The document discusses the implementation of statistical quality control (SQC) through control charts, which monitor process outputs to identify quality issues. It outlines the types of control charts, distinguishes between chance and assignable causes of variation, and describes their characteristics and benefits. Objectives include aiding in specification settings, production procedures, and quality improvement by providing valuable process data.

1. 1
Statistical Quality Control Charts
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2. Control Charts
Statistical Quality Control can be
implemented through control charts that
are used to monitor the output of the
process and indicate the presence of
problems requiring further action. Control
charts can be used to monitor processes
where output is measured as either
variables or attributes.
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3. Types of control charts
These are of 2 type
–Variable control charts
–Attribute control charts
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4. Basic Principle of Control Charts
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• A process that is operating with only
chance causes of variation present is said
to be in statistical control.
• A process that is operating in the presence
of assignable causes is said to be out of
control.
• The eventual goal of SPC is the elimination
of variability in the process.
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5. Causes ofVariation in Quality
The variation in the quality of product in
any manufacturing process is broadly
classified as:
(a) Chance causes
(b) Assignable causes.
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6. CHANCE CAUSES
These are the causes which are inherit in manufacturing
process by virtue of operational and constructional
features of the equipment's involved in a manufacturing
process. For example:-
1. Machine vibrations
2.Voltage variations
3. Composition variation of material, etc.
They are difficult to trace and difficult to control, even
under best condition of production. Even though, it is
possible to trace out, it is not economical to eliminate.
The chance causes results in only a minute amount of
variation in process. Variation in chance causes is due to
internal factors only the general pattern of variation
under chance causes will follow a stable statistical
distribution (normal distribution). Variation within the
control limits means only random causes are present.
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7. ASSIGNABLE CAUSES
These are the causes which creates ordinary variation in the
production quality. Assignable cause’s variation can always be
traced to a specific quality.They occur due to—
1. Lack of skill in operation
2. Wrong maintenance practice
3. New vendors
4. Error in setting jigs and fixtures
5. Raw material defects
Variation due to these causes can be controlled before the
defective items are produced. Any one assignable cause can result
in a large amount of variation in process. If the assignable causes
are present, the system will not follow a stable statistical
distribution. When the actual variation exceeds the control limits,
it is a signal that assignable causes extend the process and
process should be investigated.
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8. CHARACTERISTICS OF CONTROL CHARTS
A control chart is a time-ordered diagram to
monitor a quality characteristic, consisting of:
1. A nominal value, or center line, the average of
several past samples.
2. Two control limits used to judge whether action
is required, an upper control limit (UCL) and a
lower control limit (LCL).
3. Data points, each consisting of the average
measurement calculated from a sample taken
from the process, ordered overtime. By the
Central Limit Theorem, regardless of the
distribution of the underlying individual
measurements, the distribution of the sample
means will follow a normal distribution. The
control limits are set based on the sampling
distribution of the quality measurement.
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9. BENEFITS OF USING CONTROL CHARTS
1. A control chart indicates when something
may be wrong, so that corrective action
can be taken.
2. The patterns of the plot on a control
chart diagnosis possible cause and hence
indicate possible remedial actions.
3. It can estimate the process capability of
process.
4. It provides useful information regarding
actions to take for quality improvement.
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10. OBJECTIVES OF CONTROL CHARTS
1. To secure information to be used in establishing or
changing specifications or in determining whether
the process can meet specifications or not.
2. To secure information to be used on establishing
or changing production procedures.
3. To secure information to be used on establishing
or changing inspection procedures or acceptance
procedures or both.
4. To provide a basis for current decision during
production.
5. To provide a basis for current decisions on
acceptance for rejection of manufacturing or
purchased product.
6. To familiarize personnel with the use of control
chart.
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11. Terms used in SQC Techniques
• Variables: - are quality characteristics that
can be measured on a continuous scale. For
example, the diameter of a shaft can be
measured by a dial micrometer before taking
a decision regarding the quality i.e. whether
the diameter is within the permissible limits
of variation.
• Attributes: are quality characteristics which
can be classified into one of the two
categories namely good or bad, defective or
non-defective. For example, a painted surface
is good or bad depending on the quality of
the workmanship of the painter and the
quality of the paint used.
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12. Terms used in SQC Techniques contd..
• Chance causes of variation:- are reasons for
minor variations in the quality characteristics that are
inspected. These causes do not cause the item to be
rejected as the variations are within the limits (i.e.
tolerance limits). Chance causes of variation are
inherent in the process.
• Assignable causes of variation:- causes are
external to the process and cause large variation in
quality characteristics making the item liable to be
rejected. For example, defective raw materials, faulty
machine settings, worn out machine parts or worn
out or defective tools cause major variations in
quality characteristics and are called as assignable
causes of variation. Assignable causes must be
identified and eliminated from the process.
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13. Terms used in SQC Techniques Contd..
Type I error: - This is an error in sampling
inspection. A sample from the output of a
process may lead to the conclusion, that the
process is out of control when, in fact it is
operating as intended. Such an error is
known as type I error.
Type II error: - This error occurs, when
the process is not working as intended, but,
sampling error causes one to infer that, the
process is satisfactory.
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14. Terms used in SQC Techniques Contd..
Acceptable quality level (AQL):- is the
maximum percentage or fraction defective, that
is considered as the overall process average.
The lots having quality equal to AQL or better
have a high probability of acceptance (i.e. 0.95).
Lot tolerance percent defective (LTPD):-
is the upper limit of the percentage of defective
products in an individual lot that the consumer
is willing to tolerate, even if the process
average is acceptable. This is also known as
limiting quality level (LQL). Lots having quality
equal to LTPD or worse have a very low
probability of acceptance. (i.e. 0.10)
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15. • Producer’s risk (α): - is the risk of getting
sample which has higher proportion of defectives
than the lot as a whole and thereby rejecting a
good lot based on sample evidence, i.e. a lot as
good as AQL will be rejected by use of a particular
sampling plan. While using acceptance sampling
plans, producers hope to keep this risk (α) as low
as 5%.
• Consumer’s Risk (β):- is the risk of getting a
sample which has a lower proportion of defectives
than the lot as a whole and thereby accepting a
bad lot as a good lot i.e. it is the probability that a
lot with a percentage of defective equal to the
LTPD will be accepted by the sampling plan. While
using sampling plans, consumers want to keep this
risk (β) as low as 10%.
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Terms used in SQC Techniques Contd..

16. • Average outgoing quality (AOQ): - In a
production process, if the lots that are
produced have an average fraction defective
p’ and if some of the lots which are
rejected based on sample evidence are
inspected 100% and the defective units are
either simply removed or replaced with non-
defective ones, the average quality of the
outgoing lots after inspection improves. This
average level of quality leaving the inspection
operation is called average outgoing quality
(AOQ).
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Terms used in SQC Techniques Contd..

17. Introduction to Control Charts
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A typical control chart
has control limits set at
values such that if the
process is in control,
nearly all points will lie
within the upper control
limit (UCL) and the
lower control limit
(LCL).
A typical Control Chart.
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18. 18
Process improvement using the control chart.
Control Charts
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19. THANKYOU
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