Example Using a Distribution to Approximate the CDF - Revision history

Lisa Hacker at 20:57, 18 September 2023

2023-09-18T20:57:24Z

← Older revision		Revision as of 20:57, 18 September 2023
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	<noinclude>{{Banner BlockSim Examples}}		<noinclude>{{Banner BlockSim Examples}}
	''This example appears in the [~~[Time-Dependent_System_Reliability_(Analytical)#Approximating the~~ System ~~cdf\|System Analysis Reference book]~~]''.		''This example appears in the [https://help.reliasoft.com/reference/system_analysis System analysis reference]''.

Richard House at 21:14, 5 January 2016

2016-01-05T21:14:00Z

← Older revision		Revision as of 21:14, 5 January 2016
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	[[Image:Fig 5.13.PNG\|center\|250px\|<div align="center"> Representing a system with a distribution.</div>]]		[[Image:Fig 5.13.PNG\|center\|250px\|<div align="center"> Representing a system with a distribution.</div>\|link=]]


	This opens the Distribution Estimator window, which allows you to select a distribution to represent the data.		This opens the Distribution Estimator window, which allows you to select a distribution to represent the data.

	[[Image:Fig 5.12.PNG\|center\|~~450px~~\|<div align="center"> Distribution Estimator.</div>]]		[[Image:Fig 5.12.PNG\|center\|495px\|<div align="center"> Distribution Estimator.</div>\|link=]]

	When you analyze the diagram, BlockSim will generate a number of system failure times based on the system's reliability function. The system's reliability function can be used to solve for a time value associated with an unreliability value. For example, consider an unreliability value of <math>F(t)=0.11\,\!</math>. Using the system's reliability equation, the corresponding time-to-failure for a 0.11 unreliability is 389.786 hours. The distribution of the generated time values can then be fitted to a probability distribution function.		When you analyze the diagram, BlockSim will generate a number of system failure times based on the system's reliability function. The system's reliability function can be used to solve for a time value associated with an unreliability value. For example, consider an unreliability value of <math>F(t)=0.11\,\!</math>. Using the system's reliability equation, the corresponding time-to-failure for a 0.11 unreliability is 389.786 hours. The distribution of the generated time values can then be fitted to a probability distribution function.
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	[[Image:Fig 5.14.PNG\|center\|~~500px~~\|<div align="center"> Using Weibull++ to calculate distribution parameters.</div>]]		[[Image:Fig 5.14.PNG\|center\|747px\|<div align="center"> Using Weibull++ to calculate distribution parameters.</div>\|link=]]

Richard House at 21:19, 17 September 2012

2012-09-17T21:19:52Z

← Older revision		Revision as of 21:19, 17 September 2012
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	Components <math>A\,\!</math> through <math>E\,\!</math> are Weibull distributed with <math>\beta =1.2\,\!</math> and <math>\eta =1230\,\!</math> hours. The starting and ending blocks cannot fail. Compute a single Weibull distribution approximation for the system.</noinclude><includeonly>Compute a single Weibull distribution approximation for the parallel system in the previous example.</includeonly>		Components <math>A\,\!</math> through <math>E\,\!</math> are Weibull distributed with <math>\beta =1.2\,\!</math> and <math>\eta =1230\,\!</math> hours. The starting and ending blocks cannot fail. Compute a single Weibull distribution approximation for the system.</noinclude><includeonly>Compute a single Weibull distribution approximation for the parallel system in the previous example.</includeonly>
	<!-- THIS EXAMPLE USES THE DATA SET FROM ANOTHER EXAMPLE. IF YOU EDIT THE DATA SET ON THIS PAGE, YOU MUST ALSO EDIT THE DATA SET IN THE PAGE: Time-Dependent System Reliability for Components in Parallel -->		<!-- THIS EXAMPLE USES THE DATA SET FROM ANOTHER EXAMPLE. IF YOU EDIT THE DATA SET ON THIS PAGE, YOU MUST ALSO EDIT THE DATA SET IN THE PAGE: Time-Dependent System Reliability for Components in Parallel -->

	'''Solution'''		'''Solution'''

	Assume that the system can be approximated by a 2-parameter Weibull distribution with <math>\beta =2.02109\,\!</math> and <math>\eta =1123.51\,\!</math>. In BlockSim, this is accomplished by representing the entire system as one distribution. To do this, click the '''Distribution fit''' area on the diagram's control panel, as shown next.		Assume that the system can be approximated by a 2-parameter Weibull distribution with <math>\beta =2.02109\,\!</math> and <math>\eta =1123.51\,\!</math>. In BlockSim, this is accomplished by representing the entire system as one distribution. To do this, click the '''Distribution fit''' area on the diagram's control panel, as shown next.


