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Next, the upper control limit (UCL) and lower control limit (LCL) for the individual values (or upper and lower natural process limits) are calculated by adding or subtracting 2.66 times the average moving range to the process average: = ¯ + ¯.
Process capability studies do examine the relationship between the natural process limits (the control limits) and specifications, however. The purpose of control charts is to allow simple detection of events that are indicative of an increase in process variability. [12]
The control limits are set at three standard deviations on either side of the process mean, and are known as the upper control limit (UCL) and lower control limit (LCL) respectively. [2] If the process data plotted on the control chart remains within the control limits over an extended period, then the process is said to be stable. [2] [3]
The importance of knowing the natural process variation becomes clear when we apply statistical process control. In a stable process, the mean is on target; in the example, the target is the filling, set to 1 litre. The variation within the upper and lower control limits (UCL and LCL) is considered the natural variation of the process.
The Western Electric rules are decision rules in statistical process control for detecting out-of-control or non-random conditions on control charts. [1] Locations of the observations relative to the control chart control limits (typically at ±3 standard deviations) and centerline indicate whether the process in question should be investigated for assignable causes.
Nelson rules are a method in process control of determining whether some measured variable is out of control (unpredictable versus consistent). Rules for detecting "out-of-control" or non-random conditions were first postulated by Walter A. Shewhart [1] in the 1920s.
The control limits for this chart type are ¯ ¯ (¯) where ¯ is the estimate of the long-term process mean established during control-chart setup. [ 2 ] : 268 Naturally, if the lower control limit is less than or equal to zero, process observations only need be plotted against the upper control limit.
In statistical process control (SPC), the ¯ and R chart is a type of scheme, popularly known as control chart, used to monitor the mean and range of a normally distributed variables simultaneously, when samples are collected at regular intervals from a business or industrial process. [1]
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