Standard Folio Plots: Difference between revisions

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Weibull++ provides many useful plots. We will use this example to illustrate them. Assume we have the following failure data.
Weibull++ provides many useful plots. We will use this example to illustrate them. Assume we have the following failure data.


{| | border="1" class="wikitable" style="margin: 1em auto 1em auto"
{| | border="1" align="center" style="border-collapse: collapse;" cellpadding="5" cellspacing="5"
| align="center" style="background:#f0f0f0;"|'''Number in State'''
| align="center" style="background:#f0f0f0;"|'''Number in State'''
| align="center" style="background:#f0f0f0;"|'''State F or S'''
| align="center" style="background:#f0f0f0;"|'''State F or S'''
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Analyze the above data using MLE, 2P Weibull distribution, we have the following results.  
Analyze the data using the 2P-Weibull distribution and the MLE analysis method. The results are shown next.  
 
[[image: Plot Type Data and Results.png|thumb|center|400px]]
 


Click on the Plot button, Weibull++ automatically shows the first plot probability plot.
[[image: Plot Type Data and Results.png|center|500px]]


Click the '''Plot''' icon on the control panel. This displays the first plot probability plot.


'''1. Probability Plot'''
'''1. Probability Plot'''


[[image: Plot Type Probability Plot.png|thumb|center|400px]]
[[image: Plot Type Probability Plot.png|center|500px]]
 
You also can choose to display the confidence bounds on time, reliability, or both. Click on the '''Confidence Bounds…''' link.
 
[[image: Plot Type confidence bound Set up.png|thumb|center|400px]]
 
Then click on '''OK''',
 
[[image: Plot Type Reliability confidence bound.png|thumb|center|400px]]
 
Probability plot shows the predicted (the line) and observed probability of failure (the dots, calculated from non-parametric LDA). If the straight line can fit the dots well, it means the distribution in use is suitable for this data set.
 
Click on the '''Plot Type''' drop down list to view all the available plots.
 
[[image: Plot Type plot type list.png|thumb|center|400px]]
 
We will explain each plot type in below.
 
 
'''2. Reliability vs. Time Plot.'''
 
[[image: Plot Type Reliability plot.png|thumb|center|400px]]
 
It shows how reliability changes with time. Similar to the probability plot, it has both the predicted and the observed reliability values on the plot.
 
 
'''3. UnReliability vs. Time Plot.'''
[[image: Plot Type UnReliability plot.png|thumb|center|400px]]


It shows how Unreliability (Probability of Failure) changes with time. Similar to the probability plot, it has both the predicted and the observed values on the plot.  
You can choose to display the confidence bounds on time, reliability, or both. To do this, click the '''Confidence Bounds…''' link on the control panel. The following picture shows the Confidence Bounds Setup window.


[[image: Plot Type confidence bound Set up.png|center|400px]]


'''4. pdf Plot'''
The following example shows the two-sided confidence bounds on the reliability.
[[image: Plot Type Reliability confidence bound.png|center|500px]]


[[image: Plot Type pdf plot.png.png|thumb|center|400px]]
The points on the probability plot represent the observed probability of failure, while the straight line represents the predicted probability of failure. If the line fits the points well, it indicates that the distribution in use is suitable for the data set.  


pdf (probability density function) plot shows how the failure data distributed at different time range, if the failure data indeed follows the distribution in use. The range around the peak of the pdf curve is where most of the failures occur.  
To view all the available plots for the Weibull++ standard folio, click the '''Plot Type''' drop down list on the control panel, as shown next.  


[[image: Plot Type plot type list.png|center|300px]]


'''5. Failure Rate Vs. Time Plot'''
All the available plot types are explained next.


[[image: Plot Type failure rate plot.png|thumb|center|400px]]
'''2. Reliability vs. Time Plot''' shows how reliability changes with time. Similar to the probability plot, it has both the predicted and the observed reliability values on the plot.  


Failure rate plot shows how the failure rate (the frequency of having failures) changes with time. For this example, we can see it has an increasing failure rate.  
[[image: Plot Type Reliability plot.png|center|500px]]


'''3. Unreliability vs. Time Plot''' shows how unreliability (probability of failure) changes with time. Similar to the probability plot, it has both the predicted and the observed values on the plot.


'''6. Contour Plot'''
[[image: Plot Type UnReliability plot.png|center|500px]]


[[image: Plot Type Contour plot.png|thumb|center|400px]]
'''4. PDF Plot''' (probability density function plot) shows how the failure data are distributed at different time ranges, if the failure data indeed follows the distribution in use. The range around the peak of the pdf curve is where most of the failures occur.  


