This case study focuses on analyzing the quality control process at DataStor, a company that manufactures hard drives. The goal is to identify potential quality issues in the production process using statistical methods. The company uses a PDQ test score to assess the quality of their drives, rejecting any drive with a score below 6.2. The analysis explores the distribution of production data, identifies anomalies, and investigates the root cause of higher-than-expected shipment rejections.
DataStor produces hard drives and uses a PDQ test score to evaluate the quality of each drive. Drives with a PDQ score below 6.2 are rejected. The analysis begins by examining the distribution of:
- Hours worked by production employees
- Number of drives produced
- Average PDQ scores
The initial analysis suggests that the data distribution appears normal, and no major issues are evident. However, further investigation reveals a discrepancy between the expected and actual rejection rates, indicating potential quality control problems.
- PDQ Score Threshold: 6.2 (drives below this score are rejected)
- **Expected Defect