AI-based automatic test equipment with component interchangeability

This paper proposes a method for structuring an intelligent test station to increase diagnostic efficiency, maximize code reuse, and offer portability between different test instruments. In automatic test equipment (ATE) commonly found in government maintenance organizations, traditional test program sets include vendor-specific test code that is expensive to rehost when instruments become obsolete. This paper proposes a method of Test Program Sets (TPS) development using commercially available technologies that separate the TPS into diagnostics, test and driver components. The test diagnostics logic can be based on any diagnostics reasoner including expert systems, neural networks, case-based reasoning, and model-based dependency models. If communicates with LabVIEW or a similar type of test environment to conduct automated tests using VXI instrument drivers provided by manufacturers. The VXI drivers should be encapsulated to facilitate easier interchangeability. This paper will demonstrate that there are commercial off-the-shelf (COTS) tools in the market that can accomplish the aforementioned tasks. They are not magic cures and do not replace human intelligence; however, they are capable of aiding the engineer with knowledge capture and providing integration without elaborate software development