPTS & PRINCIPLES
2. Common cause
Once the special cause of variation has
been removed, the variation present is left
to chance, it is random or what is referred
to as common cause.
The random variation is caused by factors
that are inherent in the system.

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Common cause contd.
The operator has done all he/she
can do to remove the special
causes, the rest are down to
management.
The variation could be caused by
poorly designed working
environment, equipment
maintenance or inadequacy of
information.
BASIC CONCEPTS & PRINCIPLES

28. 28
BASIC CONCEPTS & PRINCIPLES
Stabilizing process
Removal of Special
cause
Process stabilizing (variation due
to common cause)
Proportions of
nonconformities
Time
Figure 2.1 Stabilizing process

29. Summary
Special Cause of VariationsCommon cause of Variations
Are transient in nature and
affects only some products,
Are inherent in the system
and affect all products,
Influence both predictability
and capability of the process,
Influence only capability not
predictability of the process,
Result in unpredictable
process (out of statistical
control),
Possess a pattern of variation
which is stable ( in statistical
control),
Can be removed by taking
corrective actions.
Can only be removed by
changing or making
modification to the process.
29

30. 30
BASIC CONCEPTS & PRINCIPLES
Principles of SPC
Principle 1:
No two things are exactly alike
All processes have their inherent
variability which can not be avoided.
No machine or process, however, accurate
and well programmed, can produce
identical parts or jobs.

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BASIC CONCEPTS & PRINCIPLES
Principle 2:
Variation in a product or
process can be measured
measure the output of any process or
operation to know when trouble is
brewing.

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BASIC CONCEPTS & PRINCIPLES
Principle 3:
Things vary according to a definite
pattern

This pattern is sometimes called a
frequency distribution

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BASIC CONCEPTS & PRINCIPLES
Principle 3 contd.
x
x
x x x
x x x x
x x x x x x
x x x x x x x
x x x x x x x x
x x x x x x x x x x x
1 2 3 4 5 6 7 8 9 10 11 12
Frequency distribution

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BASIC CONCEPTS & PRINCIPLES
Principle 3 contd.
If you enclose the tally marks in a curved
line, frequency distribution curve is
formed. This curve shows that there are
more measurements or numbers in the
middle and fewer as you go away from the
middle. As you can see, the curve is
shaped like a bell.

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Principle 3 contd.
1 2 3 4 5 6 7 8 9 10 11 12
Bell-shaped curve
BASIC CONCEPTS & PRINCIPLES

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BASIC CONCEPTS & PRINCIPLES
Principle 4:
Whenever things of the same
kind are measured, a large group
of the measurements will tend to
cluster around the middle.

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BASIC CONCEPTS & PRINCIPLES
Principle 4 contd.
Most measurements fall close to the
middle.
 The percentage of measurements in
various sections of the frequency
distribution curve is shown in
normal distribution (bell) curve.

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BASIC CONCEPTS & PRINCIPLES
X
XX
Approximate percentages of different
measurements within the normal distribution curve.
Principle 4 contd.
XXXX
X
X X XXX
-3∂
-2∂- ∂ +∂ +2∂ +3∂
2%

14%
34%

34%
14%
2%

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BASIC CONCEPTS & PRINCIPLES
The three characteristics of a normal
distribution curve are:
 The Mean = Median = Mode
The curve is symmetrical; the curve is a
mirror image along the vertical axis at the
mean value;
The area under the curve is equal to 1 (or
100%).

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BASIC CONCEPTS & PRINCIPLES
The Bell Curve informs you that:
Curve Height: the height of the curve at
any point is related to the probability of
occurrence for a particular value
Curve Width: if the sample standard
deviation is large, the Bell Curve will be
wide. If the sample standard deviation is
small, the Bell Curve will be narrow.

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BASIC CONCEPTS & PRINCIPLES
Area under the Curve
The percentage of normally distributed data that
fall under the curve can be predicted as follows;
 1∂ = 0.6826 or approximately 68 % of t
total area
2∂ = 0.9544 or approximately 95 % of the
total area
 3∂ = 0.9974 or approximately 97.7 % of
the total area

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BASIC CONCEPTS & PRINCIPLES
If we measure each piece that
comes from a machine or operation
and make a tally of the
measurement, we will eventually
have a curve similar to the bell-
shaped curve.

