The following notation is used in this section:
u |
expected number of nonconformities per unit produced by process |
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number of nonconformities per unit in the ith subgroup. In general, . |
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total number of nonconformities in the ith subgroup |
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number of inspection units in the ith subgroup |
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average number of nonconformities per unit taken across subgroups. The quantity is computed as a weighted average:
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N |
number of subgroups |
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has a central distribution with degrees of freedom |
Each point on a u chart indicates the number of nonconformities per unit () in a subgroup. For example, Figure 17.94 displays three sections of pipeline that are inspected for defective welds (indicated by an X). Each section represents a subgroup composed of a number of inspection units, which are 1000-foot-long sections. The number of units in the ith subgroup is denoted by , which is the subgroup sample size.
Figure 17.94: Terminology for c Charts and u Charts
The number of nonconformities in the ith subgroup is denoted by . The number of nonconformities per unit in the ith subgroup is denoted by . In Figure 17.94, the number of defective welds per unit in the third subgroup is .
A u chart plots the quantity for the ith subgroup. A c chart plots the quantity for the ith subgroup (see CCHART Statement: SHEWHART Procedure). An advantage of a u chart is that the value of the central line at the ith subgroup does not depend on . This is not the case for a c chart, and consequently, a u chart is often preferred when the number of units is not constant across subgroups.
On a u chart, the central line indicates an estimate of u, which is computed as by default. If you specify a known value () for u, the central line indicates the value of .
You can compute the limits in the following ways:
as a specified multiple (k) of the standard error of above and below the central line. The default limits are computed with k = 3 (these are referred to as limits).
as probability limits defined in terms of , a specified probability that exceeds the limits
The lower and upper control limits, LCLU and UCLU, respectively, are given by
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The limits vary with .
The upper probability limit UCLU for can be determined using the fact that
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The limit UCLU is then calculated by setting
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and solving for UCLU.
Likewise, the lower probability limit LCLC for can be determined using the fact that
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The limit LCLC is then calculated by setting
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and solving for LCLC. For more information, refer to Johnson, Kotz, and Kemp (1992). This assumes that the process is in statistical control and that has a Poisson distribution. Note that the probability limits vary with and are asymmetric around the central line. If a standard value is available for u, replace with in the formulas for the control limits.
You can specify parameters for the limits as follows:
Specify k with the SIGMAS= option or with the variable _SIGMAS_
in a LIMITS= data set.
Specify with the ALPHA= option or with the variable _ALPHA_
in a LIMITS= data set.
Specify a constant nominal sample size for the control limits with the LIMITN= option or with the variable _LIMITN_
in a LIMITS= data set.
Specify with the U0= option or with the variable _U_
in a LIMITS= data set.