Systems and methods for monitoring and validating status of hardware devices in a classification yard

Abstract

Methods and systems for determining a status of hardware devices in a classification yard. In particular embodiments, a set of device event data associated with a hardware device may be analyzed to determine the performance of the hardware device during operations of each device event. A status of the hardware device may be determined from the analysis of the performance of the hardware device during operations of each device event. In embodiments, the analysis may include thresholding analysis that may be configured to determine a relationship between real-world measurements and expected (e.g., predicted or desired) results for each device event associated with the hardware device. In embodiments, the status of the hardware device may be used to ensure corrective actions on the hardware device (e.g., deploy maintenance personnel, report the status of the hardware device, send a control signal to the hardware device to deactivate, etc.).

What is claimed is: 
     
         1 . A method of determining a status of hardware devices in a classification yard, comprising:
 compiling a plurality of device events associated with a hardware device in a classification yard, wherein each device event of the plurality of device events is associated with an expected measurement and includes one or more of:
 real-world measurements of an actual measurement at the hardware device during each device event of the plurality of device events; and 
 an indication of a utilization of the hardware device during each device event of the plurality of device events to obtain the expected measurement for each device event; 
   generating a set of deviation metrics associated with the hardware device based on the plurality of device events associated with the hardware device;   applying thresholding analysis to the set of deviation metrics associated with the hardware device to determine a status of the hardware device; and   generating a corrective action signal including one or more of:
 an indication of the status of the hardware device; and 
 a corrective action to be taken on the hardware device. 
   
     
     
         2 . The method of  claim 1 , wherein generating the set of deviation metrics associated with the hardware device includes generating one or more of:
 a set of measurement differences associated with the hardware device; and   a set of utilization metrics associated with the hardware device.   
     
     
         3 . The method of  claim 2 , wherein generating the set of measurement differences associated with the hardware device includes:
 calculating, for each device event in the plurality of device events associated with a hardware device, a measurement difference by calculating a difference between the expected measurement associated with a respective device event and the actual measurement measured at the hardware device during the respective device event; and   aggregating each calculated measurement difference for each device event into the set of measurement differences associated with the hardware device.   
     
     
         4 . The method of  claim 3 , wherein applying thresholding analysis to the set of deviation metrics associated with the hardware device includes applying one or more of a set of differential rules to the set of measurement differences associated with the hardware device, wherein the set of differential rules includes one or more of:
 a first differential rule specifying that the status of the hardware device is based on whether a threshold percentage of the set of measurement differences associated with the hardware device are range defined by plus or minus a measurement threshold;   a second differential rule specifying that the status of the hardware device is based on whether a median or average of the set of measurement differences associated with the hardware device is within a range defined by plus or minus an average threshold;   a third differential rule specifying that the status of the hardware device is based on whether a spread range of measurement differences values within a middle percentage of the set of measurement differences associated with the hardware device is less than a spread threshold, wherein the middle percentage of the set of measurement differences is defined by a range of measurement differences values including a top percentile threshold of the measurement differences values in the set of measurement differences and a bottom percentile threshold of the measurement differences values in the set of measurement differences; and   a combination differential rule that includes a weighted combination of the results of one or more of the first differential rule, the second differential rule, and the third differential rule.   
     
     
         5 . The method of  claim 1 , wherein applying the thresholding analysis to the set of deviation metrics associated with the hardware device to determine the status of the hardware device includes:
 obtaining a percentage result for the hardware device, the percentage result indicating a percentage status of the hardware device.   
     
     
         6 . The method of  claim 5 , wherein determining the status of the hardware device includes flagging a status flag of the hardware device with one or more of:
 a bad status indication when the percentage status of the hardware device is at least 100%;   a warning status indication when the percentage status of the hardware device is greater than a threshold percentage and less than 100%;   a good status indication when the percentage status of the hardware device is less than the threshold percentage.   
     
     
         7 . The method of  claim 6 , wherein the warning status indication includes a section warning indication identifying a section of the hardware device determined to have failed the thresholding analysis. 
     
     
         8 . The method of  claim 1 , further comprising:
 identifying that the indication of the status of the hardware device found to be bad has previously been reset a number of times;   determining that the number of times exceeds a threshold amount; and   flagging the hardware device as a potential misidentification of a bad hardware device.   
     
     
         9 . A system for determining a status of hardware devices in a classification yard, comprising:
 at least one processor; and   a memory operably coupled to the at least one processor and storing processor-readable code that, when executed by the at least one processor, is configured to perform operations including:
 compiling a plurality of device events associated with a hardware device in a classification yard, wherein each device event of the plurality of device events is associated with an expected measurement and includes one or more of:
 real-world measurements of an actual measurement at the hardware device during each device event of the plurality of device events; and 
 an indication of a utilization of the hardware device during each device event of the plurality of device events to obtain the expected measurement for each device event; 
 
 generating a set of deviation metrics associated with the hardware device based on the plurality of device events associated with the hardware device; 
 applying thresholding analysis to the set of deviation metrics associated with the hardware device to determine a status of the hardware device; and 
 generating a corrective action signal including one or more of:
 an indication of the status of the hardware device; and 
 a corrective action to be taken on the hardware device. 
 
