Anomaly detection from aggregate statistics using neural networks

A system comprising:

• a memory;
• and
• a processing device operatively coupled to the memory, the processing device to:
• obtain a reduced representation of a plurality of sensor statistics representative of data collected by a plurality of sensors associated with a device manufacturing system performing a manufacturing operation;
• generate, using a plurality of outlier detection models, a plurality of outlier scores, wherein each of the plurality of outlier scores is generated based on the reduced representation of the plurality of sensor statistics using a respective one of the plurality of outlier detection models;
• and
• process the plurality of outlier scores using a detector neural network to generate an anomaly score indicative of a likelihood of an anomaly associated with the manufacturing operation.

A non-transitory computer readable storage medium comprising instructions that, when executed by at least one processing device, cause the at least one processing device to:

• obtain a reduced representation of a plurality of sensor statistics representative of data collected by a plurality of sensors associated with a device manufacturing system performing a manufacturing operation;
• generate, using a plurality of outlier detection models, a plurality of outlier scores, wherein each of the plurality of outlier scores is generated based on the reduced representation of the plurality of sensor statistics using a respective one of the plurality of outlier detection models;
• and
• process the plurality of outlier scores using a detector neural network to generate an anomaly score indicative of a likelihood of an anomaly associated with the manufacturing operation.