Integrated vehicle management


Description

The aim is to facilitate integrated vehicle health monitoring (IVHM) of heavy trucks. The focus then was to investigate how to predict the vehicle’s health status by calculating the components remaining life to be able for create better decisions for example: (1) using health status to schedule maintenance so that unplanned downtime is minimized, (2) creating a system that optimizes maintenance plans based in part on the health status and customer preferences, and (3) creating a system that provides decision support to drivers and fleet planners utilization of vehicles.


Latest publications

  • Robust Contrastive Learning and Multi-shot Voting for High-dimensional Multivariate Data-driven Prognostics
    Sun, Kaiji, Magnússon, Sindri, Steinert, Olof, and Lindgren, Tony
    In 2023 IEEE International Conference on Prognostics and Health Management (ICPHM), 2023
    Bridging the Gap: A Comparative Analysis of Regressive Remaining Useful Life Prediction and Survival Analysis Methods for Predictive Maintenance
    Rahat, Mahmoud, Kharazian, Zahra, Mashhadi, Peyman Sheikholharam, Rögnvaldsson, Thorsteinn, and Choudhury, Shamik
    In PHM Society Asia-Pacific Conference, 2023
    Low dimensional synthetic data generation for improving data driven prognostic models
    Lindgren, Tony, and Steinert, Olof
    In 2022 IEEE International Conference on Prognostics and Health Management (ICPHM), 2022
    Hierarchical Bayesian modeling for knowledge transfer across engineering fleets via multitask learning
    Bull, L. A., Francesco, D. Di, Dhada, M., Steinert, O., Lindgren, Tony, Parlikad, A. K., Duncan, A. B., and Girolami, M.
    Computer-Aided Civil and Infrastructure Engineering, 2022
    Weibull recurrent neural networks for failure prognosis using histogram data
    Dhada, Maharshi, Parlikad, Ajith Kumar, Steinert, Olof, and Lindgren, Tony
    Neural Computing and Applications, 2022
    An Interactive Visual Tool to Enhance Understanding of Random Forest Predictions
    Gurung, Ram B., Lindgren, Tony, and Boström, Henrik
    Archives of Data Science, Series A (Online First), 2020
    Prediction of Global Navigation Satellite System Positioning Errors with Guarantees
    Kuratomi, Alejandro, Lindgren, Tony, and Papapetrou, Panagiotis
    In Joint European Conference on Machine Learning and Knowledge Discovery in Databases, 2020

    People

    Tony Lindgren, Associate Professor
    Tony Lindgren, Associate Professor
    explainability, predictive maintanance
    Alejandro Kuratomi, Teaching Assistant
    Alejandro Kuratomi, Teaching Assistant
    interpretable models with statistical guarantees
    Zahra Kharazian
    Zahra Kharazian
    data science, predictive maintenance
    Department of Computer and Systems Sciences of Stockholm University