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Establishing tolerance levels for customer complaints.

Leslie Rodriguez1, Robert T Magari

  • 1Beckman Coulter, Inc., Miami, Florida.

Quality Assurance (San Diego, Calif.)
|January 6, 2006
PubMed
Summary

This study introduces a method to set maximum customer complaint limits using Poisson process analysis. It identifies stable periods to detect significant changes in product performance.

Area of Science:

  • Statistical modeling
  • Quality control
  • Reliability engineering

Background:

  • Customer complaints data often follow a Poisson process, which can be stationary or indicate performance changes.
  • Monitoring complaint counts is crucial for assessing product performance over time.

Purpose of the Study:

  • To develop an approach for establishing maximum monthly tolerance levels for customer complaints.
  • To differentiate stable complaint periods from those indicating potential product issues.

Main Methods:

  • Utilizing Poisson process modeling for complaint data analysis.
  • Applying change-point analysis to identify shifts in complaint rates.
  • Defining tolerance levels based on stationary periods of the Poisson process.

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Main Results:

  • The proposed method effectively partitions complaint data into stable and problematic periods.
  • Change-point analysis successfully detects significant alterations in complaint counts.
  • Established tolerance levels provide a benchmark for acceptable complaint volumes.

Conclusions:

  • The described approach offers a robust framework for setting customer complaint tolerance levels.
  • This method aids in proactive product performance monitoring and issue detection.
  • Statistical analysis of complaint data enhances quality management strategies.