Use Acceptance Sampling to Improve Manufacturing Process and Product Quality

January 4, 2018
4 min read

How do manufacturing organizations confirm that supplier products comply with critical quality standards? For the most part, manufacturers rely on inspectors to check incoming materials. Those results are compared with the company’s own quality standards and supplier-generated documents such as Certificates of Analysis (COAs). Based on results, inspectors either accept or reject a shipment.
However, most of us can recite the 3rd of Dr. W. Edwards
Deming’s 14 management principles, which exhorts organizations to “cease dependence on inspection to achieve quality.” Organizations that take Deming’s guidance to heart may wonder if it’s better to skip inspection at intake.
Personally, I believe it’s better to expend resources on inspection of critical received goods. By not inspecting, companies are basically crossing their corporate fingers and hoping that products meet requirements.

Apply Statistical Sampling to Minimize Risk and Maximize Quality

But in many cases, checking 100% of incoming materials isn’t realistic. Lot Acceptance Sampling (or just Acceptance Sampling) applies statistical sampling to enable inspectors to decide whether to accept or reject materials.
Organizations typically use Acceptance Sampling procedures as defined by the MIL-STD-1916 (DoD Preferred Methods for Acceptance of Product) or ANSI/ASQ Z1.4 or Z1.9. Regardless of the method, Acceptance Sampling helps minimize inspection costs, manage risk, and prevent off-quality product from entering the production process.

Turn Acceptance Sampling into a Quality Improvement Tool

Acceptance Sampling occupies the middle ground between no inspection and 100% inspection. The result is that these techniques have been derided as just another set of inspection tools. Plus, most quality professionals consider Acceptance Sampling unworthy of being called a quality-improvement tool because the end result of all those statistical gyrations is a meek, stand-alone “Accept” or “Reject” conclusion.
Long ago, I agreed with these assertions, but no more. Instead, I believe Acceptance Sampling can be used as a highly effective means of improving quality.
Here’s how: Imagine inspectors use Acceptance Sampling to check incoming product. But assume inspectors save the data that has been used for making the Accept/Reject conclusion.
For example, when performing attribute checks using ANSI/ASQ Z1.4, the actual defect codes and reasons for failure might be noted along with the supplier name, product code, lot number, and other important traceability fields. Likewise, when using ANSI/ASQ Z1.9 for variables data, the actual measurements (and traceability elements associated with the shipment) are saved to a database. By capturing this valuable data, inspectors would not just make an Accept/Reject decision, but create an Acceptance Sampling plan that would allow data that lead up to the conclusion to be saved to a database.

Learn more about the advantages of centralizing statistical and quality management data.

Benefits of Collecting Quality Inspection Data

Imagine what you can do when you have those data available for reference all in one place. Now you have a database in which historical data are available by supplier, product, and other traceability elements. The Acceptance Sampling plans themselves become the source for these quality data. Now—

  • Control charts, histograms, Pareto charts, and other statistical analyses can be used to analyze receiving-inspection data.
  • Defect levels between suppliers can be compared.
  • Significant time-based changes in PPM defect rates can be identified.
  • The control (or lack of control) of a supplier’s processes can be confirmed.
  • The data can be used to collaboratively work with suppliers to help them improve the quality of their supplied products and their manufacturing processes.

In essence, saving the measurement data along with the Accept/Reject conclusion allows Acceptance Sampling procedures to be a tremendous complement to typical quality improvement efforts.
Previously unknown vendor-specific quality levels can be accurately quantified and that information can be used for significantly improving vendor quality and reducing quality costs across the supply chain.
And it can all be done simply with little or no cost to those who already use ANSI/ASQ procedures. All it takes is a change in mindset. We must think differently about Acceptance Sampling.