Template:Stress-Strength Analysis in Design For Reliability - Revision history

Lisa Hacker: Redirected page to Stress-Strength Analysis

2012-08-15T06:47:00Z

Redirected page to Stress-Strength Analysis

← Older revision		Revision as of 06:47, 15 August 2012
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	~~===~~Stress-~~Strength Analysis in Design for Reliability===~~		#REDIRECT [[Stress-Strength_Analysis]]

	~~As we know, the expected reliability is called from the following stress-strength calculation:~~

	~~<center><math>R=P[Stress\le Strength~~]~~=\int_{0}^{\infty }{{{f}_{Stress}}(x)\cdot {{R}_{Strength}}(x)}dx</math></center>~~

	The stress distribution is usually estimated from customer usage data, such as the mileage per year of a passenger car or the load distribution for a beam. The strength distribution, on the other hand, is affected by the material used in the component, the geometric dimensions and the manufacturing process.

	Because the stress distribution can be estimated from customer usage data, we can assume that <math>{f}_{Stress} </math> is known. Therefore, for a given reliability goal, the strength distribution <math> {R}_{Strength}</math> is the only unknown in the given equation. The factors that affect the strength distribution can be adjusted to obtain a strength distribution that meets the reliability goal. The following example shows how to use the Target Reliability Parameter Estimator tool in the stress-strength folio to obtain the parameters for a strength distribution that will meet a specified reliability goal.

	~~'''Example 2:'''~~
	~~{{Example: Stress-Strength Analysis for Determing Strength Distribution}}~~

Kate Racaza: /* Stress-Strength Analysis in Design for Reliability */

2012-05-30T16:25:31Z

Stress-Strength Analysis in Design for Reliability

← Older revision		Revision as of 16:25, 30 May 2012
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	The stress distribution is usually estimated from customer usage data, such as the mileage per year of a passenger car or the load distribution for a beam. The strength distribution, on the other hand, is affected by the material used in the component, the geometric dimensions and the manufacturing process.		The stress distribution is usually estimated from customer usage data, such as the mileage per year of a passenger car or the load distribution for a beam. The strength distribution, on the other hand, is affected by the material used in the component, the geometric dimensions and the manufacturing process.

	Because the stress distribution can be estimated from customer usage data, we can assume that <math>{f}_{Stress} </math> is known. Therefore, for a given reliability goal, the strength distribution <math> {R}_{Strength}</math> is the only unknown in the given equation. The factors that affect the strength distribution can be adjusted to obtain a strength distribution that meets the reliability goal. The following example shows how to use the Target Reliability Estimator tool in the stress-strength folio to obtain the parameters for a strength distribution that will meet a specified reliability goal.		Because the stress distribution can be estimated from customer usage data, we can assume that <math>{f}_{Stress} </math> is known. Therefore, for a given reliability goal, the strength distribution <math> {R}_{Strength}</math> is the only unknown in the given equation. The factors that affect the strength distribution can be adjusted to obtain a strength distribution that meets the reliability goal. The following example shows how to use the Target Reliability Parameter Estimator tool in the stress-strength folio to obtain the parameters for a strength distribution that will meet a specified reliability goal.

	'''Example 2:'''		'''Example 2:'''
	{{Example: Stress-Strength Analysis for Determing Strength Distribution}}		{{Example: Stress-Strength Analysis for Determing Strength Distribution}}

Kate Racaza: /* Stress-Strength Analysis in Design for Reliability */

2012-05-30T15:07:19Z

Stress-Strength Analysis in Design for Reliability

← Older revision		Revision as of 15:07, 30 May 2012
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	The stress distribution is usually estimated from customer usage data, such as the mileage per year of a passenger car or the load distribution for a beam. The strength distribution, on the other hand, is affected by the material used in the component, the geometric dimensions and the manufacturing process.		The stress distribution is usually estimated from customer usage data, such as the mileage per year of a passenger car or the load distribution for a beam. The strength distribution, on the other hand, is affected by the material used in the component, the geometric dimensions and the manufacturing process.

