Providing corrective solution recommendations for an industrial machine failure
A system and method for providing a corrective solution recommendation for an industrial machine failure, the method including: monitoring a plurality of segments of at least an industrial machine behavioral model to identify a first segment having at least a first set of characteristics associated with a previous machine failure; determining a corrective solution recommendation that solved the previous machine failure; identifying at least a second set of characteristics associated with a second segment; and generating a notification comprising the corrective solution recommendation when the second set of characteristics is determined to be similar to the first set of characteristics above a predetermined threshold.
1. A method for providing a corrective solution recommendation for an industrial machine failure, comprising:
monitoring a plurality of segments of at least a first industrial machine behavioral model to identify a first segment having at least a first set of characteristics associated with a previous industrial machine failure;
determining a corrective solution recommendation that solved the previous industrial machine failure;
identifying at least a second set of characteristics associated with a second segment, wherein the second set of characteristics is of a second industrial machine behavioral model associated with a machine;
generating a notification comprising the corrective solution recommendation when the second set of characteristics is determined to be similar to the first set of characteristics above a predetermined threshold; and
sending, to a client device associated with the machine to which the second industrial machine behavioral model is associated, the generated notification.
2. The method of claim 1 , wherein the first set of characteristics and the second set of characteristics are indicative of at least one of: a feature, an anomaly, a statistical metric, a correlation between sensory inputs, a machine behavior patterns, and a root cause.
3. The method of claim 1 , wherein the previous industrial machine failure is a first industrial machine failure, wherein the first set of characteristics allows for the detection of a second industrial machine failure by detecting abnormal behaviors of at least a component of the machine.
4. The method of claim 1 , wherein the notification includes at least one of: time to failure, industrial machine failure root cause, evolution of degradation events, information related to previous industrial machine failure.
5. The method of claim 1 , further comprising:
determining a suitability score for the corrective solution recommendation, wherein the suitability score indicates a probability that the corrective solution recommendation will solve a forthcoming or existing second industrial machine failure.
6. The method of claim 1 , wherein the second set of characteristics is determined to be similar to the first set of characteristics above a predetermined threshold based on a similarity function that provides a quantitative value representing the similarity between the two sets of characteristics.
7. The method of claim 1 , wherein the at least a first industrial machine behavioral model is represented by a plurality of meta-models, where each of the plurality of meta-models is associated with a component of an industrial machine.
8. The method of claim 1 , wherein the second set of characteristics is determined to be similar to the first set of characteristics using machine learning models.
9. A non-transitory computer readable medium having stored thereon instructions for causing a processing circuitry to perform a process, the process comprising:
monitoring a plurality of segments of at least a first industrial machine behavioral model to identify a first segment having at least a first set of characteristics associated with a previous industrial machine failure;
determining a corrective solution recommendation that solved the previous industrial machine failure;
identifying at least a second set of characteristics associated with a second segment, wherein the second set of characteristics is of a second industrial machine behavioral model associated with a machine;
generating a notification comprising the corrective solution recommendation when the second set of characteristics is determined to be similar to the first set of characteristics above a predetermined threshold; and
sending, to a client device associated with the machine to which the second industrial machine behavioral model is associated, the generated notification.
10. A system for providing a corrective solution recommendation for an industrial machine failure, comprising:
a processing circuitry; and
a memory, the memory containing instructions that, when executed by the processing circuitry, configure the system to:
monitor a plurality of segments of at least a first industrial machine behavioral model to identify a first segment having at least a first set of characteristics associated with a previous industrial machine failure;
determine a corrective solution recommendation that solved the previous industrial machine failure;
identify at least a second set of characteristics associated with a second segment, wherein the second set of characteristics is of a second industrial machine behavioral model associated with a machine;
generate a notification comprising the corrective solution recommendation when the second set of characteristics is determined to be similar to the first set of characteristics above a predetermined threshold; and
send, to a client device associated with the machine to which the second industrial machine behavioral model is associated, the generated notification.
11. The system of claim 10 , wherein the first set of characteristics and the second set of characteristics are indicative of at least one of: a feature, an anomaly, a statistical metric, a correlation between sensory inputs, a machine behavior patterns, and a root cause.
12. The system of claim 10 , wherein the previous industrial machine failure is a first industrial machine failure, wherein the first set of characteristics allows for the detection of a second industrial machine failure by detecting abnormal behaviors of at least a component of the machine.
13. The system of claim 10 , wherein the notification includes at least one of: time to failure, industrial machine failure root cause, evolution of degradation events, information related to previous industrial machine failure.
14. The system of claim 10 , wherein the system is further configured to:
determine a suitability score for the corrective solution recommendation, wherein the suitability score indicates a probability that the corrective solution recommendation will solve a forthcoming or existing second industrial machine failure.
15. The system of claim 10 , wherein the second set of characteristics is determined to be similar to the first set of characteristics above a predetermined threshold based on a similarity function that provides a quantitative value representing the similarity between the two sets of characteristics.
16. The system of claim 10 , wherein the at least a first industrial machine behavioral model is represented by a plurality of meta-models, where each of the plurality of meta-models is associated with a component of an industrial machine.
17. The system of claim 10 , wherein the second set of characteristics is determined to be similar to the first set of characteristics using machine learning models.