Technical Programme

Session: T33Predictive Maintenance


Interpretable Survival Models for Predictive Maintenance
Paul Castle, Janet Ham, Melinda Hodkiewicz and Adriano Polpo


Low-Cost Solutions for Maintenance with a Raspberry Pi
Martin Larrañaga, Riku Salokangas, Olli Saarela and Petri Kaarmila


Machine Learning-Enabled Modeling Approach for Predictive Mainte-nance Decision-Making Support
Chunsheng Yang, Yubin Yang, Xiaohui Yang and Qiangqiang Cheng


The SUPREEMO Experiment for Smart Monitoring for Energy Efficiency and Predictive Maintenance of Electric Motor Systems
S. Kotsilitis, K. Chairetakis, A. Katsari and E. Marcoulaki


Degradation Modelling of Centrifugal Pumps as Input to Predictive Maintenance
Tom Ivar Pedersen, Jørn Vatn and Kim A. Jørgensen


Modeling Turbocharger Failures using Markov Process for Predictive Maintenance
Mahmoud Rahat, Sepideh Pashami, Slawomir Nowaczyk and Zahra Kharazian


Data Analysis to Facilitate Offshore Seawater Ultrafiltration Membrane Replacement Decision and Scheduling of Chemical Wash
Abu MD Ariful Islam and Jørn Vatn


Remaining Useful Life Estimation Using Vibration-based Degradation Signals
Bahareh Tajiani, Jørn Vatn and Viggo Gabriel Borg Pedersen


Condition Monitoring and Reliability of a Resistance Spot Welding Process
Matteo Strozzi, Marco Cocconcelli, Riccardo Rubini, Gianmarco Genchi and Alessandro Zanella


Avenues For Future Research on Predictive Maintenance Purposes in Terms of Risk Minimization
Rim Louhichi, Mohamed Sallak and Jacques Pelletan