In: Statistics and Probability
General HyThere, Inc., is a manufacturer of hydraulic machine
tools. It has had a history leakage trouble resulting from a
certain critical fitting. Twenty five samples of machined parts
were selected, one per shift, and the diameters of the fitting was
measured.
Required:
a. Construct x-bar- and R-charts for the data. What do you
observe?
b. If the regular machine operator was absent when samples 4, 8,
14, 22 were taken, how will the results in part (a) be
affected?
c. A second table in the worksheet represents measurements taken
during the next 10 shifts. Does the process continue to remain
stable? What information does this table provide to the quality
control manager?
Can you show how you entered the data into excel to get the graphs please.
Diameter Measurement (cm) | ||||
Observations | ||||
Sample | 1 | 2 | 3 | 4 |
1 | 10.94 | 10.64 | 10.88 | 10.70 |
2 | 10.66 | 10.66 | 10.68 | 10.68 |
3 | 10.68 | 10.68 | 10.62 | 10.68 |
4 | 10.03 | 10.42 | 10.48 | 11.06 |
5 | 10.70 | 10.46 | 10.76 | 10.80 |
6 | 10.38 | 10.74 | 10.62 | 10.54 |
7 | 10.46 | 10.90 | 10.52 | 10.74 |
8 | 10.66 | 10.04 | 10.58 | 11.04 |
9 | 10.50 | 10.44 | 10.74 | 10.66 |
10 | 10.58 | 10.64 | 10.60 | 10.26 |
11 | 10.80 | 10.36 | 10.60 | 10.22 |
12 | 10.42 | 10.36 | 10.72 | 10.68 |
13 | 10.52 | 10.70 | 10.62 | 10.58 |
14 | 11.04 | 10.58 | 10.78 | 10.17 |
15 | 10.52 | 10.40 | 10.60 | 10.40 |
16 | 10.38 | 10.02 | 10.60 | 10.60 |
17 | 10.56 | 10.68 | 10.78 | 10.34 |
18 | 10.58 | 10.50 | 10.48 | 10.60 |
19 | 10.42 | 10.74 | 10.64 | 10.50 |
20 | 10.48 | 10.44 | 10.32 | 10.70 |
21 | 10.56 | 10.78 | 10.46 | 10.42 |
22 | 10.82 | 10.64 | 11.00 | 10.01 |
23 | 10.28 | 10.46 | 10.82 | 10.84 |
24 | 10.64 | 10.56 | 10.92 | 10.54 |
25 | 10.84 | 10.68 | 10.44 | 10.68 |
c) The following table represents measurements taken during the next 10 shifts. | ||||
Observations | ||||
Sample | 1 | 2 | 3 | 4 |
1 | 10.40 | 10.76 | 10.54 | 10.64 |
2 | 10.60 | 10.28 | 10.74 | 10.86 |
3 | 10.56 | 10.58 | 10.64 | 10.70 |
4 | 10.70 | 10.60 | 10.74 | 10.52 |
5 | 11.02 | 10.36 | 10.90 | 11.02 |
6 | 10.68 | 10.38 | 10.22 | 10.32 |
7 | 10.64 | 10.56 | 10.82 | 10.80 |
8 | 10.28 | 10.62 | 10.40 | 10.70 |
9 | 10.50 | 10.88 | 10.58 | 10.54 |
10 | 10.36 | 10.44 | 10.40 | 10.66 |
Load the data into Excel.
Go to Data> Data Analysis.
Go to Megastat > Quality control process charts.
Select the Data as the Input Range.
Click OK.
All the outputs will appear on the screen.
a. Construct x-bar- and R-charts for the data. What do you observe?
The output is:
Sample size | 4 | |
Number of samples | 25 | |
Mean | Range | |
Upper Control Limit, UCL | 10.9060 | 0.9995 |
Center | 10.5867 | 0.4380 |
Lower Control Limit, LCL | 10.2674 | 0.0000 |
The control charts are:
We observe that the control chart for the range shows that the process is out-of-control.
b. If the regular machine operator was absent when samples 4, 8, 14, 22 were taken, how will the results in part (a) be affected?
The output is:
Sample size | 4 | |
Number of samples | 21 | |
Mean | Range | |
Upper Control Limit, UCL | 10.8322 | 0.7672 |
Center | 10.5871 | 0.3362 |
Lower Control Limit, LCL | 10.3421 | 0.0000 |
The control charts are:
The process is in control.
c. A second table in the worksheet represents measurements taken during the next 10 shifts. Does the process continue to remain stable? What information does this table provide to the quality control manager?
The output is:
Sample size | 4 | |
Number of samples | 10 | |
Mean | Range | |
Upper Control Limit, UCL | 10.8741 | 0.8626 |
Center | 10.5985 | 0.3780 |
Lower Control Limit, LCL | 10.3229 | 0.0000 |
The control charts are:
The process continue to remain stable. Thus, the quality control manager should remove the samples 4, 8, 14, 22 to get a stable process.