Template:Example: Warranty Analysis Usage Format Example - Revision history

Lisa Hacker: Redirected page to Warranty Analysis Usage Format Example

2012-08-13T03:13:20Z

Redirected page to Warranty Analysis Usage Format Example

← Older revision		Revision as of 03:13, 13 August 2012
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	[[~~Category: For Deletion~~]]		#REDIRECT [[Warranty_Analysis_Usage_Format_Example]]

Kate Racaza: content moved to page: Warranty_Analysis_Usage_Format_Example

2012-07-26T05:50:13Z

content moved to page: Warranty_Analysis_Usage_Format_Example

← Older revision		Revision as of 05:50, 26 July 2012
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	~~'''Warranty Analysis Usage Format Example'''~~		[[Category: For Deletion]]

	~~Suppose that an automotive manufacturer collects the warranty returns and sales data given in the following tables. Convert this information to life data and fit a suitable distribution to it.~~

	~~<center>'''Quality In-Service Data'''</center>~~

	~~{\| border="1" class="wikitable" style="margin: 1em auto 1em auto"~~
	~~\| align="center" style="background:#f0f0f0;"\|'''Quantity In-Service'''~~
	~~\| align="center" style="background:#f0f0f0;"\|'''Date In-Service'''~~
	\|-
	~~\| 9\|\|Dec-09~~
	\|-
	~~\| 13\|\|Jan-10~~
	\|-
	~~\| 15\|\|Feb-10~~
	\|-
	~~\| 20\|\|Mar-10~~
	\|-
	~~\| 15\|\|Apr-10~~
	\|-
	~~\| 25\|\|May-10~~
	\|-
	~~\| 19\|\|Jun-10~~
	\|-
	~~\| 16\|\|Jul-10~~
	\|-
	~~\| 20\|\|Aug-10~~
	\|-
	~~\| 19\|\|Sep-10~~
	\|-
	~~\| 25\|\|Oct-10~~
	\|-
	~~\| 30\|\|Nov-10~~
	\|-
	\|
	\|}

	~~<center>'''Quality Return Data'''</center>~~

	~~{\| border="1" class="wikitable" style="margin: 1em auto 1em auto"~~
	~~\| align="center" style="background:#f0f0f0;"\|'''Quantity Returned'''~~
	~~\| align="center" style="background:#f0f0f0;"\|'''Usage at Return Date'''~~
	~~\| align="center" style="background:#f0f0f0;"\|'''Return Date'''~~
	\|-
	~~\| 1\|\|9072\|\|Dec-09~~
	\|-
	~~\| 1\|\|9743\|\|Jan-10~~
	\|-
	~~\| 1\|\|6857\|\|Feb-10~~
	\|-
	~~\| 1\|\|7651\|\|Mar-10~~
	\|-
	~~\| 1\|\|5083\|\|May-10~~
	\|-
	~~\| 1\|\|5990\|\|May-10~~
	\|-
	~~\| 1\|\|7432\|\|May-10~~
	\|-
	~~\| 1\|\|8739\|\|May-10~~
	\|-
	~~\| 1\|\|3158\|\|Jun-10~~
	\|-
	~~\| 1\|\|1136\|\|Jul-10~~
	\|-
	~~\| 1\|\|4646\|\|Aug-10~~
	\|-
	~~\| 1\|\|3965\|\|Sep-10~~
	\|-
	~~\| 1\|\|3117\|\|Oct-10~~
	\|-
	~~\| 1\|\|3250\|\|Nov-10~~
	\|-
	\|
	\|}


	~~'''Solution'''~~

	~~To perform this analysis using the Warranty Analysis tool in Weibull++, create a Warranty Analysis Folio and choose I want to enter data in usage format in the Project Wizard.~~
	~~The sales data are entered as follows:~~

	~~[[Image:Usage In-Service Weibull Data.png\|thumb\|center\|500px\| ]]~~

	~~The return data (accumulated mileage at time of failure and the date the failed unit was put in-service ( <math>DIS</math> )) is shown in the next figure.~~

	~~[[Image:Usage Return Weibull Data.png\|thumb\|center\|500px\| ]]~~

	~~The above figure also shows the calculation End Date ( <math>ED</math> ), which can be set on the Analysis page of the Control Panel. In this example, the warranty data were collected until 12/1/2010.~~

	The user has the option to input either a constant value that describes an average of usage or a distribution with intervals to be considered in the analysis. In this example, the manufacturer has been documenting the mileage accumulation per year for this type of product across the customer base in comparable regions for many years. The yearly usage has been determined to follow a lognormal distribution with <math>{{\mu }_{T\prime }}=9.38</math> , <math>{{\sigma }_{T\prime }}=0.085</math> . Graphically, the distribution looks as follows.

