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Refer to the data of Exercise 22, and construct a control chart using the\(si{n^{ - 1}}\)transformation as suggested in the text.

Short Answer

Expert verified

The process is out-of-control.

Step by step solution

01

 Given Information

See the text for the transformation. Mean value of the given transformation

\(Y = h(X) = {\sin ^{ - 1}}\left( {\sqrt {\frac{X}{n}} } \right)\)

is given by

\({\sin ^{ - 1}}(\sqrt p )\)

and variance

\(\frac{1}{{4n}}.\)

The values using the inverse transformation (arcsin) are

02

Calculate the limits

\(i\) \({\sin ^{ - 1}}(\sqrt p )\)

\(\begin{aligned}{*{20}{l}}{1\;\;0.22551}\\{2\;\;\;0.30469}\\{3\;\;\;0.35374}\\{4\;\;\;0.29584}\\{5\;\;\;0.44462}\\{6\;\;0.31332}\\{7\;\;0.18819}\\{8\;\;0.36137}\\{9\;\;0.23673}\\{10\;0.35374}\\{11\;0.39065}\\{12\;0.27741}\end{aligned}\)

\(\begin{aligned}{*{20}{l}}{13\;\;0.28676}\\{14\;\;\;0.32999}\\{15\;\;0.30469}\\{16\;\;0.29584}\\{17\;\;0.27741}\\{18\;\;0.33807}\\{19\;\;0.24747}\\{20\;\;\;0.32175}\\{21\;\;0.29584}\\{22\;\;\;0.30469}\\{23\;\;\;0.24747}\\{24\;\;\;0.35374}\\{25\;\;\;0.39770}\\{26\;\;\;0.28676}\\{27\;\;\;0.23673}\\{28\;\;\;0.32175}\end{aligned}\)

03

Calculate LCL and UCL

The center line, from the fact that

\(\sum\limits_{i = 1}^k {{{\hat y}_i}} = 9.24373\)

is given by

\(\bar y = \frac{{9.24373}}{{30}} = 0.30812\)

The\(LCL\) is

\(\begin{aligned}{l}LCL = \bar y - 3\sqrt {\frac{1}{{4n}}} = 0.30812 - 3 \cdot \sqrt {\frac{1}{{800}}} \\ = 0.2020\end{aligned}\)

The \(UCL\) is

\(\begin{aligned}{l}UCL = \bar y + 3\sqrt {\frac{1}{{4n}}} = 0.30812 + 3 \cdot \sqrt {\frac{1}{{800}}} \\ = 0.4142\end{aligned}\)

There are two points out of the limits, first one is \(0.18819\) which is lower than the \(LCL\) and\(0.44462\) which is higher than the\(UCL\).

04

Mapping the chart

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Most popular questions from this chapter

Some sources advocate a somewhat more restrictive type of doubling-sampling plan in which \({r_1} = {c_2} + 1\); that is, the lot is rejected if at either stage the (total) number of defectives is at least \({r_1}\) (see the book by Montgomery). Consider this type of sampling plan with \({n_1} = 50,{n_2} = 100,{c_1} = 1\), and \({r_1} = 4\). Calculate the probability of lot acceptance when \(p = .02,.05\), and .10.

Refer to Example \(16.11\), in which a single-sample plan with \(n = 50\) and \(c = 2\) was employed.

a. Calculate \(AOQ\) for \(p = .01,.02, \ldots ,.10\). What does this suggest about the value of \(p\) for which \(AOQ\) is a maximum and the corresponding \(AOQL\) ?

b. Determine the value of \(p\) for which \(AOQ\) is a maximum and the corresponding value of \(AOQL\). (Hint: Use calculus.)

c. For \(N = 2000\), calculate ATI for the values of \(p\) given in part (a).

Refer to the data given in Exercise\(8\), and construct a control chart with an estimated center line and limits based on using the sample standard deviations to estimate\(\sigma \). Is there any evidence that the process is out of control?

A sample of 50 items is to be selected from a batch consisting of 5000 items. The batch will be accepted if the sample contains at most one defective item. Calculate the probability of lot acceptance for \(p = .01,.02, \ldots ,10\), and sketch the OC curve.

A sample of 200 ROM computer chips was selected on each of 30 consecutive days, and the number of nonconforming chips on each day was as follows: \(10,18,24,17,37,19,7,25,11,24,29,15,16,21,18,17,15,22,12\$ ,\$ 20,17,18,12,24,30,16,11,20,14,28\)Construct a\(p\)chart and examine it for any out-of-control points.

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