Control charts (also called Shewhart charts) are a powerful statistical quality control tool used for online process monitoring. Control charts detect assignable causes of variation by monitoring the process for points outside the natural limits called control limits. This ensures variations are kept within specification limits, delivering more consistent quality. There are different types of control charts for variables and attributes. Control charts must be acted on if points fall outside control limits or show non-random patterns, indicating the presence of assignable causes that need investigation and elimination.

1. CONTROL CHARTS
(SHEWHART CHARTS)
A presentation by
THE SOCIETY
OF
STATISTICAL QUALITY CONTROL ENGINEERS
BHOPAL

2. WHAT IS CONTROL CHART
A powerful SQC tool for on-line
process control

3. HOW CONTROL CHART WORKS
Control Chart detects assignable causes ( also called special
causes )
in the process. Once the assignable causes are eliminated, the
process runs under the influence of chance causes alone and the
process is said to be under statistical control. Variations are, then,
controlled within natural limits called “control limits” which are
generally narrower than the specification limits.
CONTROL CHARTS ADVANTAGES
(1) Control chart prevents defects in the process
(2) Control chart keeps the variations to a minimum, generally
narrower than the specification limits.
The result : process delivers better and consistent quality
products.

4. UNDERSTANDING CHANCE CAUSES AND
ASSIGNABLE CAUSES OF VARIATION
 Variation is inevitable in any process /operation/component
 Variations occur due to the following two causes:
(i) Chance causes
(ii) Assignable causes

5. VARIATION DUE TO CHANCE CAUSES
(Also called natural variation or inherent variation)
• These variations are due to a large number of factors which are either
uncontrollable or uneconomical to control.
Examples of such factors are: temperature, humidity variations, variation in
other environmental conditions, slight variations in raw material etc.
• These variations are unavoidable. It is not possible to enumerate each and
every chance cause and eliminate it.
• The factors causing chance variations are many, but the effect of a single
cause is very less. Variation due to chance cause is the sum total of
variations due to all chance causes – known or unknown.
• Variations due to chance causes follow certain standard probability
distributions like Normal distribution in case of variable type of data and
binomial/poisson distribution in case of attribute type of data.

6. VARIATION DUE TO ASSIGNABLE CAUSES
(Also called variation due to special causes/
unnatural causes)
• These variations are due to just one or few individual causes.
• Even a single assignable cause results in a large variation.
• Assignable causes being few, they can be detected and
eliminated.
• Examples of assignable causes: variations due to defective raw
material, faulty setup or untrained operator.
• Variations due to assignable causes do not follow any probability
distribution and hence they can easily be “singled out” from
chance variations.

7. CONTROL CHART TYPES
(1) Control charts for VARIABLES
(2) Control charts for ATTRIBUTES

10. CONTROL CHART FOR ATTRIBUTES
CONTROL CHART TYPE QUALITY CHARACTERISTIC
p – chart Proportion defective or percent defective
np – chart Number of defectives
c – chart Number of defects in a defined “unit”
u – chart Number of defects per piece

16. WHEN TO ACT ON A CONTROL CHART
The requirements in a control chart are:
(i) All the points should lie within control limits
(ii) The points should be randomly distributed.
(i.e. the points should not depict any rising/falling trend, cyclic
pattern, clustering of points above or below central line, shift of
process average etc.)
Violation of either of the above two conditions indicates presence
of assignable cause in the process which must be investigated and
eliminated.
In case of p-chart/np-chart/c-chart/u-chart, if a point goes below the
lower control limit, it should not be ignored thinking that it is an
improvement. The cause of improvement must be investigated and if it
is true, the same should be implemented in the process.

18. RUN CHART

19. WHAT IS A RUN CHART
Run chart is a process control chart much simpler but less powerful than control chart.
Run charts generally precede control charts.
In a run chart individual observations (not averages) are plotted on time scale in order
of production. The chart shows central line (nominal value) and specification limits.
WHEN TO ACT ON A RUN CHART
The requirements in a run chart are:
(i) All the points should lie within specification limits
(ii) The points should be randomly distributed.
Violation of either of the above two conditions calls for investigation and corrective action.