Contour plot shows the jointed range of the estimated distribution parameters. With higher confidence level, the range will be larger.  
[[image: Plot Type pdf plot.png.png|center|500px]]


'''5. Failure Rate vs. Time Plot''' shows how the failure rate (the frequency of having failures) changes with time. For this example, we can see it has an increasing failure rate.


'''7. Histogram'''
[[image: Plot Type failure rate plot.png|center|500px]]
[[image: Plot Type histogram plot.png|thumb|center|400px]]


'''6. Contour Plot''' shows the jointed range of the estimated distribution parameters. With higher confidence level, the range will be larger.


Histogram shows the number of failures/suspensions at a given time interval. Users can set the time interval at the control panel. The Y value is the number of observations; the X value is the time range of when the observations occurred.
[[image: Plot Type Contour plot.png|center|500px]]


'''7. Histogram''' shows the number of failures/suspensions at a given time interval. Users can set the time interval at the control panel. The Y value is the number of observations, while the X value is the time range of when the observations occurred.


'''8. F/S Pie Chart'''
[[image: Plot Type histogram plot.png|center|500px]]
[[image: Plot Type Pie plot.png|thumb|center|400px]]


F/S Pie visually displays the percentage of failures and suspensions in the data set.  
'''8. F/S Pie Chart''' visually displays the percentage of failures and suspensions in the data set.  


[[image: Plot Type Pie plot.png|center|500px]]


'''9. F/S Timeline'''
'''9. F/S Timeline''' graphically displays the values for each failure and suspension. In the following example, there are 6 failures between 60 and 120 hours.
[[image: Plot Type Time line plot.png|thumb|center|400px]]


F/S Timeline plot graphically display the values for each failure and suspension. For example, from the above plot, you can see there are 6 failures between 60 and 120 hours.
[[image: Plot Type Time line plot.png|center|500px]]

Latest revision as of 07:50, 7 August 2012

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Weibull++ provides many useful plots. We will use this example to illustrate them. Assume we have the following failure data.

Number in State State F or S State End Time
2 F 20
3 F 45
4 F 89
2 F 100
5 F 123
15 S 150
20 S 200


Analyze the data using the 2P-Weibull distribution and the MLE analysis method. The results are shown next.

Plot Type Data and Results.png

Click the Plot icon on the control panel. This displays the first plot probability plot.

1. Probability Plot

Plot Type Probability Plot.png

You can choose to display the confidence bounds on time, reliability, or both. To do this, click the Confidence Bounds… link on the control panel. The following picture shows the Confidence Bounds Setup window.

Plot Type confidence bound Set up.png

The following example shows the two-sided confidence bounds on the reliability.

Plot Type Reliability confidence bound.png

The points on the probability plot represent the observed probability of failure, while the straight line represents the predicted probability of failure. If the line fits the points well, it indicates that the distribution in use is suitable for the data set.

To view all the available plots for the Weibull++ standard folio, click the Plot Type drop down list on the control panel, as shown next.

Plot Type plot type list.png

All the available plot types are explained next.

2. Reliability vs. Time Plot shows how reliability changes with time. Similar to the probability plot, it has both the predicted and the observed reliability values on the plot.

Plot Type Reliability plot.png

3. Unreliability vs. Time Plot shows how unreliability (probability of failure) changes with time. Similar to the probability plot, it has both the predicted and the observed values on the plot.

Plot Type UnReliability plot.png

4. PDF Plot (probability density function plot) shows how the failure data are distributed at different time ranges, if the failure data indeed follows the distribution in use. The range around the peak of the pdf curve is where most of the failures occur.

Plot Type pdf plot.png.png

5. Failure Rate vs. Time Plot shows how the failure rate (the frequency of having failures) changes with time. For this example, we can see it has an increasing failure rate.

Plot Type failure rate plot.png

6. Contour Plot shows the jointed range of the estimated distribution parameters. With higher confidence level, the range will be larger.

Plot Type Contour plot.png

7. Histogram shows the number of failures/suspensions at a given time interval. Users can set the time interval at the control panel. The Y value is the number of observations, while the X value is the time range of when the observations occurred.

Plot Type histogram plot.png

8. F/S Pie Chart visually displays the percentage of failures and suspensions in the data set.

Plot Type Pie plot.png

9. F/S Timeline graphically displays the values for each failure and suspension. In the following example, there are 6 failures between 60 and 120 hours.

Plot Type Time line plot.png