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A New Variable-Censoring Control Chart Using Lifetime Performance Index under Exponential and Weibull Distributions.

Muhammad Aslam1, P Jeyadurga2, S Balamurali2

  • 1Department of Statistics, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia.

Computational Intelligence and Neuroscience
|January 6, 2022
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Summary

This study introduces a new control chart for reliability and life testing using lifetime performance index with Type II censoring for exponential and Weibull distributions. The chart optimizes parameters for accurate process monitoring, enhancing quality control in component and system reliability.

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Area of Science:

  • Reliability Theory
  • Statistical Quality Control
  • Life Testing Analysis

Background:

  • Exponential and Weibull distributions are standard models for component and system lifetimes in reliability engineering.
  • Effective process monitoring is crucial for maintaining quality and predicting failures in manufactured components and systems.

Purpose of the Study:

  • To design and evaluate a novel control chart utilizing the lifetime performance index.
  • To apply the control chart to exponential and Weibull distributions under Type II censoring.
  • To optimize control chart parameters for enhanced process monitoring accuracy.

Main Methods:

  • Development of a control chart based on the lifetime performance index.
  • Application of Type II censoring for data collection in life testing.
  • Utilization of Average Run Length (ARL) to assess control chart performance.
  • Simulation studies to determine optimal parameters for in-control and out-of-control scenarios.

Main Results:

  • The proposed control chart effectively monitors processes based on lifetime performance index for specified distributions.
  • Optimal values for the number of failure items and decision criteria were determined to maximize ARL performance.
  • Simulated data confirmed the practical utility and performance of the designed control chart.

Conclusions:

  • The designed control chart offers an effective method for quality control in reliability and life testing.
  • The study provides a framework for optimizing control chart parameters using ARL metrics for censored data.
  • This approach enhances the ability to detect process shifts in systems modeled by exponential and Weibull distributions.