	~~[[Image:Usage lognormal pdf.png\|thumb\|center\|500px\| ]]~~


	~~The usage distribution is specified on the Usage page of the Control Panel, as shown next.~~

	~~[[Image:Specify Usage Distribution.png\|thumb\|center\|250px\| ]]~~

	~~Note that the Interval Width was defined to be 1000 miles (as seen in the above figure). This interval facilitates the calculations of mileage usage for the suspensions in the data set.~~

	In addition to 14 failures, the data set contains 212 suspensions spread according to the defined usage distribution. This data set contains 12 groups of suspensions that have the same age. To illustrate the analysis procedure explained above, let us use one suspension group, the first group. The first group contains 9 units that went in service on a given date; 1 unit failed from that batch. Therefore, 8 suspensions have survived from December 2009 until the beginning of December 2010, a total of 12 months. The calculations are summarized as follows.

	~~[[Image:Usage Suspension Allocation.PNG\|center\|500px\| ]]~~

	The two columns on the right constitute the calculated suspension data (number of suspensions and their usage) for the first group. The calculation in the above table is then repeated for each of the remaining 11 suspension groups in the data set. We then add the resulting data and the failure data and proceed with estimating a failure distribution model.

	The data set that is used to perform the estimation of the failure distribution model can be extracted and displayed by selecting Transfer Life Data to New Folio from the Data menu. The failures and suspensions data set, as presented in the Standard Folio, is partially shown next. (Note that the Folio contains 66 rows.)

	~~[[Image:Usage Example Weibull Std Folio Data.png\|thumb\|center\|500px\| ]]~~

	The entered sales and return data set, the usage distribution and the interval width in the Warranty Folio can be used to derive a failure distribution. The manufacturer assumes that the observed failures are typically modeled by a lognormal distribution. The parameters of the distribution are estimated (by clicking on the Calculate button) to be:

	~~::<math>\begin{align}~~
	~~& {{\mu }_{T\prime }}= & 10.4747 \\~~
	~~& {{\sigma }_{T\prime }}= & 1.1159~~
	~~\end{align}</math>~~

	~~The reliability plot (with mileage being the random variable driving reliability), along with the 90% confidence bounds on reliability, is shown next.~~

	[[~~Image~~:~~Usage Example Reliability Plot.png\|thumb\|center\|500px\|~~ ]]

Chris Kahn at 19:16, 21 May 2012

2012-05-21T19:16:56Z

Nicolette Young at 22:31, 25 April 2012

2012-04-25T22:31:27Z

← Older revision		Revision as of 22:31, 25 April 2012
Line 101:		Line 101:
	In addition to 14 failures, the data set contains 212 suspensions spread according to the defined usage distribution. This data set contains 12 groups of suspensions that have the same age. To illustrate the analysis procedure explained above, let us use one suspension group, the first group. The first group contains 9 units that went in service on a given date; 1 unit failed from that batch. Therefore, 8 suspensions have survived from December 2009 until the beginning of December 2010, a total of 12 months. The calculations are summarized as follows.		In addition to 14 failures, the data set contains 212 suspensions spread according to the defined usage distribution. This data set contains 12 groups of suspensions that have the same age. To illustrate the analysis procedure explained above, let us use one suspension group, the first group. The first group contains 9 units that went in service on a given date; 1 unit failed from that batch. Therefore, 8 suspensions have survived from December 2009 until the beginning of December 2010, a total of 12 months. The calculations are summarized as follows.

	[[Image:Usage Suspension Allocation.PNG\|center\|~~400px~~\| ]]		[[Image:Usage Suspension Allocation.PNG\|center\|300px\| ]]

	The two columns on the right constitute the calculated suspension data (number of suspensions and their usage) for the first group. The calculation in the above table is then repeated for each of the remaining 11 suspension groups in the data set. We then add the resulting data and the failure data and proceed with estimating a failure distribution model.		The two columns on the right constitute the calculated suspension data (number of suspensions and their usage) for the first group. The calculation in the above table is then repeated for each of the remaining 11 suspension groups in the data set. We then add the resulting data and the failure data and proceed with estimating a failure distribution model.

