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Current avionics maintenance and repair is a complex process that presents many opportunities for improved diagnostic methods and better capture and retention of on-board and at-wing data to be incorporated into the maintenance and logistics chain. High occurrences of built-in-test (BIT) false alarm, cannot duplicate (CND), and no fault found (NFF) statistics indicate the need for improvements in the maintenance process. Capture and preservation of fault and maintenance data with situational context can support off-board repair processes and provide opportunities for data mining to identify rogue units and emerging or otherwise undetected patterns. Previous papers by the authors have described open-systems architecture and innovative reasoning processes to capitalize evidence sources and decrease diagnostic ambiguity while preserving information continuity through the logistics chain. In this paper, the authors describe an at-wing modular application for portable maintenance aids, building upon open architecture designs and utilizing reusable, modular components to enhance diagnosis and reduce ambiguity. ReasonPro - at Wing™ presents a direct opportunity for increased diagnostic accuracy and ambiguity reduction through a better understanding of system dependencies and interactions. The technology is being embedded into a personal data assistant (PDA) to facilitate multiple element in the maintenance process. ReasonPro - at Wing™ implements onboard information sources and automated reasoning techniques that extend BITs with environmental data and data maturation processing through the support of automated data warehousing and mining.