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264 Part IV: Quality AssuranceCL = xLCL = x = 3sˆxsˆ= x 3nR= x 3d n2= xA R2(19.7)(19.8)where the values of A 2 and d 2 for various sample sizes are givenin Appendix E.Note: Instead of calculating three-sigma limits (common inthe United States), we can also calculate the probability limits(common in Europe) at the desired level of significance a simplyby replacing 3 with z a/2 in equations (19.6) and (19.8). Thus, thecontrol limits will bePart IV.B.3UCL = x+z= x+zLCL = xz= xza / 2a / 2a / 2a / 2sˆnRd2sˆnnR.d nStep 4. Calculate the control limits for the R control chart:UCL = R + 3sˆ2= R+3d R 3d d 3= + 1 3d R= DR4R22(19.9)(19.10)(19.11)CL = R(19.12)
Chapter 19: B. Statistical Process Control 265LCL = R 3sˆR= R3d R 3d d 3= 1 3d R= DR322(19.13)where the values of D 3 and D 4 for various sample sizes are given inAppendix E. The first implementation of control charts is referredto as phase I. In phase I, it is important that we calculate thepreliminary control limits. The preliminary control limits arecalculated to find the extent of variation in sample means and sampleranges if the process is stable. In other words, at this point, onlycommon causes would be affecting the process. If all of the plottedpoints fall within the control limits and there is no evidence of anypattern, then it means the control limits are suitable for the currentor future process. However, if some points exceed the control limits,then such points are ignored and every effort is made to eliminateany evident special causes that may be present in the process. Thenfresh control limits are calculated by using the remaining data andthe whole process is repeated again. Remember that ignoring thepoints that exceed the control limits without eliminating the specialcauses may result in unnecessarily narrow control limits, which maycause different kinds of headaches such as putting points beyondthe control limits when, in fact, they should not be. Furthermore, it ishighly recommended that for preliminary control limits, we use atleast 25 samples of size four or five. Otherwise, the control limits maynot be suitable for the current and future process.Part IV.B.3EXAMPLE 19.4Table 19.3 provides the data on the diameter measurements of ball bearings used inthe wheels of heavy construction equipment. Twenty five samples each of size fourare taken directly from the production line. Samples come from all three shifts and nosample contains data from two or more shifts. Use this data to construct an X – and Rchart and to verify that the process is stable.Solution:From Appendix E for sample of size n = 4, we have D 3 = 0, and D 4 = 2.282. Thus, thecontrol limits for the R chart areLCL = DR3= 0× 0.03479 = 0UCL = DR= 2. 282× 0. 03479 = 0.07936.4Continued
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264 Part IV: Quality Assurance
CL = x
LCL = x = 3sˆ
x
sˆ
= x 3
n
R
= x 3
d n
2
= x
A R
2
(19.7)
(19.8)
where the values of A 2 and d 2 for various sample sizes are given
in Appendix E.
Note: Instead of calculating three-sigma limits (common in
the United States), we can also calculate the probability limits
(common in Europe) at the desired level of significance a simply
by replacing 3 with z a/2 in equations (19.6) and (19.8). Thus, the
control limits will be
Part IV.B.3
UCL = x+
z
= x+
z
LCL = x
z
= x
z
a / 2
a / 2
a / 2
a / 2
sˆ
n
R
d
2
sˆ
n
n
R
.
d n
Step 4. Calculate the control limits for the R control chart:
UCL = R + 3sˆ
2
= R+
3d R 3
d
d
3
= +
1 3
d
R
= DR
4
R
2
2
(19.9)
(19.10)
(19.11)
CL = R
(19.12)