Explainable Predictive Maintenance is Not Enough: Quantifying Trust in Remaining Useful Life Estimation
Ripan Kumar Kundu,
Khaza Anuarul Hoque
Abstract:Machine learning (ML)/deep learning (DL) has shown tremendous success in data-driven predictive maintenance (PdM). However, operators and technicians often require insights to understand what is happening, why it is happening, and how to react, which these black-box models cannot provide. This is a major obstacle in adopting PdM as it cannot support experts in making maintenance decisions based on the problems it detects. Motivated by this, several researchers have recently utilized various post-hoc explanatio… Show more
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