Nicolette Young at 22:31, 25 April 2012

2012-04-25T22:31:02Z

← Older revision		Revision as of 22:31, 25 April 2012
Line 95:		Line 95:
	The usage distribution is specified on the Usage page of the Control Panel, as shown next.		The usage distribution is specified on the Usage page of the Control Panel, as shown next.

	[[Image:Specify Usage Distribution.png\|thumb\|center\|~~250px~~\| ]]		[[Image:Specify Usage Distribution.png\|thumb\|center\|200px\| ]]

	Note that the Interval Width was defined to be 1000 miles (as seen in the above figure). This interval facilitates the calculations of mileage usage for the suspensions in the data set.		Note that the Interval Width was defined to be 1000 miles (as seen in the above figure). This interval facilitates the calculations of mileage usage for the suspensions in the data set.
Line 101:		Line 101:
	In addition to 14 failures, the data set contains 212 suspensions spread according to the defined usage distribution. This data set contains 12 groups of suspensions that have the same age. To illustrate the analysis procedure explained above, let us use one suspension group, the first group. The first group contains 9 units that went in service on a given date; 1 unit failed from that batch. Therefore, 8 suspensions have survived from December 2009 until the beginning of December 2010, a total of 12 months. The calculations are summarized as follows.		In addition to 14 failures, the data set contains 212 suspensions spread according to the defined usage distribution. This data set contains 12 groups of suspensions that have the same age. To illustrate the analysis procedure explained above, let us use one suspension group, the first group. The first group contains 9 units that went in service on a given date; 1 unit failed from that batch. Therefore, 8 suspensions have survived from December 2009 until the beginning of December 2010, a total of 12 months. The calculations are summarized as follows.

	[[Image:Usage Suspension Allocation.PNG\|center\|~~300px~~\| ]]		[[Image:Usage Suspension Allocation.PNG\|center\|400px\| ]]

	The two columns on the right constitute the calculated suspension data (number of suspensions and their usage) for the first group. The calculation in the above table is then repeated for each of the remaining 11 suspension groups in the data set. We then add the resulting data and the failure data and proceed with estimating a failure distribution model.		The two columns on the right constitute the calculated suspension data (number of suspensions and their usage) for the first group. The calculation in the above table is then repeated for each of the remaining 11 suspension groups in the data set. We then add the resulting data and the failure data and proceed with estimating a failure distribution model.

Nicolette Young at 22:11, 25 April 2012

2012-04-25T22:11:29Z

Nicolette Young at 23:05, 2 April 2012

2012-04-02T23:05:22Z

← Older revision		Revision as of 23:05, 2 April 2012
Line 101:		Line 101:
	In addition to 14 failures, the data set contains 212 suspensions spread according to the defined usage distribution. This data set contains 12 groups of suspensions that have the same age. To illustrate the analysis procedure explained above, let us use one suspension group, the first group. The first group contains 9 units that went in service on a given date; 1 unit failed from that batch. Therefore, 8 suspensions have survived from December 2009 until the beginning of December 2010, a total of 12 months. The calculations are summarized as follows.		In addition to 14 failures, the data set contains 212 suspensions spread according to the defined usage distribution. This data set contains 12 groups of suspensions that have the same age. To illustrate the analysis procedure explained above, let us use one suspension group, the first group. The first group contains 9 units that went in service on a given date; 1 unit failed from that batch. Therefore, 8 suspensions have survived from December 2009 until the beginning of December 2010, a total of 12 months. The calculations are summarized as follows.

	[[Image:Usage Suspension Allocation.PNG\|center\|~~400px~~\| ]]		[[Image:Usage Suspension Allocation.PNG\|center\|500px\| ]]

	The two columns on the right constitute the calculated suspension data (number of suspensions and their usage) for the first group. The calculation in the above table is then repeated for each of the remaining 11 suspension groups in the data set. We then add the resulting data and the failure data and proceed with estimating a failure distribution model.		The two columns on the right constitute the calculated suspension data (number of suspensions and their usage) for the first group. The calculation in the above table is then repeated for each of the remaining 11 suspension groups in the data set. We then add the resulting data and the failure data and proceed with estimating a failure distribution model.

