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With the Synthesis API, you can leverage the Weibull++ analysis engine to perform life data analysis on an external data source. In this tutorial, you will learn how to use the API to create and analyze a data set, and | With the Synthesis API, you can leverage the Weibull++ analysis engine to perform life data analysis on an external data source. In this tutorial, you will learn how to use the API to create and analyze a data set, and obtain analysis results from the model. | ||
==Tutorial: Life Data Analysis== | ==Tutorial: Life Data Analysis== | ||
The following example demonstrates how to define a Weibull++ data set, | The following example demonstrates how to define and analyze a Weibull++ data set, and use the result to estimate the probability of failure. A discussion of the example follows. | ||
This example uses the following data set: | |||
{|{{table}} | {|{{table}} | ||
|Number in State||State||Time to F or S | |Number in State||State||Time to F or S | ||
Line 82: | Line 82: | ||
WDS.AddSuspension(120, 5) | WDS.AddSuspension(120, 5) | ||
The AnalysisSetting property returns a [[WeibullAnalysisOptions Class|WeibullAnalysisOptions]] object, which represents the analysis settings of the | The AnalysisSetting property returns a [[WeibullAnalysisOptions Class|WeibullAnalysisOptions]] object, which represents the analysis settings of the data set. In the following example, we use the <code>Distribution</code>, <code>Parameters</code> and <code>Analysis</code> properties of the object to specify the life distribution and analysis method. | ||
{{APIComment|'Use the 2-parameter Weibull distribution and the rank regression on X (RRX) analysis method.}} | {{APIComment|'Use the 2-parameter Weibull distribution and the rank regression on X (RRX) analysis method.}} | ||
Line 90: | Line 90: | ||
WDS.AnalysisSettings.Analysis = WeibullSolverMethod.RRX | WDS.AnalysisSettings.Analysis = WeibullSolverMethod.RRX | ||
Use the [[WeibullDataSet.Calculate|Calculate]] method to analyze the data set. The method returns a message box that shows the estimated parameters of the life distribution, based on the settings specified in the <code>AnalysisSettings</code> property. | |||
{{APIComment|'Analyze the data set.}} | {{APIComment|'Analyze the data set.}} | ||
WDS.Calculate() | WDS.Calculate() | ||
The FittedModel property gets a [[CModel Class|cModel]] object that represents the fitted model of the life data analysis. From the model, you can calculate useful metrics such as reliability, failure rate, mean time, etc. In this example, we calculate for the probability of failure | The <code>FittedModel</code> property gets a [[CModel Class|cModel]] object that represents the fitted model of the life data analysis. From the model, you can calculate useful metrics such as reliability, failure rate, mean time, etc. In this example, we use the [[CModel.Unreliability|cModel.Unreliability]] method to calculate for the probability of failure. | ||
{{APIComment|'Calculate the probability of failure at 226 hrs and display the result.}} | {{APIComment|'Calculate the probability of failure at 226 hrs and display the result.}} |
Revision as of 20:32, 12 May 2016
DRAFT
With the Synthesis API, you can leverage the Weibull++ analysis engine to perform life data analysis on an external data source. In this tutorial, you will learn how to use the API to create and analyze a data set, and obtain analysis results from the model.
Tutorial: Life Data Analysis
The following example demonstrates how to define and analyze a Weibull++ data set, and use the result to estimate the probability of failure. A discussion of the example follows.
This example uses the following data set:
Number in State | State | Time to F or S |
1 | F | 16 |
1 | F | 34 |
1 | F | 53 |
1 | F | 75 |
1 | F | 93 |
5 | S | 120 |
VB.NET Imports SynthesisAPI Module Module1 Sub Main() 'Declare a new WeibullDataSet object. Dim WDS As New WeibullDataSet 'Add failure times to the data set. WDS.AddFailure(16, 1) WDS.AddFailure(34, 1) WDS.AddFailure(53, 1) WDS.AddFailure(75, 1) WDS.AddFailure(93, 1) 'Add five suspensions to the data set. WDS.AddSuspension(120, 5) 'Use the 2-parameter Weibull distribution and the rank regression on X (RRX) analysis method. 'Keep all other analysis settings at default. WDS.AnalysisSettings.Distribution = WeibullSolverDistribution.Weibull WDS.AnalysisSettings.Parameters = WeibullSolverNumParameters.MS_2Parameter WDS.AnalysisSettings.Analysis = WeibullSolverMethod.RRX 'Analyze the data set. WDS.Calculate() 'Calculate the probability of failure at 226 hrs and display the result. Dim r As Double r = WDS.FittedModel.unreliability(226) MsgBox("Prob. Fail: " & r) End Sub End Module
Discussion
The WeibullDataSet class represents a Weibull++ standard folio data sheet. The class contains all the methods and properties that allow you to define a data set and fit a statistical distribution to the data.
'Declare a new WeibullDataSet object. Dim WDS As New WeibullDataSet
The data set can contain failures, suspensions, interval data or free-form data. The following example shows how to use the AddFailure method to define failures and the AddSuspension method to define suspensions.
'Add failure times to the data set. WDS.AddFailure(16, 1) WDS.AddFailure(34, 1) WDS.AddFailure(53, 1) WDS.AddFailure(75, 1) WDS.AddFailure(93, 1) 'Add five suspensions to the data set. WDS.AddSuspension(120, 5)
The AnalysisSetting property returns a WeibullAnalysisOptions object, which represents the analysis settings of the data set. In the following example, we use the Distribution
, Parameters
and Analysis
properties of the object to specify the life distribution and analysis method.
'Use the 2-parameter Weibull distribution and the rank regression on X (RRX) analysis method. 'Keep all other analysis settings at default. WDS.AnalysisSettings.Distribution = WeibullSolverDistribution.Weibull WDS.AnalysisSettings.Parameters = WeibullSolverNumParameters.MS_2Parameter WDS.AnalysisSettings.Analysis = WeibullSolverMethod.RRX
Use the Calculate method to analyze the data set. The method returns a message box that shows the estimated parameters of the life distribution, based on the settings specified in the AnalysisSettings
property.
'Analyze the data set.
WDS.Calculate()
The FittedModel
property gets a cModel object that represents the fitted model of the life data analysis. From the model, you can calculate useful metrics such as reliability, failure rate, mean time, etc. In this example, we use the cModel.Unreliability method to calculate for the probability of failure.
'Calculate the probability of failure at 226 hrs and display the result. Dim r As Double r = WDS.FittedModel.unreliability(226) MsgBox("Prob. Fail: " & r)