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Automated algorithm selection for Predictive Maintenance: Advances and challenges
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AI
DOI：10.1016/j.jmsy.2025.06.023.png)
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Abstract
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• Systematic review of Meta-Learning methods for industrial PdM tasks. • Formalizes CASH problem for algorithm and hyperparameter selection in PdM. • Identifies model development bottlenecks and key PdM implementation challenges. • Reveals gaps in unsupervised and adaptive methods for dynamic conditions. • Proposes research roadmap for robust industrial deployment of Meta-Learning.
Keywords:
Meta-Learning
Predictive Maintenance
Hyperparameter Optimization
Industrial Deployment
Adaptive Methods
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14.2
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2.7K
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1.6W
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Cited Papers
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