Methods and apparatus for monitoring robot health in manufacturing environments
Methods, apparatus, systems, and articles of manufacture for monitoring robot health in manufacturing environments are described herein. An example system, to monitor health of a robot in a semiconductor wafer manufacturing facility, includes a sensor coupled to the robot. The sensor is to obtain a vibration signal representative of vibration of the robot. The example system also includes a health monitor extract a feature from the vibration signal, compare the feature to a threshold, and, in response to determining the feature satisfies the threshold, transmit an alert.
1. A system to monitor health of a robot in a semiconductor wafer manufacturing facility, the system comprising:
a sensor coupled to the robot, the sensor to obtain a vibration signal representative of vibration of the robot;
a health monitor to:
obtain a user selection of a feature to be extracted from the vibration signal;
extract the feature from the vibration signal;
compare the feature to a threshold; and
in response to determining the feature satisfies the threshold, transmit an alert; and
a fault classifier to:
determine, using a multi-variable analysis based on the feature, whether the feature is a false alarm; and
if the feature is a false alarm, transmit a message to a technician device indicating the alert was a false alarm.
2. The system of claim 1 , wherein the feature is a median frequency, spectral energy, root mean square, or variance of the vibration signal.
3. The system of claim 1 , wherein the robot is located in a clean room of the semiconductor wafer manufacturing facility.
4. The system of claim 3 , wherein the health monitor is located in the clean room.
5. The system of claim 4 , wherein the technician device is located outside of the clean room.
6. The system of claim 1 , wherein the health monitor is to compare the feature to the threshold by determining whether the feature is within a multiple of a standard deviation of a mathematical combination of historical values of the feature.
7. The system of claim 1 , wherein the sensor is a triaxial microelectromechanical systems (MEMS) accelerometer.
8. The system of claim 7 , wherein the sensor is to obtain vibration data associated with movement in each of X, Y, and Z directions.
9. The system of claim 1 , wherein the health monitor is to transmit the feature to the fault classifier.
10. The system of claim 1 , wherein the fault classifier is to determine a type of fault associated with the feature.
11. The system of claim 1 , wherein the fault classifier is implemented on a cloud-based computing device.
12. A method to monitor health of a robot in a semiconductor wafer manufacturing facility, the method comprising:
obtaining a user selection of a feature to be extracted from a vibration signal associated with the robot;
extracting, by executing an instruction with at least one processor, the feature of the vibration signal obtained by a sensor coupled to the robot;
comparing the feature to a threshold; and
generating, by executing an instruction with the least one processor, an alert when the feature satisfies the threshold.
13. The method of claim 12 , wherein the generating of the alert includes transmitting the alert over a network to an electronic device to be presented to a user.
14. The method of claim 12 , wherein the comparing of the feature to the threshold includes comparing the feature to a multiple of a standard deviation of a mathematical combination of a plurality of historical values of the feature.
15. The method of claim 12 , further including communicating the feature to a fault classifier.
16. A non-transitory machine readable storage medium comprising instructions that, when executed, cause at least one machine to at least:
obtain a user selection of a feature to be extracted from a vibration signal associated with a robot in a semiconductor wafer manufacturing facility;
extract the feature of the vibration signal obtained by a sensor coupled to the robot;
compare the feature to a threshold corresponding to a multiple of a standard deviation of a mathematical combination of a plurality of historical values of the feature; and
generate an alert when the feature satisfies the threshold.
17. The non-transitory machine readable storage medium of claim 16 , wherein the instructions, when executed, cause the at least one machine to transmit the alert over a network to an electronic device to be presented to a user.
18. The non-transitory machine readable storage medium of claim 16 , wherein the instructions, when executed, cause the at least one machine to transmit the feature to a fault classifier.
19. The system of claim 5 , wherein the fault classifier is remote from a manufacturing facility containing the clean room and the technician device.
20. The system of claim 5 , wherein the fault classifier is outside of a firewall of a manufacturing facility containing the clean room and the technician device.