Stratified Sampling and Odd-Even Sampling for Content Uniformity (CU)

Introduction

Stratified sampling and odd-even sampling are systematic approaches to evaluate batch variability during production . These methods ensure robust CU testing, addressing potential inconsistencies across processes .

Stratified Sampling

Stratified sampling divides a batch into subgroups (strata) based on critical factors like production stages, equipment zones, or storage layers. This ensures variability across the entire batch is represented.

Key Variables

1. Time Intervals:

• Samples collected at the start, middle, and end of production.

2. Equipment Zones:

• Samples from different compression stations or filling heads.

3. Batch Segmentation:

• Layers or containers during storage or packaging.

Steps for Stratified Sampling

1. Define Strata:

• Segment the batch into subgroups based on critical parameters.

2. Random Sampling:

• Select representative samples from each stratum.

3. Sample Size:

• Collect a sufficient number of samples (e.g., 10 units or more).

Benefits

• Represents variability across the batch.
• Identifies specific sources of inconsistency.
• Provides data for process optimization.

Odd-Even Sampling

• Odd-even sampling alternates sample collection across odd- and even-numbered locations in the process or storage.

Concept of 40 Locations

• Odd Locations: Positions 1, 3, 5, ..., 39.
• Even Locations: Positions 2, 4, 6, ..., 40.

Implementation Steps

1. Define Sampling Points:

• Assign odd and even numbers to 40 locations across production or storage.

2. Alternate Sampling:

• Collect samples from odd positions first, followed by even positions.

3. Applications:

• Compression stations, filling heads, or storage layers.

Benefits

• Systematic coverage of variability.
• Easy implementation with predefined locations.
• Minimizes sampling bias.
• Combining Stratified and Odd-Even Sampling
• Integrating stratified and odd-even sampling provides comprehensive batch evaluation.

Implementation

1. Batch Segmentation:

• Divide the batch into strata (e.g., early, middle, late stages).

2. Odd-Even Sampling:

• Within each stratum, alternate odd and even samples.

3. Testing:

• Analyze all samples for CU to identify process inconsistencies.

Example: Tablet Compression

• Early Stage: Odd samples from stations 1, 3, 5, ..., 19.
• Middle Stage: Even samples from stations 2, 4, 6, ..., 20.
• Late Stage: Repeat the odd-even sampling pattern.

Applications and Benefits

Applications

1. Process Validation:

• Confirms consistency during manufacturing.

2. Process Improvement:

• Enhances reliability of CU results.

Benefits

• Comprehensive representation of batch variability.
• Improves reliability of CU testing.

Conclusion

Stratified sampling and odd-even sampling, when combined, create a robust framework for CU testing. These systematic methods enhance batch evaluation, ensuring reliable and consistent results while supporting process optimization.

Read also:

• Blend Uniformity Analysis
  
• Content Uniformity Analysis
  
• Statistical Analysis of Content Uniformity
  

Resource Person: Moinuddin syed. Ph.D, PMP