Nicolette Young at 18:53, 16 March 2012

2012-03-16T18:53:57Z

← Older revision		Revision as of 18:53, 16 March 2012
Line 101:		Line 101:
	In addition to 14 failures, the data set contains 212 suspensions spread according to the defined usage distribution. This data set contains 12 groups of suspensions that have the same age. To illustrate the analysis procedure explained above, let us use one suspension group, the first group. The first group contains 9 units that went in service on a given date; 1 unit failed from that batch. Therefore, 8 suspensions have survived from December 2009 until the beginning of December 2010, a total of 12 months. The calculations are summarized as follows.		In addition to 14 failures, the data set contains 212 suspensions spread according to the defined usage distribution. This data set contains 12 groups of suspensions that have the same age. To illustrate the analysis procedure explained above, let us use one suspension group, the first group. The first group contains 9 units that went in service on a given date; 1 unit failed from that batch. Therefore, 8 suspensions have survived from December 2009 until the beginning of December 2010, a total of 12 months. The calculations are summarized as follows.

	[[Image:Usage Suspension Allocation.~~png~~\|center\|400px\| ]]		[[Image:Usage Suspension Allocation.PNG\|center\|400px\| ]]

	The two columns on the right constitute the calculated suspension data (number of suspensions and their usage) for the first group. The calculation in the above table is then repeated for each of the remaining 11 suspension groups in the data set. We then add the resulting data and the failure data and proceed with estimating a failure distribution model.		The two columns on the right constitute the calculated suspension data (number of suspensions and their usage) for the first group. The calculation in the above table is then repeated for each of the remaining 11 suspension groups in the data set. We then add the resulting data and the failure data and proceed with estimating a failure distribution model.

Nicolette Young at 18:53, 16 March 2012

2012-03-16T18:53:34Z

← Older revision		Revision as of 18:53, 16 March 2012
Line 101:		Line 101:
	In addition to 14 failures, the data set contains 212 suspensions spread according to the defined usage distribution. This data set contains 12 groups of suspensions that have the same age. To illustrate the analysis procedure explained above, let us use one suspension group, the first group. The first group contains 9 units that went in service on a given date; 1 unit failed from that batch. Therefore, 8 suspensions have survived from December 2009 until the beginning of December 2010, a total of 12 months. The calculations are summarized as follows.		In addition to 14 failures, the data set contains 212 suspensions spread according to the defined usage distribution. This data set contains 12 groups of suspensions that have the same age. To illustrate the analysis procedure explained above, let us use one suspension group, the first group. The first group contains 9 units that went in service on a given date; 1 unit failed from that batch. Therefore, 8 suspensions have survived from December 2009 until the beginning of December 2010, a total of 12 months. The calculations are summarized as follows.

	[[Image:Usage Suspension Allocation.~~PNG\|thumb~~\|center\|400px\| ]]		[[Image:Usage Suspension Allocation.png\|center\|400px\| ]]

	The two columns on the right constitute the calculated suspension data (number of suspensions and their usage) for the first group. The calculation in the above table is then repeated for each of the remaining 11 suspension groups in the data set. We then add the resulting data and the failure data and proceed with estimating a failure distribution model.		The two columns on the right constitute the calculated suspension data (number of suspensions and their usage) for the first group. The calculation in the above table is then repeated for each of the remaining 11 suspension groups in the data set. We then add the resulting data and the failure data and proceed with estimating a failure distribution model.

Harry Guo at 21:01, 2 March 2012

2012-03-02T21:01:29Z

← Older revision		Revision as of 21:01, 2 March 2012
Line 36:		Line 36:
	\|}		\|}

