Abstract
This paper describes a failure-diagnosis expert system for printed circuit boards which exploits functional test data. The data is output from automatic test equipment which is used to test every board subsequent to manufacture.
The use of a conventional machine-learning technique produced only limited success due to the very large search space of failure reports. This also ruled out the use of a conventional knowledge-based approach. In addition, there was a requirement to track changes in printed circuit board design and manufacture which also ruled out a conventional knowledge-based approach.
The investigations led to the development of a system which tracks changes by learning in a more restricted search space derived from the original space of reports. The system performs a diagnosis by matching a failure report with information about previously seen reports. The matching rules used are heuristic. The system uses basic circuit connectivity information in conjunction with the matching procedure to improve diagnostic performance, especially in cases where matching fails to identify a unique component.
The use of a conventional machine-learning technique produced only limited success due to the very large search space of failure reports. This also ruled out the use of a conventional knowledge-based approach. In addition, there was a requirement to track changes in printed circuit board design and manufacture which also ruled out a conventional knowledge-based approach.
The investigations led to the development of a system which tracks changes by learning in a more restricted search space derived from the original space of reports. The system performs a diagnosis by matching a failure report with information about previously seen reports. The matching rules used are heuristic. The system uses basic circuit connectivity information in conjunction with the matching procedure to improve diagnostic performance, especially in cases where matching fails to identify a unique component.
Original language | English |
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Pages (from-to) | 447-456 |
Number of pages | 10 |
Journal | Engineering Applications of Artificial Intelligence |
Volume | 6 |
Issue number | 5 |
DOIs | |
Publication status | Published - Oct 1993 |
Keywords / Materials (for Non-textual outputs)
- DIAGNOSIS
- FAULT DICTIONARY
- PCB TEST