Subject matter expert knowledge mapping using dynamic clustering
The example embodiments are directed to a system and method that applies knowledge developed by a subject matter expert with respect to a physical asset. In one example, the method includes receiving knowledge and issue resolution information developed of subject matter experts in association with historical issues for an asset, generating a plurality of data clusters for the asset based on the knowledge, wherein each historical issue of the asset is mapped to a cluster and includes a plurality of resolutions for the issue, receiving a new issue and new issue information, and processing the new issue by extracting keywords from the new issue information and assigning the new issue to a data cluster from among the plurality of data clusters based on the extracted keywords, and outputting, to a display, a cause of the new issue and potential solutions for the new issue.
1. A computing system comprising
a memory configured to store historical work orders;
a network interface configured to receive sensor data from an asset which is captured of an issue associated with the asset; and
a processor configured to
dynamically assign different subsets of the historical work orders to different clusters corresponding to different causes, respectively, based on sensor data included in the different subsets of historical work orders,
map the issue to a cluster from among the plurality of clusters based on the sensor data, and
output, via a user interface, information for resolving the issue based on a cause corresponding to the mapped cluster.
2. The computing system of claim 1 , wherein the processor is further configured to determine previous actions taken to resolve similar issues assigned to the cluster, and output information about the previous actions via the user interface.
3. The computing system of claim 1 , wherein the cluster represents a cause of failure of the asset from among a plurality of causes of failure of the asset which are represented by the plurality of clusters, respectively.
4. The computing system of claim 1 , wherein each cluster corresponds to a single cause of failure of the asset.
5. The computing system of claim 1 , wherein the asset comprises one or more of an industrial machine and an industrial equipment.
6. The computing system of claim 1 , wherein the processor is configured to display a previous order that corresponds to an issue of a same cause, and an identifier of a service technician that resolved the issue.
7. A method comprising
storing historical work orders;
receiving sensor data from an asset which is captured of an issue associated with the asset;
dynamically assigning different subsets of the historical work orders to different clusters corresponding to different causes, respectively, based on sensor data included in the different subsets of historical work orders;
mapping the issue, via a processor, to a cluster from among the plurality of clusters based on the sensor data; and
outputting, via a user interface, information for resolving the issue based on a cause corresponding to the mapped cluster.
8. The method of claim 7 , wherein the method further comprises determining previous actions taken to resolve similar issues assigned to the cluster, and outputting information about the previous actions via the user interface.
9. The method of claim 7 , wherein the receiving further comprises receiving sensor data of the issue, and the mapping is further performed based on the received sensor data.
10. The method of claim 7 , wherein each cluster corresponds to a single cause of failure of the asset.
11. The method of claim 7 , wherein the asset comprises one or more of an industrial machine and an industrial equipment.
12. The method of claim 7 , wherein the outputting comprises displaying a previous order that corresponds to an issue of a same cause, and an identifier of a service technician that resolved the issue.
13. A non-transitory computer-readable medium comprising instructions which when executed by a processor cause a computer to perform a method comprising:
storing historical work orders;
receiving sensor data from an asset which is captured of an issue associated with the asset;
dynamically assigning different subsets of the historical work orders to different clusters corresponding to different causes, respectively, based on sensor data included in the different subsets of historical work orders;
mapping the issue, via a processor, to a cluster from among the plurality of clusters based on the sensor data; and
outputting, via a user interface, information for resolving the issue based on a cause corresponding to the mapped cluster.
14. The non-transitory computer-readable medium of claim 13 , wherein the method further comprises determining previous actions taken to resolve similar issues assigned to the cluster, and outputting information about the previous actions via the user interface.
15. The non-transitory computer-readable medium of claim 13 , wherein the cluster represents a cause of failure of the asset from among a plurality of causes of failure of the asset which are represented by the plurality of clusters, respectively.
16. The non-transitory computer-readable medium of claim 13 , wherein each cluster corresponds to a single cause of failure of the asset.
17. The non-transitory computer-readable medium of claim 13 , wherein the outputting comprises displaying a previous order that corresponds to an issue of a same cause, and an identifier of a service technician that resolved the issue.