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Exam 3: Statistical Process Control

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Question 31

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One advantage of using a pattern test is that special cause variations may be identified before any points are plotted outside the control limits.

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Question 32

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Statistical process control is a subset of statistical quality control.

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Question 33

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A p-chart is used to monitor the proportion defective in the output of a process.

Tolerances reflect the amount of common cause variation allowed in a process.

Special cause variation in a process is more likely to be detected with

When monitoring a process's output with a quantitative variable either an R-chart or an -chart is used,but never both.

A process capability ratio greater than one shows that a process is capable of producing output within its specification limits.

The process capability index indicates how much a process mean differs from the target specification value.

Control charts visually show when a process is not within statistical control limits.

Control chart sample sizes are becoming smaller because it is easier to detect a pattern with Excel or other data analysis software.

Statistical process control is only effective for service processes.

If a pattern is evident in the points plotted on a control chart,the points are always considered evidence that the process is in control.

A control chart that uses the actual number of defects per item to monitor a process is known as a

If the quality of a process's output is determined by the average value of a sample,use a(n) ___ control chart.

Which of the following control charts is based on the number of defects within a sample?

In some cases,the -chart is used without the R-chart because the within sample variation is not of concern.

The popularity of Excel and other data analysis software has been a major factor in the increased use of statistical process control.

Process control is achieved by taking periodic samples from a process and plotting the sample points on a chart to determine if the process is within control limits.

Employee training in statistical process control is a fundamental principle in total quality management programs.

All processes contain a certain amount of variation in their output.