Question

A manufacturing process produces steel rods in batches of 2,200. The firm believes that the percent of defective items generated by this process is 4.3%.

**a.** Calculate the centerline, the upper control
limit (UCL), and the lower control limit (LCL) for the p¯p¯ chart.
**(Round your answers to 3 decimal places.)**

centerline-

Upper control limit-

Lower control limit-

**b.** An engineer inspects the next batch of 2,200
steel rods and finds that 5.5% are defective. Is the manufacturing
process under control?

A)Yes, because the sample proportion lies within the control limits.

B)Yes, because the sample proportion lies below the lower control limit.

C)No, because the sample proportion lies between the upper and lower control limits.

D)No, because the sample proportion lies below the lower control limit.

Answer #1

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A manufacturing process produces steel rods in batches of 1,700.
The firm believes that the percent of defective items generated by
this process is 5.4%. a. Calculate the centerline, the upper
control limit (UCL), and the lower control limit (LCL) for the p⎯⎯
chart. (Round your answers to 3 decimal places.) b. An engineer
inspects the next batch of 1,700 steel rods and finds that 6.5% are
defective. Is the manufacturing process under control?

Random samples of size n = 200 are taken from a population with
p = 0.08.
a. Calculate the centerline, the upper control limit (UCL), and
the lower control limit (LCL) for the p¯chart
b. Calculate the centerline, the upper control limit (UCL), and
the lower control limit (LCL) for the p¯ chart if samples of 120
are used.
c. Discuss the effect of the sample size on the control limits.
The control limits have a ___ spread with smaller...

Twelve samples, each containing five parts, were taken from a
process that produces steel rods at Emmanual Kodzi's factory. The
length of each rod in the samples was determined. The results were
tabulated and sample means and ranges were computed.
Refer to Table S6.1 - Factors for computing control chart limits
(3 sigma) for this problem.
Sample
Size, n
Mean Factor,
A2
Upper Range,
D4
Lower Range,
D3
2
1.880
3.268
0
3
1.023
2.574
0
4
0.729
2.282
0...

Random samples of size n= 400 are taken from a
population with p= 0.15.
a.Calculate the centerline, the upper control
limit (UCL), and the lower control limit (LCL) for the p
chart.
b.Suppose six samples of size 400 produced the
following sample proportions: 0.06, 0.11, 0.09, 0.08, 0.14, and
0.16. Is the production process under control?

Twenty-five samples of 100 items each were inspected when a
process was considered to be operating satisfactorily. In the 25
samples, a total of 185 items were found to be defective.
(a)
What is an estimate of the proportion defective when the process
is in control?
(b)
What is the standard error of the proportion if samples of size
100 will be used for statistical process control? (Round your
answer to four decimal places.)
(c)
Compute the upper and lower...

A local company makes snack-size bags of potato chips. The
company produces batches of 400 snack-size bags using a process
designed to fill each bag with an average of 2 ounces of potato
chips. However, due to imperfect technology, the actual amount
placed in a given bag varies. Assume the population of filling
weights is normally distributed with a standard deviation of 0.1
ounce. The company periodically weighs samples of 10 bags to ensure
the proper filling process. The last...

The following are quality control data for a manufacturing
process at Kensport Chemical Company. The data show the temperature
in degrees centigrade at five points in time during a manufacturing
cycle.
Sample
x
R
1
95.72
1.0
2
95.24
0.9
3
95.18
0.7
4
95.42
0.4
5
95.46
0.5
6
95.32
1.1
7
95.40
0.9
8
95.44
0.3
9
95.08
0.2
10
95.50
0.6
11
95.80
0.6
12
95.22
0.2
13
95.60
1.3
14
95.22
0.6
15
95.04
0.8
16...

The following are quality control data for a manufacturing
process at Kensport Chemical Company. The data show the temperature
in degrees centigrade at five points in time during a manufacturing
cycle.
Sample
x
R
1
95.72
1.0
2
95.24
0.9
3
95.18
0.7
4
95.44
0.4
5
95.46
0.5
6
95.32
1.1
7
95.40
0.9
8
95.44
0.3
9
95.08
0.2
10
95.50
0.6
11
95.80
0.6
12
95.22
0.2
13
95.54
1.3
14
95.22
0.6
15
95.04
0.8
16...

The following are quality control data for a manufacturing
process at Kensport Chemical Company. The data show the temperature
in degrees centigrade at five points in time during a manufacturing
cycle.
Sample
x
R
1
95.72
1.0
2
95.24
0.9
3
95.18
0.7
4
95.42
0.4
5
95.46
0.5
6
95.32
1.1
7
95.40
0.9
8
95.44
0.3
9
95.08
0.2
10
95.50
0.6
11
95.80
0.6
12
95.22
0.2
13
95.58
1.3
14
95.22
0.6
15
95.04
0.8
16...

An online clothing retailer monitors its order-filling process.
Each week, the quality control manager selects a random sample of
size n = 350 orders that have been filled but have not shipped. The
contents of the shipping container are checked against the items
ordered by the customer (including color and size categories), and
the order is categorized as defective or non-defective. A p chart
is used to identify whether or not the process is in control.
The graph below shows...

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