   
     
     
         10 . The system of  claim 9 , wherein generating the set of deviation metrics associated with the hardware device includes generating one or more of:
 a set of measurement differences associated with the hardware device; and   a set of utilization metrics associated with the hardware device.   
     
     
         11 . The system of  claim 10 , wherein generating the set of measurement differences associated with the hardware device includes:
 calculating, for each device event in the plurality of device events associated with a hardware device, a measurement difference by calculating a difference between the expected measurement associated with a respective device event and the actual measurement measured at the hardware device during the respective device event; and   aggregating each calculated measurement difference for each device event into the set of measurement differences associated with the hardware device.   
     
     
         12 . The system of  claim 11 , wherein applying thresholding analysis to the set of deviation metrics associated with the hardware device includes applying one or more of a set of differential rules to the set of measurement differences associated with the hardware device, wherein the set of differential rules includes one or more of:
 a first differential rule specifying that the status of the hardware device is based on whether a threshold percentage of the set of measurement differences associated with the hardware device are range defined by plus or minus a measurement threshold;   a second differential rule specifying that the status of the hardware device is based on whether a median or average of the set of measurement differences associated with the hardware device is within a range defined by plus or minus an average threshold;   a third differential rule specifying that the status of the hardware device is based on whether a spread range of measurement differences values within a middle percentage of the set of measurement differences associated with the hardware device is less than a spread threshold, wherein the middle percentage of the set of measurement differences is defined by a range of measurement differences values including a top percentile threshold of the measurement differences values in the set of measurement differences and a bottom percentile threshold of the measurement differences values in the set of measurement differences; and   a combination differential rule that includes a weighted combination of the results of one or more of the first differential rule, the second differential rule, and the third differential rule.   
     
     
         13 . The system of  claim 9 , wherein applying the thresholding analysis to the set of deviation metrics associated with the hardware device to determine the status of the hardware device includes:
 obtaining a percentage result for the hardware device, the percentage result indicating a percentage status of the hardware device.   
     
     
         14 . The system of  claim 13 , wherein determining the status of the hardware device includes flagging a status flag of the hardware device with one or more of:
 a bad status indication when the percentage status of the hardware device is at least 100%;   a warning status indication when the percentage status of the hardware device is greater than a threshold percentage and less than 100%;   a good status indication when the percentage status of the hardware device is less than the threshold percentage.   
     
     
         15 . The system of  claim 14 , wherein the warning status indication includes a section warning indication identifying a section of the hardware device determined to have failed the thresholding analysis. 
     
     
         16 . The system of  claim 9 , further comprising:
 identifying that the indication of the status of the hardware device found to be bad has previously been reset a number of times;   determining that the number of times exceeds a threshold amount; and   flagging the hardware device as a potential misidentification of a bad hardware device.   
     
     
         17 . A computer-based tool for determining a status of hardware devices in a classification yard, the computer-based tool including non-transitory computer readable media having stored thereon computer code which, when executed by a processor, causes a computing device to perform operations comprising:
 compiling a plurality of device events associated with a hardware device in a classification yard, wherein each device event of the plurality of device events is associated with an expected measurement and includes one or more of:
 real-world measurements of an actual measurement at the hardware device during each device event of the plurality of device events; and 
 an indication of a utilization of the hardware device during each device event of the plurality of device events to obtain the expected measurement for each device event; 
   generating a set of deviation metrics associated with the hardware device based on the plurality of device events associated with the hardware device;   applying thresholding analysis to the set of deviation metrics associated with the hardware device to determine a status of the hardware device; and   generating a corrective action signal including one or more of:
 an indication of the status of the hardware device; and 
 a corrective action to be taken on the hardware device. 
   
     
     
         18 . The computer-based tool of  claim 17 , wherein generating the set of deviation metrics associated with the hardware device includes generating one or more of:
 a set of measurement differences associated with the hardware device; and   a set of utilization metrics associated with the hardware device.   
     
     
         19 . The computer-based tool of  claim 18 , wherein generating the set of measurement differences associated with the hardware device includes:
 calculating, for each device event in the plurality of device events associated with a hardware device, a measurement difference by calculating a difference between the expected measurement associated with a respective device event and the actual measurement measured at the hardware device during the respective device event; and   aggregating each calculated measurement difference for each device event into the set of measurement differences associated with the hardware device.   
     
     
         20 . The method of  claim 19 , wherein applying thresholding analysis to the set of deviation metrics associated with the hardware device includes applying one or more of a set of differential rules to the set of measurement differences associated with the hardware device, wherein the set of differential rules includes one or more of:
 a first differential rule specifying that the status of the hardware device is based on whether a threshold percentage of the set of measurement differences associated with the hardware device are range defined by plus or minus a measurement threshold;   a second differential rule specifying that the status of the hardware device is based on whether a median or average of the set of measurement differences associated with the hardware device is within a range defined by plus or minus an average threshold;   a third differential rule specifying that the status of the hardware device is based on whether a spread range of measurement differences values within a middle percentage of the set of measurement differences associated with the hardware device is less than a spread threshold, wherein the middle percentage of the set of measurement differences is defined by a range of measurement differences values including a top percentile threshold of the measurement differences values in the set of measurement differences and a bottom percentile threshold of the measurement differences values in the set of measurement differences; and   a combination differential rule that includes a weighted combination of the results of one or more of the first differential rule, the second differential rule, and the third differential rule.