Charts for rare events

Article Abstract:

A XmR chart is more useful than a c-chart when it comes to dealing with small numbers, such as rare events, because a one-unit change can show a large difference in percentage. For example, Department 16 averages approximately one spill every seven months. An analysis using a c-chart will not show a great difference in percentage, suggesting that what is happening is normal and does not need any form of intervention. An analysis using an XmR chart shows that the spill is above the upper natural process limit and, therefore, should be remedied.

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Which detection rules should you use?

Article Abstract:

There are a number of detection rules apart from the two most commonly used that are quite useful in analyzing process behavior charts. These include the 'point outside the limits' rule, which may provide data to improve processes, the 'run of eight' rule, which detects small but sustained shifts, and the 'patterns detection' rule, which furnishes data on the source of persistent patterns. These three help supervisors make sense of their data and learn about their processes.

Production Management, Methods, Analysis, Column, Manufacturing processes, Manufacturing, Process control

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Analyze subgroups with average and range charts

Article Abstract:

Average and range charts are special types of control charts using subgroups with homogenous data for analysis. The frame starts with a computation of the averages and ranges of each individual subgroup and plotted in two running records. Averages are plotted on the upper running record while ranges are plotted on the lower running record. Central line limits for each running record are then obtained through averaging.

Models, Mensuration, Measurement, Control engineering

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