Abstract
Goal for Predictive Maintenance for 3D printing system is to contribute to reduce unplanned
downtime and possible failures, helping the customers save money while building trust. Not all
failure modes can be captured in internal testing owing to variety of usage environments and
usage conditions. For instance, the threshold for specific sensor monitoring might not be
applicable with specific usage conditions for customer(s). In this paper, we describe a process
based on machine learning to predict the lifespan of servo motors (Z-Motor) in terms of number
of layers remaining and generate alarms.
Creative Commons License
This work is licensed under a Creative Commons Attribution-Share Alike 4.0 License.
Recommended Citation
INC, HP, "SERVO MOTOR SHUTDOWN PREDICTION FOR 3DMJF", Technical Disclosure Commons, (September 23, 2019)
https://www.tdcommons.org/dpubs_series/2516