Weibull++ Simumatic Data 1P-Exponential: Difference between revisions
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Reliability growth analysis using simulation can be a valuable tool for reliability practitioners. With this approach, reliability growth analyses are performed a large number of times on data sets that have been created using Monte Carlo simulation. | |||
The SimuMatic utility generates calculated values of beta and lambda parameters, based on user specified input parameters of beta and lambda. SimuMatic essentially performs a user defined number of Monte Carlo simulations based on user defined required test time or failure termination settings, and then recalculates the beta and lambda parameters for each of the generated data sets. The number of times that the Monte Carlo data sets are generated and the parameters are re-calculated is also user defined. The final output presents the calculated values of beta and lambda and allows for various types of analysis. | |||
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| align="center" valign="middle" | [http://reliawiki.com/index.php/Template:One_parameter_exp_distribution#The_One-Parameter_Exponential_Distribution 1p Exponential Distribution] | | align="center" valign="middle" | [http://reliawiki.com/index.php/Template:One_parameter_exp_distribution#The_One-Parameter_Exponential_Distribution 1p Exponential Distribution] | ||
Revision as of 23:28, 17 January 2012
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Reliability Web Notes |
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| Simumatic Data 1p-Exponential |
| Weibull++ |
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Reliability growth analysis using simulation can be a valuable tool for reliability practitioners. With this approach, reliability growth analyses are performed a large number of times on data sets that have been created using Monte Carlo simulation. The SimuMatic utility generates calculated values of beta and lambda parameters, based on user specified input parameters of beta and lambda. SimuMatic essentially performs a user defined number of Monte Carlo simulations based on user defined required test time or failure termination settings, and then recalculates the beta and lambda parameters for each of the generated data sets. The number of times that the Monte Carlo data sets are generated and the parameters are re-calculated is also user defined. The final output presents the calculated values of beta and lambda and allows for various types of analysis. |
| 1p Exponential Distribution |
