Proposed software standards for control and sequencing of automatic test equipment

Whether using human or machine intelligence, the best decisions are made when using all available information from all relevant sources. This is in direct contrast to typical card-level automatic test equipment (ATE) programs which usually stop functional testing when a failure is encountered. The philosophy has been explained that there is no point in further testing until the problem has been corrected. This philosophy of refusing to supply further information often causes the software to fail in its primary task of diagnosing the true problem, requiring the technician to resort to other means, and limits the utility of intelligent use of the software, from either a human or artificially intelligent point of view. The design model of traditional software is usually based on a single failing component. Our experience is that as much as 40% of circuit cards contain multiple malfunctions and partial failures which do not conform to this model. While some of the proposed controls exist for some ATE, the implementations can be deficient by failure to display or to record data critical to the task of diagnosis. What is proposed is a set of standards for ATE software control and sequencing which will improve diagnostic accuracy and allow for application of true Artificial Intelligence