Optimal designing of two-level skip-lot sampling reinspection plan.

Area of Science:

• Quality Control
• Industrial Statistics
• Operations Research

Background:

• Skip-lot sampling plans reduce inspection costs for products with good quality history.
• Existing plans offer economic advantages but can be further optimized.
• Resampling techniques can enhance the efficiency of sampling plans.

Purpose of the Study:

• To develop a novel two-level skip-lot sampling plan with resampling, designated SkSP-2L.1-R.
• To provide a Markov chain formulation and derive performance measures for the new plan.
• To establish a methodology for optimizing SkSP-2L.1-R parameters to minimize average sample number.

Main Methods:

• Developed the SkSP-2L.1-R plan by integrating resampling into a two-level skip-lot framework.
• Utilized Markov chain formulation for performance analysis.
• Employed a two-point on the operating characteristic curve approach for parameter optimization.
• Constructed a table for optimal parameter determination considering various quality levels and risks.

Main Results:

• The SkSP-2L.1-R plan was formulated and its performance measures derived.
• An optimal parameter design methodology was established, minimizing the average sample number.
• Comparative analysis demonstrated that SkSP-2L.1-R outperforms conventional single sampling, SkSP-2, and SkSP-2-R plans.
• An industrial application validated the practical utility of the SkSP-2L.1-R plan.

Conclusions:

• The proposed SkSP-2L.1-R sampling plan offers significant advantages in reducing inspection costs and improving efficiency.
• The resampling incorporation and optimization methodology provide a robust framework for quality control.
• SkSP-2L.1-R is a superior alternative to existing sampling plans for industries prioritizing cost-effective quality assurance.