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Weibull++ 7 Case Studies

 


Case Study 5 - Warranty Analysis Example

Software Used: 
Weibull++ 7


Background
A company keeps track of its shipments and warranty returns on a month-by-month basis. Using the Warranty Analysis module, determine the parameters for a 2-parameter Weibull distribution and predict the number of products from each of the three shipment periods that will be returned under warranty in October.

Experiment and Data
In June, 100 units are sold and in July, three are returned. This gives three failures at one month for the June shipment. Likewise, three failures occur in August and five occur in September for this shipment. Consequently, at the end of the three-month analysis period, there are a total of 11 failures for the 100 units shipped in June. This means that 89 units are presumably still operating and can be considered suspensions at three months. For the shipment of 140 in July, two are returned the following month and four more are returned the month after that. After two months, there are 134 units from the July shipment still operating. For the final shipment of 150 in August, four fail in September, with the remaining 146 units being suspensions at one month. The shipment and returns data are shown in the following table.

                                         Returns
Month Shipments July August September
June 100 3 3 5
July 140 - 2 4
August 150 - - 4

Analysis
Step 1:
Using the New Project Wizard in Weibull++ 7, select the appropriate options to create a Warranty Analysis Folio with the Nevada data format. In Step 4 of the New Project Wizard, select the options as shown next.

New Project Wizard

Step 2: Enter the shipments data on the Sales Data Sheet and the returns data on the Returns Data Sheet, as shown next.

The shipments data entered into the Sales Data Sheet

The returns data entered into the Returns Data Sheet

Step 3: From the Returns Data Sheet, select the 2-parameter Weibull distribution with MLE and calculate the parameters.

Step 4: Next, transfer the life data to a new Standard Folio and calculate the parameters. The calculated results are beta = 2.4928 and eta = 6.6951, as shown next.

Standard Folio with calculated parameters displayed

Step 5: Return to the Warranty Analysis Folio and generate forecasts for the quantity of units that can be expected to be returned.

In the figure shown next, the Forecast Data Sheet shows the number of failures that can be expected from each shipment in upcoming months. The predicted number of products that will be returned in October are 12 from the June shipment, 11 from the July shipment and 6 from the August shipment for a total of 29 returned units.

The predicted number of products that will be returned from each shipment in upcoming months

 

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