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	[[Image:Fig 5.12.PNG\|center\|450px\|<div align="center"> Distribution Estimator.</div>]]		[[Image:Fig 5.12.PNG\|center\|450px\|<div align="center"> Distribution Estimator.</div>]]

	When you analyze the diagram, BlockSim will generate a number of system failure times based on the system's reliability function. The system's reliability function can be used to solve for a time value associated with an unreliability value. For example, consider an unreliability value of <math>F(t)=0.11\,\!</math>. Using the system's reliability equation, the corresponding time-to-failure for a 0.11 unreliability is 389.786 hours. The distribution of the generated time values can then be fitted to a probability distribution function.		When you analyze the diagram, BlockSim will generate a number of system failure times based on the system's reliability function. The system's reliability function can be used to solve for a time value associated with an unreliability value. For example, consider an unreliability value of <math>F(t)=0.11\,\!</math>. Using the system's reliability equation, the corresponding time-to-failure for a 0.11 unreliability is 389.786 hours. The distribution of the generated time values can then be fitted to a probability distribution function.

	When enough points have been generated, the selected distribution will be fitted to the generated data set and the distribution's parameters will be calculated. In addition, if ReliaSoft's Weibull++ is installed, the fit of the distribution can be analyzed using a Weibull++ standard folio, as shown in the next figure. It is recommended that the analyst examine the fit to ascertain the applicability of the approximation.		When enough points have been generated, the selected distribution will be fitted to the generated data set and the distribution's parameters will be calculated. In addition, if ReliaSoft's Weibull++ is installed, the fit of the distribution can be analyzed using a Weibull++ standard folio, as shown in the next figure. It is recommended that the analyst examine the fit to ascertain the applicability of the approximation.

Kate Racaza at 22:45, 20 August 2012

2012-08-20T22:45:48Z

← Older revision		Revision as of 22:45, 20 August 2012
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	This opens the Distribution Estimator window, which allows you to select a distribution to represent the data. BlockSim will then generate a number of system failure times based on the system's reliability function. The system's reliability function can be used to solve for a time value associated with an unreliability value. For example, consider an unreliability value of <math>F(t)=0.11\,\!</math>. Using the system's reliability equation, the corresponding time-to-failure for a 0.11 unreliability is 389.786 hours. The distribution of the generated time values can then be fitted to a probability distribution function.		This opens the Distribution Estimator window, which allows you to select a distribution to represent the data.


	[[Image:Fig 5.12.PNG\|center\|450px\|<div align="center"> Distribution Estimator.</div>]]		[[Image:Fig 5.12.PNG\|center\|450px\|<div align="center"> Distribution Estimator.</div>]]

			When you analyze the diagram, BlockSim will generate a number of system failure times based on the system's reliability function. The system's reliability function can be used to solve for a time value associated with an unreliability value. For example, consider an unreliability value of <math>F(t)=0.11\,\!</math>. Using the system's reliability equation, the corresponding time-to-failure for a 0.11 unreliability is 389.786 hours. The distribution of the generated time values can then be fitted to a probability distribution function.

			When enough points have been generated, the selected distribution will be fitted to the generated data set and the distribution's parameters will be calculated. In addition, if ReliaSoft's Weibull++ is installed, the fit of the distribution can be analyzed using a Weibull++ standard folio, as shown in the next figure. It is recommended that the analyst examine the fit to ascertain the applicability of the approximation.

	When enough points have been generated, the selected distribution will be fitted to the data set and the distribution's parameters will be ~~returned~~. In addition, if ReliaSoft's Weibull++ is installed, the fit of the distribution can be analyzed using a Weibull++ standard folio, as shown in the next figure. It is recommended that the analyst examine the fit to ascertain the applicability of the approximation.


