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91Ó°ÊÓ

Calculate control limits for an\(S\)chart from the refractive index data of Exercise 11 . Does the process appear to be in control with respect to variability? Why or why not?

Short Answer

Expert verified

1. \(\begin{aligned}{l}LCL = 0.45\\UCL = 2.484\\CL = 30.34\end{aligned}\)

Step by step solution

01

Determine the LCL and UCL for S control chart

Assume\(k\)independently selected samples, where every sample consisting of\(n\)observations of a normally distributed variable. Sample standard deviations are\({s_1},{s_2}, \ldots ,{s_k}\), and

\(\bar s = \frac{{\sum {{s_i}} }}{k}\)

where we plot values\({s_1},{s_2}, \ldots ,{s_k}\)on the\({\rm{S}}\)Chart. The center line is on height\(\bar s\).

Upper Control Limit and Lower Control Limit for\({\rm{S}}\)control chart are

\(\begin{aligned}{l}LCL = \bar s - 3\bar s\frac{{\sqrt {1 - a_n^2} }}{{{a_n}}}\\UCL = \bar s + 3\bar s\frac{{\sqrt {1 - a_n^2} }}{{{a_n}}}\end{aligned}\)

Where LCL will be negative for\(n \le 5\). When this happens it is customary to take\({\rm{LCL}} = 0\)

Values for\({a_n}\)are given in the table on the page\(684\)for\(n = 3,4, \ldots ,8\).

\(\begin{aligned}{*{20}{c}}{\rm{n}}&{\rm{3}}&{\rm{4}}&{\rm{5}}&{\rm{6}}&{\rm{7}}&{\rm{8}}\\{{\rm{a\_(n)}}}&{{\rm{.886}}}&{{\rm{.921}}}&{{\rm{.940}}}&{{\rm{.952}}}&{{\rm{.959}}}&{{\rm{.965}}}\end{aligned}\)

02

Calculate the limits

From the Exercise\({\rm{11}}\), we have that\(k = 24\)and

\(\sum\limits_{i = 1}^{24} {{s_i}} = 30.34\)

which implies that

\(\bar s = \frac{1}{{24}}\sum\limits_{i = 1}^{24} {{s_i}} = \frac{1}{{24}} \cdot 30.35 = 1.2642\)

Also, from the Exercise\({\rm{11}}\)each sample standard deviation is based on\(n = 6\)observations of the refractive index of fiber-optic cable. Therefore, we look the table and see that\({a_6} = 0.952\).

\(\begin{aligned}{*{20}{c}}{\rm{n}}&{\rm{3}}&{\rm{4}}&{\rm{5}}&{\rm{6}}&{\rm{7}}&{\rm{8}}\\{{\rm{a\_(n)}}}&{{\rm{.886}}}&{{\rm{.921}}}&{{\rm{.940}}}&{{\rm{.952}}}&{{\rm{.959}}}&{{\rm{.965}}}\end{aligned}\)

Now we can calculate the limits

\(\begin{aligned}{l}LCL = \bar s - 3\bar s\frac{{\sqrt {1 - a_n^2} }}{{{a_n}}} = 1.2642 - 3 \cdot 1.2642 \cdot \frac{{\sqrt {1 - {{0.952}^2}} }}{{0.952}} = 0.45\\UCL = \bar s + 3\bar s\frac{{\sqrt {1 - a_n^2} }}{{{a_n}}} = 1.2642 + 3 \cdot 1.2642 \cdot \frac{{\sqrt {1 - {{0.952}^2}} }}{{0.952}} = 2.484\\CL = \bar s = 30.34.\end{aligned}\)

Since the biggest value is\({s_{12}} = 1.65\)and the smallest is\({s_{20}} = 0.75\)and the following is true

\(LCL = 0.45 < 0.75 = {s_{20}} < {s_{12}} = 1.65 < UCL = 2.484\)

all values are between the specification limits so the process seems to be in control in respect to variability.

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Most popular questions from this chapter

Three-dimensional (3D) printing is a manufacturing technology that allows the production of three-dimensional solid objects through a meticulous layering process performed by a\(3D\)printer.\(3D\)printing has rapidly become a time-saving and economical way to create a wide variety of products such as medical implants, furniture, tools, and even jewelry. The article "Process Capability Analysis of Cost Effective Rapid Casting Solution Based on Three Dimensional Printing" (MIT Intl. J. Mech. Engr., \(\;2012: 31 - 38\)) considered the production process of metal castings by using a\(3D\)printer. Data was collected on\(16\)batches (each having two castings), where the outer diameter of each casting (in\(mm\)) was recorded. The target diameter of each casting was\(60\;mm\). The resulting data is given here:

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Apply the supplemental rules suggested in the text to the data. Are there any out-of-control signals?

The accompanying observations are numbers of defects in\(25\)\(1\)-square-yard specimens of woven fabric of a certain type: \(3,7,5,3,4,2,8,4,3,3,6,7,2,3,2,4,7,3,2,4,4\),\(1,5,4,6\). Construct a\(c\)chart for the number of defects.

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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.

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