Template:Alta data types

Data and Data Types
The analysis of accelerated life tests relies extensively on data. Specifically, analysis relies on life and stress data or times-to-failure data at a specific stress level. The accuracy of any prediction is directly proportional to the quality and accuracy of the supplied data. Good data along with the appropriate distribution and life-stress model usually result in good predictions. Bad or insufficient data will always result in bad predictions.

In the analysis of life data, we want to use all available data sets, which sometimes are incomplete or include uncertainty as to when a failure occurred. Life data can therefore be separated into two types: complete data (all information is available) or censored data (some of the information is missing). Each type is explained next.

Censored Data
In many cases, all of the units in the sample may not have failed (i.e., the event of interest was not observed) or the exact times-to-failure of all the units are not known. This type of data is commonly called censored data. There are three types of possible censoring schemes, right censored (also called suspended data), interval censored and left censored.

It is generally recommended to avoid interval censored data because they are less informative compared to complete data. This is especially the case in accelerated life tests where the data set affects the accuracy of the fitted life-stress relationship, and subsequently, the extrapolation to Use Stress conditions. However, there are cases when interval data are unavoidable due to the nature of the product, the test and the test equipment. In those cases, caution must be taken to set the inspection intervals to be short enough to observe the spread of the failures. For example, if the inspection interval is too long, all the units in the test may fail within that interval, and thus no failure distribution could be obtained. In accelerated life testing, inspection intervals should be chosen according to the expected acceleration factor at each stress level, and therefore these intervals will be of different lengths for each stress level.

Grouped Data Analysis
Data can also be entered into ALTA individually or in groups. Grouped data analysis is used for tests in which groups of units possess the same time-to-failure or in which groups of units were suspended at the same time. We highly recommend entering redundant data in groups. Grouped data speeds data entry by the user and significantly speeds up the calculations.

A Note about Complete and Suspended Data
Depending on the event that we want to measure, data type classification (i.e., complete or suspended) can be open to interpretation. For example, under certain circumstances, and depending on the question one wishes to answer, a specimen that has failed might be classified as suspended for analysis purposes. To illustrate this, consider the following times-to-failure data for a product that can fail due to modes A, B and C: If the objective of analysis is to determine the probability of failure of the product regardless of the mode responsible for the failure, we would analyze the data with all data entries classified as failures (complete data). However, if the objective of the analysis is to determine the probability of failure of the product due to Mode A only, we would then choose to treat failures due to Modes B or C as suspended (right censored) data. Those data points would be treated as suspended data with respect to Mode A because the product operated until the recorded time without failure due to Mode A.