			<center>'''Quality Return Data'''</center>

	~~[[Image~~:Usage ~~Example~~ Return ~~Raw Data.png~~\|~~thumb~~\|~~center~~\|~~400px~~\| ]]		{\| border="1" class="wikitable" style="margin: 1em auto 1em auto"
			\| align="center" style="background:#f0f0f0;"\|'''Quantity Returned'''
			\| align="center" style="background:#f0f0f0;"\|'''Usage at Return Date'''
			\| align="center" style="background:#f0f0f0;"\|'''Return Date'''
			\|-
			\| 1\|\|9072\|\|Dec-09
			\|-
			\| 1\|\|9743\|\|Jan-10
			\|-
			\| 1\|\|6857\|\|Feb-10
			\|-
			\| 1\|\|7651\|\|Mar-10
			\|-
			\| 1\|\|5083\|\|May-10
			\|-
			\| 1\|\|5990\|\|May-10
			\|-
			\| 1\|\|7432\|\|May-10
			\|-
			\| 1\|\|8739\|\|May-10
			\|-
			\| 1\|\|3158\|\|Jun-10
			\|-
			\| 1\|\|1136\|\|Jul-10
			\|-
			\| 1\|\|4646\|\|Aug-10
			\|-
			\| 1\|\|3965\|\|Sep-10
			\|-
			\| 1\|\|3117\|\|Oct-10
			\|-
			\| 1\|\|3250\|\|Nov-10
			\|-
			\|
			\|}

← Older revision		Revision as of 19:16, 21 May 2012
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	The sales data are entered as follows:		The sales data are entered as follows:

	[[Image:Usage In-Service Weibull Data.png\|thumb\|center\|~~250px~~\| ]]		[[Image:Usage In-Service Weibull Data.png\|thumb\|center\|500px\| ]]

	The return data (accumulated mileage at time of failure and the date the failed unit was put in-service ( <math>DIS</math> )) is shown in the next figure.		The return data (accumulated mileage at time of failure and the date the failed unit was put in-service ( <math>DIS</math> )) is shown in the next figure.

	[[Image:Usage Return Weibull Data.png\|thumb\|center\|~~250px~~\| ]]		[[Image:Usage Return Weibull Data.png\|thumb\|center\|500px\| ]]

	The above figure also shows the calculation End Date ( <math>ED</math> ), which can be set on the Analysis page of the Control Panel. In this example, the warranty data were collected until 12/1/2010.		The above figure also shows the calculation End Date ( <math>ED</math> ), which can be set on the Analysis page of the Control Panel. In this example, the warranty data were collected until 12/1/2010.
Line 90:		Line 90:
	The user has the option to input either a constant value that describes an average of usage or a distribution with intervals to be considered in the analysis. In this example, the manufacturer has been documenting the mileage accumulation per year for this type of product across the customer base in comparable regions for many years. The yearly usage has been determined to follow a lognormal distribution with <math>{{\mu }_{T\prime }}=9.38</math> , <math>{{\sigma }_{T\prime }}=0.085</math> . Graphically, the distribution looks as follows.		The user has the option to input either a constant value that describes an average of usage or a distribution with intervals to be considered in the analysis. In this example, the manufacturer has been documenting the mileage accumulation per year for this type of product across the customer base in comparable regions for many years. The yearly usage has been determined to follow a lognormal distribution with <math>{{\mu }_{T\prime }}=9.38</math> , <math>{{\sigma }_{T\prime }}=0.085</math> . Graphically, the distribution looks as follows.

	[[Image:Usage lognormal pdf.png\|thumb\|center\|~~250px~~\| ]]		[[Image:Usage lognormal pdf.png\|thumb\|center\|500px\| ]]


	The usage distribution is specified on the Usage page of the Control Panel, as shown next.		The usage distribution is specified on the Usage page of the Control Panel, as shown next.

	[[Image:Specify Usage Distribution.png\|thumb\|center\|~~200px~~\| ]]		[[Image:Specify Usage Distribution.png\|thumb\|center\|250px\| ]]

	Note that the Interval Width was defined to be 1000 miles (as seen in the above figure). This interval facilitates the calculations of mileage usage for the suspensions in the data set.		Note that the Interval Width was defined to be 1000 miles (as seen in the above figure). This interval facilitates the calculations of mileage usage for the suspensions in the data set.
Line 101:		Line 101:
	In addition to 14 failures, the data set contains 212 suspensions spread according to the defined usage distribution. This data set contains 12 groups of suspensions that have the same age. To illustrate the analysis procedure explained above, let us use one suspension group, the first group. The first group contains 9 units that went in service on a given date; 1 unit failed from that batch. Therefore, 8 suspensions have survived from December 2009 until the beginning of December 2010, a total of 12 months. The calculations are summarized as follows.		In addition to 14 failures, the data set contains 212 suspensions spread according to the defined usage distribution. This data set contains 12 groups of suspensions that have the same age. To illustrate the analysis procedure explained above, let us use one suspension group, the first group. The first group contains 9 units that went in service on a given date; 1 unit failed from that batch. Therefore, 8 suspensions have survived from December 2009 until the beginning of December 2010, a total of 12 months. The calculations are summarized as follows.