	Because the stress distribution can be estimated from customer usage data, we can assume that <math>{f}_{Stress} </math> is known. Therefore, for a given reliability goal, the strength distribution <math> {R}_{Strength}</math> is the only unknown in the given equation. The factors that affect the strength distribution can be adjusted to obtain a strength distribution that meets the reliability goal. The following example ~~explains~~ how to use ~~Weibull++~~ to ~~determine~~ the parameters for a strength distribution that ~~are required to~~ meet a specified reliability goal.		Because the stress distribution can be estimated from customer usage data, we can assume that <math>{f}_{Stress} </math> is known. Therefore, for a given reliability goal, the strength distribution <math> {R}_{Strength}</math> is the only unknown in the given equation. The factors that affect the strength distribution can be adjusted to obtain a strength distribution that meets the reliability goal. The following example shows how to use the Target Reliability Estimator tool in the stress-strength folio to obtain the parameters for a strength distribution that will meet a specified reliability goal.

	'''Example 2:'''		'''Example 2:'''
	{{Example: Stress-Strength Analysis for Determing Strength Distribution}}		{{Example: Stress-Strength Analysis for Determing Strength Distribution}}

Kate Racaza: /* Stress-Strength Analysis in Design for Reliability */

2012-05-30T14:55:35Z

Stress-Strength Analysis in Design for Reliability

← Older revision		Revision as of 14:55, 30 May 2012
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	===Stress-Strength Analysis in Design for Reliability===		===Stress-Strength Analysis in Design for Reliability===

	The stress distribution usually can be estimated from customer usage data. For example, the mileage per year of a passenger car or the load distribution for a beam. The strength distribution is affected by the material used in the component, the geometric dimensions and the manufacturing process. By adjusting these factors, a strength distribution that meets the reliability goal can be obtained. The reliability goal can be used to decide the distribution goal of the strength. As we know, the expected reliability is called from the following stress-strength calculation:		As we know, the expected reliability is called from the following stress-strength calculation:

	<center><math>R=P[Stress\le Strength]=\int_{0}^{\infty }{{{f}_{Stress}}(x)\cdot {{R}_{Strength}}(x)}dx</math></center>		<center><math>R=P[Stress\le Strength]=\int_{0}^{\infty }{{{f}_{Stress}}(x)\cdot {{R}_{Strength}}(x)}dx</math></center>

	~~Since~~ the stress distribution can be estimated from customer usage data, <math>{f}_{Stress} </math> ~~can be assumed to be~~ known. ~~For~~ a given reliability goal, the strength distribution <math> {R}_{Strength}</math> is the only unknown ~~and~~ can be ~~solved from~~ the ~~above equation~~. The following example explains how to use Weibull++ to determine the parameters for a strength distribution that are required to meet a specified reliability goal.		The stress distribution is usually estimated from customer usage data, such as the mileage per year of a passenger car or the load distribution for a beam. The strength distribution, on the other hand, is affected by the material used in the component, the geometric dimensions and the manufacturing process.

			Because the stress distribution can be estimated from customer usage data, we can assume that <math>{f}_{Stress} </math> is known. Therefore, for a given reliability goal, the strength distribution <math> {R}_{Strength}</math> is the only unknown in the given equation. The factors that affect the strength distribution can be adjusted to obtain a strength distribution that meets the reliability goal. The following example explains how to use Weibull++ to determine the parameters for a strength distribution that are required to meet a specified reliability goal.

