Quality and Reliability Methods - SAS

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100 Cumulative Sum Control Charts Chapter 6 Cumulative Sum (Cusum) Charts Connect Color displays the JMP color palette for you to select a color for the connect line when the Connect Points option is in effect. Center Line Color displays the JMP color palette for you to select a color for the center line. Show Shift shows or hides the shift that you entered, or center line. Show V Mask shows or hides the V-mask based on the parameters (statistics) specified in the Cusum Control Charts launch window. Show Parameters parameters. displays a Parameters table (Figure 6.9) that summarizes the Cusum charting Show ARL displays the average run length (ARL) information. Example 1. Two-Sided Cusum Chart with V-mask To see an example of a two-sided cusum chart, open the Oil1 Cusum.jmp file from the Quality Control sample data folder. A machine fills 8-ounce cans of two-cycle engine oil additive. The filling process is believed to be in statistical control. The process is set so that the average weight of a filled can, μ 0 , is 8.10 ounces. Previous analysis shows that the standard deviation of fill weights, σ 0 , is 0.05 ounces. Subgroup samples of four cans are selected and weighed every hour for twelve hours. Each observation in the Oil1 Cusum.jmp data table contains one value of weight along with its associated value of hour. The observations are sorted so that the values of hour are in increasing order. The Control Chart platform assumes that the data are sorted in increasing order. A two-sided cusum chart is used to detect shifts of at least one standard deviation in either direction from the target mean of 8.10 ounces. To create a Cusum chart for this example, 1. Choose the Analyze > Quality And Process > Control Chart > CUSUM command. 2. Click the Two Sided check box if it is not already checked. 3. Specify weight as the Process variable. 4. Specify hour as the Sample Label. 5. Click the H radio button and enter 2 into the text box. 6. Click Specify Stats to open the Known Statistics for CUSUM Chart tab. 7. Set Target to the average weight of 8.1. 8. Enter a Delta value of 1. 9. Set Sigma to the standard deviation of 0.05. The finished dialog should look like the one in Figure 6.5. Alternatively, you can bypass the dialog and submit the following JSL script: Control Chart(Sample Size( :hour), H(2), Chart Col( :weight, CUSUM(Two sided(1), Target(8.1), Delta(1), Sigma(0.05))));
Chapter 6 Cumulative Sum Control Charts 101 Cumulative Sum (Cusum) Charts Figure 6.5 Dialog for Cusum Chart Example When you click OK, the chart in Figure 6.6 appears. Figure 6.6 Cusum Chart for Oil1 Cusum.jmp Data You can interpret the chart by comparing the points with the V-mask whose right edge is centered at the most recent point (hour=12). Because none of the points cross the arms of the V-mask, there is no evidence that a shift in the process has occurred.
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Version 10 Quality and Reliability
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INDIRECT OR CONSEQUENTIAL DAMAGES O
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6 Nelson Rules . . . . . . . . . .
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Chapter 1 Learn about JMP 17 Book C
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Chapter 1 Learn about JMP 19 Book C
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Chapter 1 Learn about JMP 21 Additi
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Chapter 1 Learn about JMP 23 Additi
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Chapter 2 Statistical Control Chart
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Chapter 10 Variability Charts 169 D
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Chapter 11 Pareto Plots The Pareto
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Chapter 11 Pareto Plots 181 Pareto
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Chapter 11 Pareto Plots 187 Launch
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Chapter 11 Pareto Plots 189 One-Way
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Chapter 11 Pareto Plots 191 Two-Way
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Chapter 11 Pareto Plots 193 Defect
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Chapter 16 Degradation Using the De
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Chapter 16 Degradation 279 Overview
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Chapter 19 Reliability and Survival
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References Abernethy, Robert B. (19
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References 407 Carroll, R.J., Ruppe
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References 409 Haaland, P.D. (1989)
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References 411 Lawless, J.F. (1982)
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References 413 Nelson, W.B. (2003),
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References 415 Snee, R.D. and Marqu
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Index JMP Quality and Reliability M
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Index 419 Fit SEV 242 Fit Weibull 2
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Index 421 Q Quantiles table 356 R R
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Index 423 Weibull Plot 360 Westgard
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Quality and Reliability Methods - SAS

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