Acceptance sampling based on truncated life tests in the Birnbaum Saunders model

Area of Science:

• Reliability Engineering
• Statistical Quality Control
• Probability Distributions

Background:

• Acceptance sampling plans are crucial for quality control in manufacturing.
• Traditional methods often assume complete life testing, which can be time-consuming and costly.
• The Birnbaum-Saunders distribution is suitable for modeling fatigue and failure times.

Purpose of the Study:

• To develop and present acceptance sampling plans based on truncated life tests.
• To determine the minimum sample size required for a specified average product life.
• To evaluate the operating characteristic values and producer's risk associated with these plans.

Main Methods:

• Utilizing the Birnbaum-Saunders distribution to model unit lifetimes.
• Implementing a truncated life testing procedure.
• Calculating minimum sample sizes and operating characteristic curves.
• Presenting producer's risk associated with the developed plans.

Main Results:

• The study provides a method for determining minimum sample sizes for acceptance sampling under truncated tests.
• Operating characteristic values and producer's risk are quantified for the proposed plans.
• An illustrative example demonstrates the practical application of the developed methodology.

Conclusions:

• The developed acceptance sampling plans offer an efficient approach for quality control when life testing is truncated.
• The methodology allows for the determination of adequate sample sizes to meet desired reliability standards.
• These plans are valuable for industries seeking to optimize testing procedures while managing risks.