CVAT is a web-based optimization application developed through U.S. Army research at Auburn University that supplements SAE Standard AS6171. Using a branch-and-bound algorithm, it determines the combination of test methods that maximizes defect detection coverage while respecting user-defined cost and time budgets. The tool draws on two data sources: Subject Matter Expert (SME) assessments, where experienced professionals rated each test method’s ability to detect each defect, and Round Robin empirical data collected from multiple well-established test labs that regularly perform AS6171 testing. In the round robin evaluation, all participating labs received comparable test samples—ranging from active complex to passive simple architectures—of both known pedigree and suspect counterfeit parts. Each lab identified the AS6171-defined counterfeit defects detected by each test method, producing measures of both detectability (whether a method could detect a given defect) and proficiency (how likely a lab would detect it). Users can select either SME data alone or a weighted blend of SME and Round Robin data when configuring a run.
Anyone using or invoking AS6171 to develop a counterfeit detection test sequence or evaluate coverage levels — including personnel at test laboratories, parts distributors, defense contractors, and government agencies responsible for EEE parts supply chain integrity.
Hover over any field label for a detailed tooltip. Look for Guide buttons throughout the interface for interactive step-by-step walkthroughs.