DocumentCode :
3711783
Title :
ATE instrument function tracking
Author :
William J Headrick;David Wong
Author_Institution :
Lockheed Martin Mission Systems and Training, 100 Global Innovation Circle, Orlando, FL 32825-5002, United States of America
fYear :
2015
Firstpage :
350
Lastpage :
353
Abstract :
In modern Automated Test Equipment (ATE) systems there is a desire to track certain aspects of system and Test Program Set (TPS) parameters. This paper discusses a set of methodologies for tracking such information. The information tracking is done as a system but on many levels. A common database is used to keep track of information for later perusal by data mining or statistical analysis. The tracking and database are designed to not impede normal operation of the station nor impact the overall speed and flow of the TPSs as they are run. By designing the interface and database in an efficient manner parametric data can be collected on multiple aspects of the running system. Important system level information such as temperature, system availability, instrument availability and any system issues are collected. Instrument level parametric information such as function calls, general parametric values and mean values can be collected and used to determine the functionality needed by the systems. TPS level data can be collected (when allowed) to determine trending data for measurements, improper limits (too close to one limit), run times or other parametric data can be saved for use by the organization to help with TPS improvement and scheduling. In general by having parametric data for the ATE, instruments, and TPSs, the entire system can be tracked and improved over time. In addition, if instruments are not required (or a limited capability) cost savings can be considered for future improvements or alternative equipment. In addition, this information can be used in conjunction with a diagnostic reasoner to help provide for more accurate fault callouts over time as more data is made available. Another goal would be to help provide a set of data to help indicate trends in parts for repair or even predict failures based on trend data.
Keywords :
"Databases","Instruments","Software","Maintenance engineering","Data mining","Power supplies","Data collection"
Publisher :
ieee
Conference_Titel :
IEEE AUTOTESTCON, 2015
Type :
conf
DOI :
10.1109/AUTEST.2015.7356515
Filename :
7356515
Link To Document :
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