Page 214 - DMGT524_TOTAL_QUALITY_MANAGEMENT

Unit 14: Statistical Process Control

Self Assessment Notes

Fill in the blanks:
4. Statistical …………………… control provides the statistical techniques necessary to assure
and improve the quality of products.
5. The …………………… of a process is the fraction of output that can be routinely found to
be within specifications.
6. …………………… capability refers to how capable a process is of making parts that are
within the range of engineering or customer specifications.
7. A capability study measures the inherent variability or the …………………… potential of
a process when no assignable causes are present.
8. The …………………… theory of the “central limit theorems says that the averages, of
samples or subgroups follow more closely a normal distribution.

14.4 Control Charts

Statistical Quality Control (SQC) or Statistical Process Control (SPC) for repetitive, high volume
production began in the 1930’s when Shewart developed control charts.

The control chart is the fundamental tool of statistical process control, as it indicates the range of
variability that is built into a system (known as common cause variation). Thus, it helps determine
whether or not a process is operating consistently or if a special cause has occurred to change the
process mean or variance.
The principles behind the application of control charts are very simple and are based on the
combined use of run charts and hypothesis testing. Control charts are used to detect whether a
process is statistically stable. Control charts differentiate variations.

Did u know? Control charts are decision-making tools. They provide an economic basis
for deciding whether to alter a process or leave it alone. Control charts are problem-
solving tools and provide a basis to formulate improvements actions.
They are trend charts with statistically determined upper and lower limits on either side of the
process average. The bounds of the control chart are marked by upper and lower control limits
that are calculated applying statistical formulas to data from the process.
Data points that fall outside these bounds represent variations due to special cause, which can
typically be found and eliminated. On the other hand, improvements in common cause variation
require fundamental changes in the process.
Control charts are powerful aids to understanding the performance of a process over time. They
identify variation. They are time plots that also indicate the range of variation built into the
system. They are used to monitor a process to see whether it is in statistical control.

Control charts help us learn more about process variation. They determine whether a process is
in a state of statistical control or out-of-control. They are used to estimate the process parameters
(mean, variation) and assess the performance of a process or its capability.

Note Control charts are outgrowth of run charts. Run chart records the output result of
a process over time and shows the trends. But they do not distinguish the type of variations.

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