Related Experiment Video
Updated: Aug 14, 2025

Tactile Semiautomatic Passive-Finger Angle Stimulator TSPAS
Published on: July 30, 2020
An attribute control chart for the inverse Weibull distribution under truncated life tests
Ayman Baklizi1, Sawsan Abu Ghannam1
1Statistics Program, Department of Mathematics, Statistics and Physics, College of Arts and Science, Qatar University, 2713, Doha, Qatar.
Abstract:
Statistical Process Control (SPC) is applied to monitor production processes in order to discover any problems or issues that may arise during the production process and to help in finding solutions for these issues. In this paper, we consider a situation in which the product's quality, as measured by its lifetime, is monitored. Since the monitoring requires life tests to be performed and this may take relatively long time, the test time is truncated at some pre-specified time , chosen to be related to the product's target mean life. This results in a truncated life test. The number of failures during the life test is used as an indicator of the quality of the product. We consider the situation in which the lifetimes follow the Inverse Weibull distribution. A control chart is proposed for this specific situation, thus extending the applicability of control charts methodology to situations involving truncated life tests. Simulation techniques has been employed to obtain the quantities needed for constructing the control chart with the aim that the average run length (ARL) is close to its target value. The control chart is evaluated by obtaining the ARL values when the process is out-of-control for various values of the shift coefficient. We obtained the coefficients of the control limit and the truncation coefficient for different sample sizes and average run length target values. An example on the application of the proposed control chart is provided.
Related Concept Videos
Parametric Survival Analysis: Weibull and Exponential Methods
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...
Life Tables
Finding Critical Values for Chi-Square
Survival Curves
The Kaplan-Meier estimator is the most common method for constructing survival curves. This...
Truncation in Survival Analysis
Left truncation occurs when individuals who experienced the event of interest before a certain time are not included in the study. This is often due to a "delayed entry" into the study where only those who survive until a certain entry point are...
Applications of Life Tables