	'''Example 2:'''		'''Example 2:'''
	{{Example: Stress-Strength Analysis for Determing Strength Distribution}}		{{Example: Stress-Strength Analysis for Determing Strength Distribution}}

Lisa Hacker: /* Stress-Strength Analysis in Design for Reliability */

2012-03-30T19:10:54Z

Stress-Strength Analysis in Design for Reliability

← Older revision		Revision as of 19:10, 30 March 2012
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	===Stress-Strength Analysis in Design for Reliability===		===Stress-Strength Analysis in Design for Reliability===

	The stress distribution usually can be estimated from customer usage data. For example, the mileage per year of a passenger car, or the load distribution for a beam. The strength distribution is affected by the material used in a component, the geometric ~~dimension~~ and the manufacturing process. By adjusting these factors, a strength distribution that meets the reliability goal can be obtained. The reliability goal is used to decide the distribution goal of the strength. As we know, the expected reliability is called from the following stress-strength calculation:		The stress distribution usually can be estimated from customer usage data. For example, the mileage per year of a passenger car or the load distribution for a beam. The strength distribution is affected by the material used in the component, the geometric dimensions and the manufacturing process. By adjusting these factors, a strength distribution that meets the reliability goal can be obtained. The reliability goal can be used to decide the distribution goal of the strength. As we know, the expected reliability is called from the following stress-strength calculation:

	<center><math>R=P[Stress\le Strength]=\int_{0}^{\infty }{{{f}_{Stress}}(x)\cdot {{R}_{Strength}}(x)}dx</math></center>		<center><math>R=P[Stress\le Strength]=\int_{0}^{\infty }{{{f}_{Stress}}(x)\cdot {{R}_{Strength}}(x)}dx</math></center>

	Since the stress distribution can be estimated from customer usage data, <math>{f}_{Stress} </math> can be assumed to be known. For a given reliability goal, the strength distribution <math> {R}_{Strength}</math> is the only unknown and can be solved from the above equation. The following example explains how to use Weibull++ to determine the parameters for a strength distribution.		Since the stress distribution can be estimated from customer usage data, <math>{f}_{Stress} </math> can be assumed to be known. For a given reliability goal, the strength distribution <math> {R}_{Strength}</math> is the only unknown and can be solved from the above equation. The following example explains how to use Weibull++ to determine the parameters for a strength distribution that are required to meet a specified reliability goal.

	'''Example 2:'''		'''Example 2:'''
	{{Example: Stress-Strength Analysis for Determing Strength Distribution}}		{{Example: Stress-Strength Analysis for Determing Strength Distribution}}

Lisa Hacker: /* Stress-Strength Analysis in Design For Reliability */

2012-03-30T18:38:24Z

Stress-Strength Analysis in Design For Reliability

← Older revision		Revision as of 18:38, 30 March 2012
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	===Stress-Strength Analysis in Design ~~For~~ Reliability===		===Stress-Strength Analysis in Design for Reliability===

	The stress distribution usually can be estimated from customer usage data. For example, the ~~milage~~ per year of a ~~passanger~~ car, or the load distribution for a beam. The strength distribution is affected by the material used in a component, the geometric dimension, and the manufacturing process. By adjusting these factors, a strength distribution that meets the reliability goal can be obtained. The reliability goal is used to decide the distribution goal of the ~~strenght~~. As we know, the expected reliability is ~~callled~~ from the following stress-strength calculation:		The stress distribution usually can be estimated from customer usage data. For example, the mileage per year of a passenger car, or the load distribution for a beam. The strength distribution is affected by the material used in a component, the geometric dimension and the manufacturing process. By adjusting these factors, a strength distribution that meets the reliability goal can be obtained. The reliability goal is used to decide the distribution goal of the strength. As we know, the expected reliability is called from the following stress-strength calculation:

	<center><math>R=P[Stress\le Strength]=\int_{0}^{\infty }{{{f}_{Stress}}(x)\cdot {{R}_{Strength}}(x)}dx</math></center>		<center><math>R=P[Stress\le Strength]=\int_{0}^{\infty }{{{f}_{Stress}}(x)\cdot {{R}_{Strength}}(x)}dx</math></center>

