by Thom Badings

PrimaVera Project

No more train delays, power outages, or failure of production machines? The PrimaVera project, funded by the Dutch National Research Agenda (NWA), represents a major step towards this goal. With predictive maintenance, or just-in-time maintenance (maintenance just before a system breaks down), the reliability of infrastructure and production resources can be increased and the costs of maintenance can be reduced.

Existing predictive maintenance techniques only work for small-scale systems and are difficult to scale up. Choices made in one place in the chain have an important influence on other processes in the chain. The choice of a certain type of sensors and measurements influences the type of predictions that can be made, and therefore also the quality of the predictions. That is why cross-level optimization methods are being developed within PrimaVera.

Latest publications

  • R. B. Ragnar Eggertsson and G. van Houtum, “Maintenance optimization for capital goods when information is incomplete and environment-dependent,” Iise transactions, pp. 1-16, 2023. doi:10.1080/24725854.2023.2257245
    [BibTeX] [Download PDF]
    author = {Ragnar Eggertsson, Rob Basten and Geert-Jan van Houtum},
    title = {Maintenance optimization for capital goods when information is incomplete and environment-dependent},
    journal = {IISE Transactions},
    volume = {0},
    number = {0},
    pages = {1-16},
    year = {2023},
    publisher = {Taylor & Francis},
    doi = {10.1080/24725854.2023.2257245},
    URL = {},
    eprint = {}

  • R. Soltani, M. Volk, L. Diamonte, M. L. -, and M. Stoelinga, “Optimal spare management via statistical model checking: A case study in research reactors,” in FMICS, 2023, p. 205–223.
    author = {Reza Soltani and
    Matthias Volk and
    Leonardo Diamonte and
    Milan Lopuha{\"{a}}{-}Zwakenberg and
    Mari{\"{e}}lle Stoelinga},
    title = {Optimal Spare Management via Statistical Model Checking: {A} Case
    Study in Research Reactors},
    booktitle = {{FMICS}},
    series = {Lecture Notes in Computer Science},
    volume = {14290},
    pages = {205--223},
    publisher = {Springer},
    year = {2023}

  • N. R. Marinho, R. Loendersloot, T. Tinga, F. Grooteman, and J. W. Wiegman, “A comparison of optical sensing systems with piezo-electric sensors for impact identification of composite plates,” in 14th international workshop on structural health monitoring, iwshm 2023, 2023, p. 1127–1133.
    title={A Comparison of Optical Sensing Systems with Piezo-Electric Sensors for Impact Identification of Composite Plates},
    author={Marinho, Nat{\'a}lia Ribeiro and Loendersloot, Richard and Tinga, Tiedo and Grooteman, Frank and Wiegman, Jan Willem},
    booktitle={14th International Workshop on Structural Health Monitoring, IWSHM 2023},
    organization={DEStech Publications, Inc}

  • Z. Kang, A. Marandi, R. J. I. Basten, and T. De Kok, “Robust spare parts inventory management,” Management science (submitted), vol. 15, 2023.
    [BibTeX] [Download PDF]
    title = "Robust Spare Parts Inventory Management",
    author = {Kang, Zhao and
    Marandi, Ahmadreza and
    Basten, Rob J.I. and
    De Kok, Ton},
    year = "2023",
    month = aug,
    day = "27",
    url = {},
    volume = "15",
    journal = "Management Science (submitted)"

  • M. Volk, M. I. Irshad, J. Katoen, F. Sher, M. Stoelinga, and A. Zafar, “Safest: the static and dynamic fault tree analysis tool,” in Esrel, 2023, p. 193–200. doi:10.3850/978-981-18-8071-1_P407-cd
    [BibTeX] [Download PDF]
    author = {Matthias Volk and
    Muzammil Ibne Irshad and
    Joost-Pieter Katoen and
    Falak Sher and
    Mari{\"{e}}lle Stoelinga and
    Ahmad Zafar},
    title = {SAFEST: the static and dynamic fault tree analysis tool},
    booktitle = {ESREL},
    pages = {193--200},
    publisher = {Research Publishing},
    year = {2023},
    doi = {10.3850/978-981-18-8071-1_P407-cd},
    url = {},

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