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BASIC CONCEPTS & PRINCIPLES
Principle 5:
It is possible to determine the shape
of the distribution curve for parts
(outputs) produced by any process
In this way we can learn what the
process is doing, as compared to what we
want it to do.

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BASIC CONCEPTS & PRINCIPLES
Principle 6:
Variation due to special (assignable)
causes tends to distort the normal
distribution curve
When assignable (special) causes of
variation are present, the curve will be
distorted and lose its normal bell
shape.

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BASIC CONCEPTS & PRINCIPLES
Principle 6 Contd
Tails of the distribution are Tails of the distribution are
chopped off. Parts were chopped off. Parts were
probably sortedprobably sorted
Measurement from two
different Sources
Normal distributionNormal distribution Measurements tail-off Measurements tail-off
to the to the rightright
Measurements from two Measurements from two
different groups that overlapdifferent groups that overlap
Measurements tail–off Measurements tail–off
to the to the leftleft
Distortions of the normal curve

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BASIC CONCEPTS & PRINCIPLES
Statistics and Statistical Data
The Meaning of Statistics
 It can refer to facts which can be put into a
numerical form, as in the
“unemployment statistics.”
 It can also refer to statistical methods,
which are devices for classifying
numerical statements of facts making clear
the relations.

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BASIC CONCEPTS & PRINCIPLES
Data
Data are numerical measures that provide
helpful information on how well a process
is or is not performing and what action (s)
need to be taken.
A number of tools can be employed to
interpret data and then correct and even
improve process; Check Sheets, Pareto
Charts, Run Charts, Histograms and
Control Charts.

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BASIC CONCEPTS & PRINCIPLES
The Nature of Statistical Data
Statistics can deal with numerical
data. Data of a qualitative nature
can be put into a quantitative form.
E.g Health might be measured by
the number of days illness
BASIC CONCEPTS & PRINCIPLES

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BASIC CONCEPTS & PRINCIPLES
Steps in Statistical Inquires
1.The problem must be clearly stated
2.Selection of the sample/Size of the
sample & method of sampling
3.Drafting the questionnaire.
4.Collection of data
5. Editing the schedules/
Questionnaires need to be checked and
sometimes coded

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BASIC CONCEPTS & PRINCIPLES
Steps in Statistical Inquires…

6. Organization of data
7. Analysis and interpretation
8. Presentation
9. Writing of the report

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BASIC CONCEPTS & PRINCIPLES
Collection of Data
Primary and Secondary Data
Data may be expressly collected for the
purpose required. Such data are known as
primary data.
Data collected for some other purposes,
frequently for administrative purposes, is
known as secondary data. Secondary data
must be used with great care.

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BASIC CONCEPTS & PRINCIPLES
Great attention must be paid to the
precise coverage of all information in the
form of secondary data.

The type of data you have will most often
dictate the tool to use, and the right tool
is a key step toward solving or improving
processes.

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BASIC CONCEPTS & PRINCIPLES
Why Collect Data?
Data are collected to:

Reveal a problem - you cannot solve what you do
not know.
Analyze a problem - solve the root cause and not
the symptom
Monitor and control a problem - Ensure that what
you solve remains so.
Prevent a problem -Prevention of problems creates
lower cost, higher quality and production.

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BASIC CONCEPTS & PRINCIPLES
How much data to collect?
Consider the following issues while
deciding how much data to collect :

What data do you already have?
How much data do you think will be
necessary to detect cycles or
patterns?
What resource constraints are
there?

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BASIC CONCEPTS & PRINCIPLES
Word Data always requires that
you collect as much as you can
get.
Individual Data Point requires
50 to 100 observations.
Paired Data requires 25 to 50
paired data sets.

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BASIC CONCEPTS & PRINCIPLES
Points to Consider in Collecting Data
Clarify the problem ensuring that the
process being studied is completely
understood.
Data often needs to be stratified;
separated out by days or machines, or
types, or a category that fits the situation.
Keep in mind the purpose of what it is
you’re doing.

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BASIC CONCEPTS & PRINCIPLES
Collect only the relevant data needed
and keep it simple and use a time
limit.
Remember that collecting data is
costing the organization money, time
and other types of resources, so do
not collect too much as this will cause
an information overload situation.

