2. NAMES OF BOOKS;
Introduction to Statistical Quality Control, Douglas C.
Montgomery, 2nd Edition, Wiley.
Charles E. Ebeling, An introduction to reliability and
maintainability engineering, Tata McGraw-Hill Education.
Quality Planning and Analysis, J.M.Juran and F.M. Gryna,
McGraw Hill
Quality Control, Dale H. Besterfield, 8th Edition,
Pearson/Prentice Hall
Statistical Quality Control, E. L. Grant and Richard S.
Leavenworth, Tata McGraw-Hill
Fundamentals of Quality Control and mprovement,
Amitava Mitra, 2nd Edition,Prentice Hall 1998
Design and Analysis of Experiments, 5th Edition, Douglas
C. Montgomery, Wiley-India 2007
3. QUALITY
“Quality product”- usually think
in terms of an excellent product or
service that fulfills our
expectations.
Expectations are based on
“fitness for use” and the selling
price of the product.*
4. DEFINITIONS
Quality is all of the features and
characteristics of product or
service that contribute to the
satisfaction of a customer’s needs.
These needs involve price, safety,
availability, maintainability,
reliability, and usability.
5. Conformance of the product or
service to these specifications
is measurable and provides a
quantifiable definition of quality.
Therefore, simply stated, quality
is conformance to
specifications and the degree of
conformance is the measure of
quality.
6. Quality control is the use of
techniques and activities to
achieve.
Sustain and improve the quality of
a product or service.
7. IT INVOLVES INTEGRATING THE FOLLOWING
RELATED TECHNIQUES AND ACTIVITIES:
Specifications of what is needed
Design of the product or service to
meet the specifications
Production or installation to meet the
full intent of the specifications
Inspection to determine conformance
to specifications
Review of usage to provide
information for the revision of
specifications is needed
8. STATISTICAL QUALITY CONTROL
It is a branch of quality control. It is
the collection, analysis and
interpretation of data for use in
quality control activities.
A number of different
techniques/tools are needed to
achieve
9. THESE TOOLS ARE;
Shewhart control charts for measurable
quality characteristics. Average and
Range charts, Sample Average and
Standard Deviation
Shewhart control charts for fraction
rejected, or p chart
Shewhart control charts for number of
nonconformities, or c chart
The portion of sampling theory that deals
with the quality protection given by any
specified sampling acceptance procedure.
10. QUALITY ASSURANCE
All the actions necessary to provide
adequate confidence that a product
or service will satisfy consumer
needs is called quality assurance.
It involves making sure that
effectiveness with a view to having
timely corrective measures and
feedback initiated where necessary.
11. QUALITY CONTROL AND QUALITY ASSURANCE.
Quality control is involved with the
activities of specification, design,
production or installation,
inspection, and review of usage.
These activities are the
responsibility of the functional
areas shown in slide no 16.
Quality assurance is involved with
these activities as well as the entire
quality system.
12. HISTORICAL REVIEW
Industrial Revolution- The concept of
specialization of labor
In 1924. W.A. Shewhart of Bell Telephone
Laboratories developed a statistical chart for
the control of product variables. H.F. Dodge
and H.G. Romig both of Bell Telephone
Laboratories, developed the area of
acceptance sampling as a substitute for
100% inspection.
Recognition of the value of statistical quality
control became apparent by 1942.
Unfortunately American managers failed to
recognize its value.
13. In 1946 the American Society for Quality
Control was formed (through its publications,
conferences, and training sessions has
promoted the use of quality control for all types
of production and service).
In 1950 W. Edwards Deming gave a series of
lectures on statistical methods to Japanese
Engineers and on quality responsibility to top
management.
Joseph M. Juran made his first trip to Japan in
1954, Japanese set the quality standards for
the rest of the world to follow.
14. In 1960 the first quality control circles
were formed for the purpose of quality
improvement. Simple statistical
techniques were learned and applied by
Japanese workers.
By the late 1970s and early 1980s
American managers were making
frequent trips to Japan to learn about the
Japanese miracle. Nevertheless a
quality renaissance began to occur in
America’s products and services.
15. RESPONSIBILITY FOR QUALITY
Departments Responsible
Quality is not the responsibility of any one
person or department: it is every one’s job.
Marketing
Marketing helps to evaluate the level of product
quality and the customer wants, needs, and is
willing to pay for. In addition, marketing
provides the customer with product quality
data and helps to determine quality
requirements.
