Abstract: A method and system for managing communication of electronic data between a diagnostic service center and a plurality of mobile assets (10) generally remote relative to each other is provided. The electronic data comprises at least respective mobile asset data indicative of respective performance of the plurality of mobile assets. The mobile asset data used for detecting the presence of potential malfunctions which, if left uncorrected, would likely result in respective mission failures of the assets. The method allows for storing in a database (104) a list of respective cases to be processed. The method further allows for assigning to each case a respective download priority. A determining action allows for determining each case to be populated next with new mobile asset data based upon the assigned download priority.

Abstract: An analysis scheduler for scheduling the automatic processing of performance data through a plurality of analysis tools is disclosed. Performance data provided to some of the tools by the analysis scheduler may be specified to be within a predetermined (but variable) look-back period. The analysis tools identify faults and anomalous conditions and also create repair recommendations, and automatically create problem cases when conditions warrant, or update existing problem cases with additional data, all under control of the analysis scheduler. The problem cases are reviewed by a human user and then forwarded to the railroad for implementation.

Abstract: An analysis scheduler for scheduling the automatic processing of performance data through a plurality of analysis tools is disclosed. Performance data provided to some of the tools by the analysis scheduler may be specified to be within a predetermined (but variable) look-back period. The analysis tools identify faults and anomalous conditions and also create repair recommendations, and automatically create problem cases when conditions warrant, or update existing problem cases with additional data, all under control of the analysis scheduler. The problem cases are reviewed by a human user and then forwarded to the railroad for implementation.

Abstract: A method for analyzing fault data specific to a machine comprising a plurality of subsystems, said method comprising collecting fault data from a machine experiencing a malfunction, filtering said fault data with a noise-reduction filter to produce noise-reduced fault data, establishing fault rules specific to a subsystem of said machine, applying fault rules specific to said subsystem to noise-reduced fault data, and predicting at least one repair specific to said subsystem based on said fault rules and said noise-reduced fault data.

Abstract: An analysis scheduler for scheduling the automatic processing of performance data through a plurality of analysis tools is disclosed. Performance data provided to some of the tools by the analysis scheduler may be specified to be within a predetermined (but variable) look-back period. The analysis tools identify faults and anomalous conditions and also create repair recommendations, and automatically create problem cases when conditions warrant, or update existing problem cases with additional data, all under control of the analysis scheduler. The problem cases are reviewed by a human user and then forwarded to the railroad for implementation.

Abstract: A method and system for managing communication of electronic data between a diagnostic service center and a plurality of machines generally remote relative to each other is provided. The electronic data is made up of respective machine data from selected machines. The machine data is used for detecting the presence of respective malfunctions which, if left uncorrected, would likely result in respective mission failures of the selected machines. The method allows for storing in a database a list of respective cases to be processed. The method further allows for assigning to each case a respective download priority. A determining step allows for determining each case to be populated next with new machine data based at least upon the assigned download priority. Respective executing steps allow for executing a download of the new machine data, and for executing predetermined analysis on the downloaded data for detecting the presence of respective malfunctions in the selected machines.