Statistical Tool
Graphical representation of the relationship between the probability of acceptance and the incoming quality level for a specific sampling plan. An operating characteristic curve shows how well a quality control process distinguishes between good and bad batches. Statistical visualization helps quality managers choose a sample size that balances producer and consumer risks.
Decisions regarding the acceptable quality limit are made by examining the shape of the line.
Probability Analysis
Steeper slopes on the graph indicate a more discriminating test that can better identify non-conforming lots. When analyzing an operating characteristic curve, the point where the probability of acceptance is 0.95 usually defines the producer risk.
Batch Qualification
Acceptance sampling plans are designed to ensure that the quality of the shipped product meets the agreed specifications. The operating characteristic curve provides a mathematical basis for deciding how many units must be tested from a large population.
Sampling Logic
Costs associated with high volume testing often limit the number of parts that can be inspected. If the operating characteristic curve is too flat, there is a high probability of accepting a lot with a high defect rate. Adjusting the sample size is the most effective way to improve the protection of the consumer.
