Zero Acceptance Sampling to Reduce Inspection Costs

Inspection is a necessary but non-value-adding activity whose purpose is to protect the customer from poor quality. We should therefore do as little as possible, upon condition that our inspection plan meet the customer’s requirement. Inspection plans with acceptance numbers of zero (c=0) minimize the sample size, albeit at the cost of a higher producer’s risk of rejecting lots at the specified acceptable quality level (AQL). This presentation will show how to define c=0 plans whose customer protection is equivalent to that of the corresponding ANSI/ASQ Z1.4 (formerly MIL-STD 105) plan.

Areas Covered in the Session :

1. How to use ANSI/ASQ Z1.4, including definition of the sampling plan based on the inspection level, acceptable quality level (AQL), and lot size.
   • How to use the standard’s switching rules to move between normal, tightened, and reduced inspection where appropriate
2. Understand the benefits of double and multiple inspection plans in terms of their ability to accept good lots very quickly, and reject bad ones quickly, to reduce the average sample size.
3. Convert any ANSI/ASQ Z1.4 plan into a zero acceptance number (c=0) plan that provides equivalent or better protection against poor quality at the rejectable quality level (RQL). (ANSI/ASQ Z1.4 plans do not have formal RQLs, but we pretend that the nonconforming fraction for which the consumer’s risk of acceptance is 10% is the RQL). A c=0 plan has a smaller sample size than any single, double, multiple, or sequential sampling plan.
   • Nothing is free in industrial statistics, though, and the cost of less inspection is a higher producer’s risk of rejecting lots at the AQL. A c=0 plan should therefore be used only when quality is far better than the specified AQL.
   • Generate an operating characteristic (OC) curve that compares the protection from the c=0 plan to that of the original ANSI/ASQ Z1.4 plan to gain the customer’s agreement for the use of a c=0 plan.

Attendees will also receive an Excel spreadsheet that shows the operating characteristic (OC) curve for a c=0 plan and compares it to the original ANSI/ASQ Z1.4 plan. Attendees can replace the example’s specification with their own.

Who Should Attend:

• Quality Managers
• Quality Inspectors
• Quality Technicians
• Quality Engineers
• Engineering Departments

Course Director: William Levinson 

William (Bill) A. Levinson, P.E., is the principal of Levinson Productivity Systems, P.C. He is an ASQ Fellow, Certified Quality Engineer, Quality Auditor, Quality Manager, Reliability Engineer, and Six Sigma Black Belt. He holds degrees in chemistry and chemical engineering from Pennsylvania State and Cornell Universities, and night school degrees in business administration and applied statistics from Union College, and he has given presentations at the ASQ World Conference, TOC World 2004, and other national conferences on productivity and quality. Mr. Levinson is also the author of several books on quality, productivity, and management. Henry Ford’s Lean Vision is a comprehensive overview of the lean manufacturing and organizational management methods that Ford employed to achieve unprecedented bottom line results, and Beyond the Theory of Constraints describes how Ford’s elimination of variation from material transfer and processing times allowed him to come close to running a balanced factory at full capacity. Statistical Process Control for Real-World Applications shows what to do when the process doesn’t conform to the traditional bell curve assumption.