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This study introduces a new attribute control chart for Weibull distributed product lifetimes using two-stage sampling. It optimizes control chart parameters for effective process monitoring in industrial settings.

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Area of Science:

  • Quality Control
  • Statistical Process Control
  • Reliability Engineering

Background:

  • Traditional control charts often assume specific lifetime distributions, which may not always hold true.
  • Product lifetime data frequently follows a Weibull distribution, necessitating specialized control charting methods.
  • Truncated life testing and two-stage sampling are practical approaches in industrial quality assessment.

Purpose of the Study:

  • To propose a novel attribute control chart for products with Weibull distributed lifetimes.
  • To implement a two-stage sampling strategy based on failures from truncated life tests.
  • To optimize control chart parameters for desired in-control average run length.

Main Methods:

  • Development of a double sampling attribute control chart tailored for Weibull distributions.
  • Determination of control chart coefficients and test duration to achieve a target average run length (ARL).
  • Calculation and tabulation of out-of-control average run lengths for various process shift parameters.

Main Results:

  • The proposed double sampling attribute control chart effectively monitors processes with Weibull distributed lifetimes.
  • Optimized parameters ensure the average run length is close to the target value when the process is in control.
  • Provided tables demonstrate the performance of the control chart under various out-of-control conditions.

Conclusions:

  • The developed control chart offers an effective tool for quality control in industries using Weibull distributed product lifetimes.
  • The two-stage sampling approach provides a practical alternative to single-stage sampling for failure analysis.
  • The study illustrates the application and benefits of the proposed chart through a case study.