Quality and Process Methods • Pareto Plots • Additional Examples of the Pareto Plot Platform
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Additional Examples of the Pareto Plot Platform
This section contains additional examples using the Pareto Plot platform.
Threshold of Combined Causes Example
This example uses the Failure.jmp sample data table, which contains failure data and a frequency column. It lists causes of failure during the fabrication of integrated circuits and the number of times each type of defect occurred. A threshold value of 2 is specified for this example.
1.
Select Help > Sample Data Library and open Quality Control/Failure.jmp.
2.
Select Analyze > Quality and Process > Pareto Plot.
3.
Select failure and click Y, Cause.
4.
Select N and click Freq.
5.
Select Threshold of Combined Causes and then select Count.
6.
Enter 2 as the threshold value.
7.
Click OK.
Pareto Plot with a Threshold Count of 2
Pareto Plot with a Threshold Count of 2 displays the plot after specifying a count of 2. All causes with counts 2 or fewer are combined into the final bar labeled 4 Others.
8.
To separate the combined bars into original categories as shown in Pareto Plot with Separated Causes, select Causes > Separate Causes.
Pareto Plot with Separated Causes
Using a Constant Size across Groups Example
This example uses the Failures.jmp sample data table, which contains failure data and a frequency column. It lists causes of failure during the fabrication of integrated circuits and the number of times each type of defect occurred for two processes. A constant sample size of 1000 is specified for this example.
1.
Select Help > Sample Data Library and open Quality Control/Failures.jmp.
2.
Select Analyze > Quality and Process > Pareto Plot.
3.
Select Causes and click Y, Cause.
4.
Select Process and click X, Grouping.
5.
Select Count and click Freq.
6.
Select Per Unit Analysis and then select Constant.
7.
Enter 1000 in Sample Size.
8.
Click OK.
Pareto Plot Report Window
Process A indicates Contamination as the top failure while Process B indicates Oxide Defect as the leading failure.
9.
Select Count Analysis > Test Rates Across Groups from the red triangle menu.
Test Rates across Groups Results
Note that the DPU for Contamination across groups (Process A and B) is around 0.06.
Using a Non-Constant Sample Size across Groups Example
This example uses the Failuressize.jmp sample data table, which contains failure data and a frequency column. It lists causes of failure during the fabrication of integrated circuits and the number of times each type of defect occurred for two processes. Among the other causes (Oxide Defect, Silicon Defect, and so on) is a cause labeled size. Specifying size as the cause code designates the rows as size rows.
1.
Select Help > Sample Data Library and open Quality Control/Failuressize.jmp.
2.
Select Analyze > Quality and Process > Pareto Plot.
3.
Select Causes and click Y, Cause.
4.
Select Process and click X, Grouping.
5.
Select Count and click Freq.
6.
Select Per Unit Analysis and then select Value in Freq Column.
7.
Enter size in Cause Code.
8.
Click OK.
Pareto Plot Report Window
9.
Select Count Analysis > Per Unit Rates and Count Analysis > Test Rates Across Groups from the red triangle menu.
Per Unit Rates and Test Rates across Groups Results
Note that the sample size of 101 is used to calculate the DPU for the causes in group A. However, the sample size of 145 is used to calculate the DPU for the causes in group B.
If there are two group variables (say, Day and Process), Per Unit Rates lists DPU or rates for every combination of Day and Process for each cause. However, Test Rate Across Groups only tests overall differences between groups.
One-Way Comparative Pareto Plot Example
This example uses the Failure2.jmp sample data table. This table records failures in a sample of capacitors manufactured before cleaning a tube in the diffusion furnace and in a sample manufactured after cleaning the furnace. For each type of failure, the variable clean identifies the samples with the values “before” or “after.”
1.
Select Help > Sample Data Library and open Quality Control/Failure2.jmp.
2.
Select Analyze > Quality and Process > Pareto Plot.
3.
Select failure and click Y, Cause.
4.
Select clean and click X, Grouping.
5.
Select N and click Freq.
6.
Click OK.
One-way Comparative Pareto Plot displays the side-by-side plots for each value of the variable, clean.
One-way Comparative Pareto Plot
The horizontal and vertical axes are scaled identically for both plots. The bars in the first plot are in descending order of the y-axis values and determine the order for all cells.
7.
Rearrange the order of the plots by clicking the title (after) in the first tile and dragging it to the title of the next tile (before).
A comparison of these two plots shows a reduction in oxide defects after cleaning. However, the plots are easier to interpret when presented as the before-and-after plot shown in One-way Comparative Pareto Plot with Reordered Cells. Note that the order of the causes changes to reflect the order based on the first cell.
One-way Comparative Pareto Plot with Reordered Cells
Two-Way Comparative Pareto Plot Example
This example uses the Failure3.jmp sample data table. The data monitors production samples before and after a furnace cleaning for three days for a capacitor manufacturing process. The data table has a column called date with values OCT 1, OCT 2, and OCT 3.
1.
Select Help > Sample Data Library and open Quality Control/Failure3.jmp.
2.
Select Analyze > Quality and Process > Pareto Plot.
3.
Select failure and click Y, Cause.
4.
Select clean and date and click X, Grouping.
5.
Select N and click Freq.
6.
Click OK.
Two-way Comparative Pareto Plot displays the Pareto plot with a two-way layout of plots that show each level of both X variables. The upper left cell is called the key cell. Its bars are arranged in descending order. The bars in the other cells are in the same order as the key cell.
7.
Click Contamination and Metallization in the key cell and the bars for the corresponding categories highlight in all other cells.
Two-way Comparative Pareto Plot
The Pareto plot shown in Two-way Comparative Pareto Plot illustrates highlighting the vital few. In each cell of the two-way comparative plot, the bars representing the two most frequently occurring problems are selected. Contamination and Metallization are the two vital categories in all cells. After furnace cleaning, Contamination is less of a problem.