16. Product Service
Packing and
Shipping
Inspection and
Test
Marketing
Product
Engineering
Purchasing
Quality Product
Manufacturing
Manufacturing
Engineering
Departments Responsible for Quality
17. Product Engineering
Product engineering translates the
customer’s quality requirements into
operating characteristics, expect
specifications. (1)
Manufacturing Engineering
Manufacturing engineering has the
responsibility to develop process and
procedures that will produce a quality
product. (2)
18. Manufacturing
Manufacturing has the responsibility to
produce quality products. Quality cannot
be inspected into a product. It must be
build into the product.
Inspection and Test
Inspection and test has the responsibility to
appraise the quality of purchased and
manufactured items and to report the
results. The reports are used to other
departments to take corrective action when
needed.
19. Packaging and Shipping
Responsibility to preserve and protect
the quality of the product. Control of the
product quality must extend beyond
manufacturing to the distribution
installation and product.
Product Service
To provide the customer with the means
for fully realizing the intended function
of the product during its expected life.
This responsibility includes reaction,
maintenance, repair and replacement
parts service.
20. QUALITY ASSURANCE
The quality assurance or quality control
department does not have direct
responsibility for quality. It assists or
supports the other departments as they
carry out their quality control
responsibilities.
Quality assurance does have the direct
responsibility to continually evaluate the
effectiveness of the total quality system.
21. GENERIC ELEMENTS OF A TOTAL
QUALITY SYSTEM ARE:
Policy, planning and administration
Design assurance and design change
control.
Control of purchased material.
User contact and field performance.
Corrective action.
22. QUALITY POLICY AND OBJECTIVE
Quality Policy - overall intentions
and direction of an organisation
related to quality as formally
expressed by top management.
Quality Objective - something
sought, or aimed for related to
quality.
23. To differentiate in simple terms, the
Policy would say "The organisation
would strive to improve customer
satisfaction" - a direction laid down by
the management.
The Objective is a measurable derived
from the Policy. It could say something
like - "Improve on time delivery
performance".
24. THE MAIN PRINCIPLES OF CONTROL CHARTS
1. Measured quality of manufactured product
have always subject to a certain amount of
variation as the result of chance
2. Some constant system of chance causes is
inherent in any particular scheme of
production and inspection
3. Variation within this stable pattern is
inevitable
4. The reasons for variation outside this stable
pattern may be discovered and corrected
25. Computing Cost of Quality
Internal Failure
Scrap
Rework
Scrap/Rework - Supplier
Appraisal
Inspection
Test
Quality audits
Test equipment - initial cost &
maintenance
External Failure
Cost to customer
Warranty costs
Complaint adjustments
Returned material
Prevention
Quality planning
Process planning
Process control
Training
Note: The listed categories provides an understanding of the COQ structure. In
general, COQ is comprised of costs due to failure, appraisal, and prevention.
26. HIDDEN COST OF QUALITY
Internal
Troubleshooting and failure analysis
Evaluation to determine usability of off specification
material
Engineering changes, redesign, buy-offs
Costs of reviewing quality problems (i.e, replanning,
meetings, expediting, firefighting, reports, etc.)
Inventory costs on held material
Overtime because of quality problems
Late shipment premiums (delayed collections)
Material handling
Tool & fixture redesign
Machine wear
Fringe benefits on labor
Loss of productivity due to rework, scrap
27. HOW TO REDUCE QUALITY LOSSES
Rule of “Tens”
Eradicate Killer Re’s…Waste
Play Offense (Prevention) vs.
Defense (Detection)
28. RULE OF “TENS”
Not doing it right the first time
costs ten times as much to find and fix
each time errors escape to a
subsequent stage of handling.
$1 Design Effort
=$10 Production Cost
=$100 Assy/Test Cost
=$1000 Field Cost
30. STATISTICS AND SAMPLING
DISTRIBUTIONS
Statistical methods are used to make
decisions about a process
Is the process out of control?
Is the process average you were given
the true value?
What is the true process variability?
31. STATISTICS AND SAMPLING
DISTRIBUTIONS
Statistics are quantities calculated
from a random sample taken from
a population of interest.
The probability distribution of a
statistic is called a sampling
distribution.
32. DESCRIBING VARIATION
One of the proverb or truism of
manufacturing is that no two
objects are never made exactly
alike.
