ALTA Simumatic Data Arrhenius-Weibull: Difference between revisions
Jump to navigation
Jump to search
No edit summary |
No edit summary |
||
| Line 12: | Line 12: | ||
Reliability analysis using simulation, in which reliability analyses are performed a large number of times on data sets that have been created using Monte Carlo simulation, can be a valuable tool for reliability practitioners. Such simulation analyses can assist the analyst to a) better understand life data analysis concepts, b) experiment with the influences of sample sizes and censoring schemes on analysis methods, c) construct simulation-based confidence intervals, d) better understand the concepts behind confidence intervals and e) design reliability tests. This section explores some of the results that can be obtained from simulation analyses with the SimuMatic utility in Weibull++ | Reliability analysis using simulation, in which reliability analyses are performed a large number of times on data sets that have been created using Monte Carlo simulation, can be a valuable tool for reliability practitioners. Such simulation analyses can assist the analyst to a) better understand life data analysis concepts, b) experiment with the influences of sample sizes and censoring schemes on analysis methods, c) construct simulation-based confidence intervals, d) better understand the concepts behind confidence intervals and e) design reliability tests. This section explores some of the results that can be obtained from simulation analyses with the SimuMatic utility in Weibull++ | ||
|- | |- | ||
| align="center" valign="middle" | [ | | align="center" valign="middle" | [http://www.reliawiki.com/index.php/Template:Aaw#Arrhenius-Weibull Arrhenius Weibull] | ||
|} | |} | ||
Revision as of 18:25, 18 January 2012
|
Reliability Web Notes |
|---|
| Simumatic Data Arrhenius-Weibull |
| ALTA |
|
Reliability analysis using simulation, in which reliability analyses are performed a large number of times on data sets that have been created using Monte Carlo simulation, can be a valuable tool for reliability practitioners. Such simulation analyses can assist the analyst to a) better understand life data analysis concepts, b) experiment with the influences of sample sizes and censoring schemes on analysis methods, c) construct simulation-based confidence intervals, d) better understand the concepts behind confidence intervals and e) design reliability tests. This section explores some of the results that can be obtained from simulation analyses with the SimuMatic utility in Weibull++ |
| Arrhenius Weibull |