Warranty Analysis Overview
  

Use Minitab's warranty analysis commands to analyze warranty data and predict future failures. Minitab's warranty analysis includes two components:

·    Pre-process warranty data - processes raw field data in the triangular matrix format to a regular time-to-failure data format in order to run any life data analysis.

·    Warranty prediction -Use to forecast future warranty claims or returns based on current warranty data.

Pre-process warranty data

It is common to keep track of reliability field data in the form of number systems shipped and number of systems returned from the shipment in subsequent time periods. When several shipments are made at different dates and their corresponding returns noted, the recorded data appears in the form of a triangular matrix.

This type of book keeping, however convenient, yields data formats that are incompatible with typical time-to-failure analyses. Use Pre-Process Warranty Data to process the raw field data (in the triangular matrix format) to a regular time-to-failure data format in order to get it ready for any reliability data analysis.

Warranty prediction

Knowledge of future failures is important for setting priorities and resources for corrective measures and estimating warranty costs. The number of failures in the next month, the next six month, or the next year may help ascertain the magnitude of a problem. Use Warranty Prediction to conduct failure forecasting analysis.

Warranty analysis

The typical steps in a warranty data analysis are:

1    Use Pre-Process Warranty Data to convert the data from triangular matrix format to arbitrary censoring format.

2    Use Distribution ID Plot, Arbitrary Censoring to choose an appropriate distribution for the existing data.

3    Use Warranty Prediction to predict the number or cost of future failures.

For more information, see [20].