Harry Guo: /* Stress-Strength Analysis in Design For Reliability */

2012-02-27T21:46:02Z

Stress-Strength Analysis in Design For Reliability

← Older revision		Revision as of 21:46, 27 February 2012
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	Since the stress distribution can be estimated from customer usage data, <math>{f}_{Stress} </math> can be assumed to be known. For a given reliability goal, the strength distribution <math> {R}_{Strength}</math> is the only unknown and can be solved from the above equation. The following example explains how to use Weibull++ to determine the parameters for a strength distribution.		Since the stress distribution can be estimated from customer usage data, <math>{f}_{Stress} </math> can be assumed to be known. For a given reliability goal, the strength distribution <math> {R}_{Strength}</math> is the only unknown and can be solved from the above equation. The following example explains how to use Weibull++ to determine the parameters for a strength distribution.

			'''Example 2:'''
			{{Example: Stress-Strength Analysis for Determing Strength Distribution}}

Harry Guo at 19:05, 27 February 2012

2012-02-27T19:05:10Z

← Older revision		Revision as of 19:05, 27 February 2012
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	<center><math>R=P[Stress\le Strength]=\int_{0}^{\infty }{{{f}_{Stress}}(x)\cdot {{R}_{Strength}}(x)}dx</math></center>		<center><math>R=P[Stress\le Strength]=\int_{0}^{\infty }{{{f}_{Stress}}(x)\cdot {{R}_{Strength}}(x)}dx</math></center>

	Since the stress distribution can be estimated from customer usage data, <math>{f}_{Stress} </math> can be assumed to be known. For a given reliability goal, the strength distribution <math> {R}_{Strength}</math> is the only unknown and can be solved from the above equation. The following example explains how to use Weibull++ to determine the parameters for a strength distribution.		Since the stress distribution can be estimated from customer usage data, <math>{f}_{Stress} </math> can be assumed to be known. For a given reliability goal, the strength distribution <math> {R}_{Strength}</math> is the only unknown and can be solved from the above equation. The following example explains how to use Weibull++ to determine the parameters for a strength distribution.

Harry Guo at 19:04, 27 February 2012

2012-02-27T19:04:55Z

← Older revision		Revision as of 19:04, 27 February 2012
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	<center><math>R=P[Stress\le Strength]=\int_{0}^{\infty }{{{f}_{Stress}}(x)\cdot {{R}_{Strength}}(x)}dx</math></center>		<center><math>R=P[Stress\le Strength]=\int_{0}^{\infty }{{{f}_{Stress}}(x)\cdot {{R}_{Strength}}(x)}dx</math></center>

	Since the stress distribution can be estimated from customer usage data, it can be assumed to be known. For a given reliability goal, the strength distribution is the only unknown and can be solved from the above equation. The following example explains how to use Weibull++ to determine the parameters for a strength distribution.		Since the stress distribution can be estimated from customer usage data, <math>{f}_{Stress} </math> can be assumed to be known. For a given reliability goal, the strength distribution <math> {R}_{Strength}</math> is the only unknown and can be solved from the above equation. The following example explains how to use Weibull++ to determine the parameters for a strength distribution.

Harry Guo: /* Stress-Strength Analysis in Design For Reliability */

2012-02-27T19:03:51Z

Stress-Strength Analysis in Design For Reliability

← Older revision		Revision as of 19:03, 27 February 2012
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	<center><math>R=P[Stress\le Strength]=\int_{0}^{\infty }{{{f}_{Stress}}(x)\cdot {{R}_{Strength}}(x)}dx</math></center>		<center><math>R=P[Stress\le Strength]=\int_{0}^{\infty }{{{f}_{Stress}}(x)\cdot {{R}_{Strength}}(x)}dx</math></center>


	Since the stress distribution can be estimated from customer usage data, it can be assumed to be known. For a given reliability goal, the strength distribution is the only unknown and can be solved from the above equation. The following example explains how to use Weibull++ to determine the parameters for a strength distribution.		Since the stress distribution can be estimated from customer usage data, it can be assumed to be known. For a given reliability goal, the strength distribution is the only unknown and can be solved from the above equation. The following example explains how to use Weibull++ to determine the parameters for a strength distribution.