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Refer to Exercise 1 and suppose the ten most recent values of the quality statistic are .0493, .0485, .0490, .0503, .0492, .0486, .0495, .0494, .0493, and .0488. Construct the relevant portion of the corresponding control chart, and comment on its appearance.

Short Answer

Expert verified

There may be decreased in average value of the sample mean thickness.

Step by step solution

01

solving using graph:

All ten values are between UCL and LCL.

Notice that only value is above the central line. This might suggest that, there may be decreased in average value of the sample mean thickness.

02

final answer:

There may be decreased in average value of the sample mean thickness.

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Most popular questions from this chapter

Subgroups of power supply units are selected once each hour from an assembly line, and the high-voltage output of each unit is determined.

a. Suppose the sum of the resulting sample ranges for\(30\)subgroups, each consisting of four units, is\(85.2\). Calculate control limits for an\(R\)chart.

b. Repeat part (a) if each subgroup consists of eight units and the sum is\(106.2\).

If a process variable is normally distributed, in the long run virtually all observed values should be between饾潄-3饾潏and饾潄+3饾潏, giving a process spread of 6饾潏.

a.With LSL and USL denoting the lower and upper specification limits, one commonly used process capability indexis Cp = (USL 鈥 LSL)/6饾潏. The value Cp= 1 indicates a process that is only marginally capable of meeting specifications. Ideally, Cp should exceed 1.33 (a 鈥渧ery good鈥 process). Calculate the value of Cp for each of the cork production processes described in the previous exercise, and comment.

b. The Cp index described in (a) does not take into account process location. A capability measure that does involve the process mean is Cpk = min {(饾潏USL -饾潄)/3饾潏, (饾潄鈥 LSL)/3饾潏} Calculate the value of Cpk for each of the cork production processes described in the previous exercise, and comment. (Note: In practice, m and s have to be estimated from process data; we show how to do this in Section 16.2)

c. How do Cp and Cpk compare, and when are they equal?

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.

An alternative to the \(p\) chart for the fraction defective is the np chart for number defective. This chart has \(UCL = n\bar p + 3\sqrt {n\bar p(1 - \bar p)} ,LCL = n\bar p - 3\sqrt {n\bar p(1 - \bar p)} \),

and the number of defectives from each sample is plotted on the chart. Construct such a chart for the data of Example 16.6. Will the use of an \(n p\) chart always give the same message as the use of a \(p\)chart (i.e., are the two charts equivalent)?

Containers of a certain treatment for septic tanks are supposed to contain \(16oz\) of liquid. A sample of five containers is selected from the production line once each hour, and the sample average content is determined. Consider the following results: \(15.992,16.051,16.066,15.912\), \(16.030,16.060,15.982,15.899,16.038,16.074,16.029\), \(15.935,16.032,15.960,16.055\). Using \(\Delta = .10\) and\(h = .20\), employ the computational form of the CUSUM procedure to investigate the behaviour of this process.

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