Neuroscience-Inspired Algorithms for the Predictive Maintenance of Manufacturing Systems

@article{VMalawade2021NeuroscienceInspiredAF,
  title={Neuroscience-Inspired Algorithms for the Predictive Maintenance of Manufacturing Systems},
  author={Arnav V. Malawade and Nathan D. Costa and Deepan Muthirayan and Pramod P. Khargonekar and Mohammad A. Al Faruque},
  journal={IEEE Transactions on Industrial Informatics},
  year={2021},
  volume={17},
  pages={7980-7990}
}
If machine failures can be detected preemptively, then maintenance and repairs can be performed more efficiently, reducing production costs. Many machine learning techniques for performing early failure detection using vibration data have been proposed; however, these methods are often power and data-hungry, susceptible to noise, and require large amounts of data preprocessing. Also, training is usually only performed once before inference, so they do not learn and adapt as the machine ages. In… 

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