	[[Image:Fig 5.14.PNG\|center\|500px\|<div align="center"> Using Weibull++ to calculate distribution parameters.</div>]]		[[Image:Fig 5.14.PNG\|center\|500px\|<div align="center"> Using Weibull++ to calculate distribution parameters.</div>]]

Kate Racaza at 04:40, 20 August 2012

2012-08-20T04:40:07Z

← Older revision		Revision as of 04:40, 20 August 2012
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	Components <math>A\,\!</math> through <math>E\,\!</math> are Weibull distributed with <math>\beta =1.2\,\!</math> and <math>\eta =1230\,\!</math> hours. The starting and ending blocks cannot fail. Compute a single Weibull distribution approximation for the system.</noinclude><includeonly>Compute a single Weibull distribution approximation for the parallel system in the previous example.</includeonly>		Components <math>A\,\!</math> through <math>E\,\!</math> are Weibull distributed with <math>\beta =1.2\,\!</math> and <math>\eta =1230\,\!</math> hours. The starting and ending blocks cannot fail. Compute a single Weibull distribution approximation for the system.</noinclude><includeonly>Compute a single Weibull distribution approximation for the parallel system in the previous example.</includeonly>
			<!-- THIS EXAMPLE USES THE DATA SET FROM ANOTHER EXAMPLE. IF YOU EDIT THE DATA SET ON THIS PAGE, YOU MUST ALSO EDIT THE DATA SET IN THE PAGE: Time-Dependent System Reliability for Components in Parallel -->

	'''Solution'''		'''Solution'''

Kate Racaza: Created page with '{{Banner BlockSim Examples}} ''This example appears in the [[Time-Dependent_System_Reliability_(Analytical)#Approximating the System cdf|System Analysis Reference book…'

2012-08-20T04:35:46Z

Created page with '<noinclude>{{Banner BlockSim Examples}} ''This example appears in the [[Time-Dependent_System_Reliability_(Analytical)#Approximating the System cdf|System Analysis Reference book…'

New page

<noinclude>{{Banner BlockSim Examples}}
''This example appears in the [[Time-Dependent_System_Reliability_(Analytical)#Approximating the System cdf|System Analysis Reference book]]''.

Consider the system shown next.

[[Image:BS5.5.png|center|450px|<div align="center"> Complex Bridge System. </div>]]

Components <math>A\,\!</math> through <math>E\,\!</math> are Weibull distributed with <math>\beta =1.2\,\!</math> and <math>\eta =1230\,\!</math> hours. The starting and ending blocks cannot fail. Compute a single Weibull distribution approximation for the system.</noinclude><includeonly>Compute a single Weibull distribution approximation for the parallel system in the previous example.</includeonly>

'''Solution'''

Assume that the system can be approximated by a 2-parameter Weibull distribution with <math>\beta =2.02109\,\!</math> and <math>\eta =1123.51\,\!</math>. In BlockSim, this is accomplished by representing the entire system as one distribution. To do this, click the '''Distribution fit''' area on the diagram's control panel, as shown next.

[[Image:Fig 5.13.PNG|center|250px|<div align="center"> Representing a system with a distribution.</div>]]

This opens the Distribution Estimator window, which allows you to select a distribution to represent the data. BlockSim will then generate a number of system failure times based on the system's reliability function. The system's reliability function can be used to solve for a time value associated with an unreliability value. For example, consider an unreliability value of <math>F(t)=0.11\,\!</math>. Using the system's reliability equation, the corresponding time-to-failure for a 0.11 unreliability is 389.786 hours. The distribution of the generated time values can then be fitted to a probability distribution function.

[[Image:Fig 5.12.PNG|center|450px|<div align="center"> Distribution Estimator.</div>]]

When enough points have been generated, the selected distribution will be fitted to the data set and the distribution's parameters will be returned. In addition, if ReliaSoft's Weibull++ is installed, the fit of the distribution can be analyzed using a Weibull++ standard folio, as shown in the next figure. It is recommended that the analyst examine the fit to ascertain the applicability of the approximation.

[[Image:Fig 5.14.PNG|center|500px|<div align="center"> Using Weibull++ to calculate distribution parameters.</div>]]