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BASIC CONCEPTS & PRINCIPLES
Attempt to collect your historic data first
and use it as an initial baseline of past and
recent performance.
Plan your data collection, get authority
where needed, assign data collection,
analysis and interpretation roles, and
think about assigning someone to graph
the data.

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BASIC CONCEPTS & PRINCIPLES
2.7 Recording Data
Category Measures
Quality Mistakes, Failures, Complaints, Returned
items, Repairs.
People Grade, Age, Experience, Skill(s), Individual.
Equipment Machines (PC, Copiers, TVs), Phones,
Buses, Trucks, Ovens, Tools, Instruments
Material Resins, Paints, Medications, Thermometers,
Books, Papers, Videos, Software.
Procedure/
Policy
Conditions, Orders, Arrangements,
Methods.

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BASIC CONCEPTS & PRINCIPLES
Category Measures
Environment Building, Room Temperature, Humidity,
Lightness, Darkness, Physical, Social,
Psychological, Ergonomics and
Atmospheric Composition.
Cost Time, Expenses, Over Production,
Inappropriate Processing, Unnecessary
Inventory.
Delivery Shortage, Instruction, Defaults in
Payments, Delays, Time Spent Waiting.
Safety Accidents, Mistakes, Breakdowns, Near
Misses, Hazards, Incidents.

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BASIC CONCEPTS & PRINCIPLES
Statistical measures
Measures of Location
Mean, Mode and Median
These show the centering of the values of
a group of data points and are also called
measures of central tendency.

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BASIC CONCEPTS & PRINCIPLES
Discrete Data Points
Example 1
Using the following data, calculate
the Mean, Mode and Median
10 63 32 21 30 2 13 19
9 15 50 24 50 21 15 35
52 8 33 27 22 40 28 42

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BASIC CONCEPTS & PRINCIPLES
Mean= 27.542
Median = 25.5
Mode: 15 occurs twice
21 occurs twice
50 occurs twice
In this case there are three Modes; 15, 21 and 50.

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BASIC CONCEPTS & PRINCIPLES
Measures of Variation
Range, Standard Deviation and the Shape of
the distribution
These show how the values of a group of
data points vary from one another or from
the centering.

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BASIC CONCEPTS & PRINCIPLES
Range
The difference between the highest and
lowest value of a group of data points
In the example above the range is 63 - 2 = 61
The limitation of the range as a measure of
variation is that it compares only the two
extreme sets of data points; the highest and
the lowest values.

R=X
max
– X
min

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BASIC CONCEPTS & PRINCIPLES
Standard Deviation
The Standard Deviation measures
the average amount each individual
point varies about the Mean.
The closer to the Mean each point is,
then the less variation there is
present. It takes every data point
into consideration unlike the range.

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BASIC CONCEPTS & PRINCIPLES
The mean identifies the location of
the center of the distribution and
the standard deviation identifies the
variation of every data point from
that mean.
In the example above, the sample
standard deviation is equal to
15.827

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BASIC CONCEPTS & PRINCIPLES
Example 2
For both data sets A and B below, calculate
the Range, the Mean, and the sample
Standard deviation.
A 10 8 12 911
B 6 14 5 15 10
Range:
RA 12 – 8 = 4
RB 15 – 5 = 10

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BASIC CONCEPTS & PRINCIPLES
Mean:
For A= 10
For B= 10
The Mean for both A and B is the same
5
)11912810( 

AX

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BASIC CONCEPTS & PRINCIPLES
Standard Deviation
For A = 1.581
For B= 4.527
Note: The Mean for both A and B was the
same but the standard deviation shows that
B is much more variable than A

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BASIC CONCEPTS & PRINCIPLES
2.9.2.1 Grouped Data Points
Example 3
Find the Range, the Mean, the Mode, the Median and
the Standard Deviation for the following grouped
data points.
Value (Xi) Frequency (fi)
5 5
10 2
12 1
15 3
20 1
Calculate the Mean, Mode, Median, Range, and
Standard deviation

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BASIC CONCEPTS & PRINCIPLES
Mean = 10.167
Mode = 5
Median= 10
Range = 15
Standard deviation = 5.254
BASIC CONCEPTS & PRINCIPLES

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BASIC CONCEPTS & PRINCIPLES
ETHIOPIAN STANDARDS
AGENCY

74. Questions??
Recap
74