Standard Guide for Statistical Analysis of Accelerated Service Life Data
|Publication Date:||1 January 2019|
|ICS Code (Application of statistical methods):||03.120.30|
This guide describes general statistical methods for analyses of accelerated service life data. It provides a common terminology and a common methodology for calculating a quantitative estimate of functional service life.
This guide covers the application of two general models for determining service life distribution at usage condition. The Arrhenius model serves as a general model where a single stress variable, specifically temperature, affects the service life. It also covers the Eyring Model for applications where multiple stress variables act simultaneously to affect the service life.
This guide emphasizes the use of the Weibull life distribution and is written to be used in combination with Guide G166.
The uncertainty and reliability of every accelerated service life model becomes more critical as the number of stress variables increases and the extent of extrapolation from the accelerated stress levels to the usage level increases, or both. The models and methodology used in this guide are to provide examples of data analysis techniques only. The fundamental requirements of proper variable selection and measurement must still be met by the users for a meaningful model to result.
This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee.