| CPC B22F 10/85 (2021.01) [B22F 10/366 (2021.01); B22F 12/90 (2021.01); B33Y 50/02 (2014.12); B22F 10/28 (2021.01)] | 13 Claims |
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1. A computer implemented method comprising:
receiving first sensor data from a first sensor monitoring an additive manufacturing process, the first sensor data comprising a plurality of first sensor values;
receiving second sensor data from a second sensor monitoring the additive manufacturing process, the second sensor data comprising a plurality of second sensor values,
each first sensor value and each second sensor value being associated with a corresponding time during the additive manufacturing process at which the sensor value was generated;
analyzing the first sensor data to identify a first anomalous event that occurred in the additive manufacturing process and a corresponding first anomalous event time;
analyzing the second sensor data to identify a second anomalous event in the additive manufacturing process and a corresponding second anomalous event time;
calculating a length of time between the first anomalous event time and the second anomalous event time;
comparing the calculated length of time to an expected time frame;
identifying whether the first anomalous event is a potential cause of the second anomalous event based upon, at least in part, a result of the comparison of the calculated length of time to the expected time frame; and
generating an output based upon an identification that the first anomalous event is a potential cause of the second anomalous event,
wherein the output comprises one or more of:
i) a command signal, which causes a change in the additive manufacturing process; and
ii) a modification of build instructions for a future additive manufacturing process.
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