Variations –very large and
noticeable
Variations – very small and can be
noticed by precision instruments
33. Three categories of variations in piece
part production
1. Within – piece variation: like
surface finish of two portion of the
same piece
2. Piece to piece variation: within
pieces, produced in same time
3. Time-to-time variation: products
produced in different times of the day
34. FIVE CONTRIBUTING FACTORS OF
VARIATION
They are;
1. Processes
2. Material
3. Environment
4. Operators
5. Inspection
35. CHANCE CAUSES OF VARIATION AND
ASSIGNABLE CAUSES
As long as these five sources of
variation fluctuate in a normal or
expected manner, a stable pattern of
many chance causes of variation
develops.
Chance causes of variation are
inevitable and because they are very
small in magnitude. They are difficult
to identify.
36. Those causes of variation which are
large in magnitude, and therefore readily
identified, are classified as assignable
causes.
When only chance causes are present
in a process, the process is considered
to be in control.
However, when an assignable cause of
variation is also present, the variation
will be excessive and the process is
classified as out of control or beyond the
expected normal variation.
37. PATTERN OF VARIATION
As we discussed variations seems inevitable
in nature.
Now it is necessary to have some simple
methods of describing patterns of variation.
Statistician have developed such methods.
One useful method involves a frequency
distribution. Another involves the finding of a
measure of the central tendency of a
distribution (that is, an average) combined
with some measure of dispersion, or spread,
of the distribution.
38. FUNDAMENTALS OF STATISTICS
It has two generally accepted meanings:
A collection of quantitative data pertaining to
any subject or group, especially when the data
are systematically gathered and collated
examples of this meaning are blood pressure
statistics, statistics of a football game,
employment statistics etc.
The science that deals with the collection,
tabulation, analysis, interpretation, and
presentation of quantitative data.
39. The use of statistics in quality
control deals with the second and
broader meaning and involves the
divisions of collection, tabulating,
analyzing, interpreting and
presenting the quantitative data.
Each division is depended on the
accuracy and completeness of the
preceding one.
40. There are two phases of statistics:
Descriptive or deductive statistics,
which endeavors to describe and
analyze a subject or group.
Inductive statistics which endeavors to
determine from a limited amount of
data (sample) an important conclusion
about a much larger amount of data
(population).*
41. COLLECTION OF DATA
Data may be collected by
direct observation or indirectly
through written or verbal
questions*.
Data that are collected for
quality control purposes are
obtained by direct observation
and are classified as either
variables or attributes.
42. Variables are those quality
characteristics which are
measurable, such as a weight
measured in grams.
Attributes, on the other hand are
those quality characteristics
which are classified as either
conforming or not conforming to
specifications such as a “go / no
go gage”.
43. A variable that is capable of any degree
of subdivision is referred to as
continuous. The weight of a gray iron
casting which can be measured as 11 kg,
11.33 kg or 11.3398 kg (25 ib), depending
on the accuracy of the measuring
instrument, is an example of a continuous
variable.
Measurements such as meter (feet), liters
(gallons) and Pascal’s (pounds per
square inch) are examples of continuous
data.
44. Variables that exhibit gaps are
called discrete. The number of
defective rivets in a travel trailer
can be any whole number, such
as 0,3,5,10,96…..however, there
cannot be say 4.65 defective
rivets in a particular trailer.
In general, continuous data are
measurable, while discrete data
are countable.
45. Describing the Data
In industry, business and government
the mass of data that have been
collected is voluminous.
There are a number of different ways to
present the frequency distribution.
Two techniques are available to
accomplish the summarization of data-graphical
and analytical.
46. Graphical techniques is a plot or picture
of a frequency distribution, which is
summarization of how the data points
(observations) occurs within each
subdivision of observed values or groups
of observed values.
Analytical techniques summarize data by
computing a measure of central
tendency and a measure of the
dispersion.
47. FREQUENCY DISTRIBUTION
UNGROUPED DATA-Comprise
a listing of the
observed values
GROUPED DATA- Lumping
together of the observed
values
51. GROUPED DATA
The construction of a frequency distribution for
grouped data is more complicated because
there are a large number of data values.
Process is as follows;
1. Collect data and construct a tally sheet
2. Determine the range
3. Determine the cell interval
4. Determine the cell midpoints
5. Determine the cell boundaries
6. Post the cell frequency