Communication Dans Un Congrès Année : 2023

Development of Predictive Maintenance Models for a Packaging Robot Based on Machine Learning

Résumé

This study presents the development of a predictive model for the health monitoring of power transmitters in a packaging robot usingmachine learning techniques. The model is based on a Discrete Bayesian Filter (DBF) and is compared to a model based on a Naïve Bayes Filter (NBF). Data preprocessing techniques are applied to select suitable descriptors for the predictive model. The results showthat theDBF model outperforms theNBFmodel in terms of predictive power. The model can be used to estimate the current state of the power transmitter and predict its degradation over time. This can lead to improved maintenance planning and cost savings in the context of Industry 4.0.

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Dates et versions

hal-04735771 , version 1 (25-03-2026)

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Ayoub Chakroun, Yasmina Hani, Sadok Turki, Nidhal Rezg, Abderrahmane Elmhamedi, et al.. Development of Predictive Maintenance Models for a Packaging Robot Based on Machine Learning. IFIP International Conference on Advances in Production Management Systems (APMS 2023), Sep 2023, Trondheim, Norway. pp.674-688, ⟨10.1007/978-3-031-43666-6_46⟩. ⟨hal-04735771⟩
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