	[[Image:Usage Suspension Allocation.PNG\|center\|~~300px~~\| ]]		[[Image:Usage Suspension Allocation.PNG\|center\|500px\| ]]

	The two columns on the right constitute the calculated suspension data (number of suspensions and their usage) for the first group. The calculation in the above table is then repeated for each of the remaining 11 suspension groups in the data set. We then add the resulting data and the failure data and proceed with estimating a failure distribution model.		The two columns on the right constitute the calculated suspension data (number of suspensions and their usage) for the first group. The calculation in the above table is then repeated for each of the remaining 11 suspension groups in the data set. We then add the resulting data and the failure data and proceed with estimating a failure distribution model.
Line 107:		Line 107:
	The data set that is used to perform the estimation of the failure distribution model can be extracted and displayed by selecting Transfer Life Data to New Folio from the Data menu. The failures and suspensions data set, as presented in the Standard Folio, is partially shown next. (Note that the Folio contains 66 rows.)		The data set that is used to perform the estimation of the failure distribution model can be extracted and displayed by selecting Transfer Life Data to New Folio from the Data menu. The failures and suspensions data set, as presented in the Standard Folio, is partially shown next. (Note that the Folio contains 66 rows.)

	[[Image:Usage Example Weibull Std Folio Data.png\|thumb\|center\|~~250px~~\| ]]		[[Image:Usage Example Weibull Std Folio Data.png\|thumb\|center\|500px\| ]]

	The entered sales and return data set, the usage distribution and the interval width in the Warranty Folio can be used to derive a failure distribution. The manufacturer assumes that the observed failures are typically modeled by a lognormal distribution. The parameters of the distribution are estimated (by clicking on the Calculate button) to be:		The entered sales and return data set, the usage distribution and the interval width in the Warranty Folio can be used to derive a failure distribution. The manufacturer assumes that the observed failures are typically modeled by a lognormal distribution. The parameters of the distribution are estimated (by clicking on the Calculate button) to be:
Line 118:		Line 118:
	The reliability plot (with mileage being the random variable driving reliability), along with the 90% confidence bounds on reliability, is shown next.		The reliability plot (with mileage being the random variable driving reliability), along with the 90% confidence bounds on reliability, is shown next.

	[[Image:Usage Example Reliability Plot.png\|thumb\|center\|~~250px~~\| ]]		[[Image:Usage Example Reliability Plot.png\|thumb\|center\|500px\| ]]

← Older revision		Revision as of 22:11, 25 April 2012
Line 80:		Line 80:
	The sales data are entered as follows:		The sales data are entered as follows:

	[[Image:Usage In-Service Weibull Data.png\|thumb\|center\|~~400px~~\| ]]		[[Image:Usage In-Service Weibull Data.png\|thumb\|center\|250px\| ]]

	The return data (accumulated mileage at time of failure and the date the failed unit was put in-service ( <math>DIS</math> )) is shown in the next figure.		The return data (accumulated mileage at time of failure and the date the failed unit was put in-service ( <math>DIS</math> )) is shown in the next figure.

	[[Image:Usage Return Weibull Data.png\|thumb\|center\|~~400px~~\| ]]		[[Image:Usage Return Weibull Data.png\|thumb\|center\|250px\| ]]

	The above figure also shows the calculation End Date ( <math>ED</math> ), which can be set on the Analysis page of the Control Panel. In this example, the warranty data were collected until 12/1/2010.		The above figure also shows the calculation End Date ( <math>ED</math> ), which can be set on the Analysis page of the Control Panel. In this example, the warranty data were collected until 12/1/2010.
Line 90:		Line 90:
	The user has the option to input either a constant value that describes an average of usage or a distribution with intervals to be considered in the analysis. In this example, the manufacturer has been documenting the mileage accumulation per year for this type of product across the customer base in comparable regions for many years. The yearly usage has been determined to follow a lognormal distribution with <math>{{\mu }_{T\prime }}=9.38</math> , <math>{{\sigma }_{T\prime }}=0.085</math> . Graphically, the distribution looks as follows.		The user has the option to input either a constant value that describes an average of usage or a distribution with intervals to be considered in the analysis. In this example, the manufacturer has been documenting the mileage accumulation per year for this type of product across the customer base in comparable regions for many years. The yearly usage has been determined to follow a lognormal distribution with <math>{{\mu }_{T\prime }}=9.38</math> , <math>{{\sigma }_{T\prime }}=0.085</math> . Graphically, the distribution looks as follows.

	[[Image:Usage lognormal pdf.png\|thumb\|center\|~~400px~~\| ]]		[[Image:Usage lognormal pdf.png\|thumb\|center\|250px\| ]]


	The usage distribution is specified on the Usage page of the Control Panel, as shown next.		The usage distribution is specified on the Usage page of the Control Panel, as shown next.

	[[Image:Specify Usage Distribution.png\|thumb\|center\|~~400px~~\| ]]		[[Image:Specify Usage Distribution.png\|thumb\|center\|250px\| ]]

	Note that the Interval Width was defined to be 1000 miles (as seen in the above figure). This interval facilitates the calculations of mileage usage for the suspensions in the data set.		Note that the Interval Width was defined to be 1000 miles (as seen in the above figure). This interval facilitates the calculations of mileage usage for the suspensions in the data set.
Line 101:		Line 101:
	In addition to 14 failures, the data set contains 212 suspensions spread according to the defined usage distribution. This data set contains 12 groups of suspensions that have the same age. To illustrate the analysis procedure explained above, let us use one suspension group, the first group. The first group contains 9 units that went in service on a given date; 1 unit failed from that batch. Therefore, 8 suspensions have survived from December 2009 until the beginning of December 2010, a total of 12 months. The calculations are summarized as follows.		In addition to 14 failures, the data set contains 212 suspensions spread according to the defined usage distribution. This data set contains 12 groups of suspensions that have the same age. To illustrate the analysis procedure explained above, let us use one suspension group, the first group. The first group contains 9 units that went in service on a given date; 1 unit failed from that batch. Therefore, 8 suspensions have survived from December 2009 until the beginning of December 2010, a total of 12 months. The calculations are summarized as follows.

	[[Image:Usage Suspension Allocation.PNG\|center\|~~500px~~\| ]]		[[Image:Usage Suspension Allocation.PNG\|center\|300px\| ]]

	The two columns on the right constitute the calculated suspension data (number of suspensions and their usage) for the first group. The calculation in the above table is then repeated for each of the remaining 11 suspension groups in the data set. We then add the resulting data and the failure data and proceed with estimating a failure distribution model.		The two columns on the right constitute the calculated suspension data (number of suspensions and their usage) for the first group. The calculation in the above table is then repeated for each of the remaining 11 suspension groups in the data set. We then add the resulting data and the failure data and proceed with estimating a failure distribution model.
Line 107:		Line 107:
	The data set that is used to perform the estimation of the failure distribution model can be extracted and displayed by selecting Transfer Life Data to New Folio from the Data menu. The failures and suspensions data set, as presented in the Standard Folio, is partially shown next. (Note that the Folio contains 66 rows.)		The data set that is used to perform the estimation of the failure distribution model can be extracted and displayed by selecting Transfer Life Data to New Folio from the Data menu. The failures and suspensions data set, as presented in the Standard Folio, is partially shown next. (Note that the Folio contains 66 rows.)

	[[Image:Usage Example Weibull Std Folio Data.png\|thumb\|center\|~~400px~~\| ]]		[[Image:Usage Example Weibull Std Folio Data.png\|thumb\|center\|250px\| ]]

	The entered sales and return data set, the usage distribution and the interval width in the Warranty Folio can be used to derive a failure distribution. The manufacturer assumes that the observed failures are typically modeled by a lognormal distribution. The parameters of the distribution are estimated (by clicking on the Calculate button) to be:		The entered sales and return data set, the usage distribution and the interval width in the Warranty Folio can be used to derive a failure distribution. The manufacturer assumes that the observed failures are typically modeled by a lognormal distribution. The parameters of the distribution are estimated (by clicking on the Calculate button) to be:
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	The reliability plot (with mileage being the random variable driving reliability), along with the 90% confidence bounds on reliability, is shown next.		The reliability plot (with mileage being the random variable driving reliability), along with the 90% confidence bounds on reliability, is shown next.

	[[Image:Usage Example Reliability Plot.png\|thumb\|center\|~~400px~~\| ]]		[[Image:Usage Example Reliability Plot.png\|thumb\|center\|250px\| ]]