I.I. (Ingeborg) de Pater MSc

I.I. (Ingeborg) de Pater MSc

Profiel

Selected papers

Title: Alarm-based predictive maintenance scheduling for aircraft engines with imperfect Remaining Useful Life prognostics. DOI:  https://doi.org/10.1016/j.ress.2022.108341 Description:   In this paper we propose a dynamic, predictive maintenance scheduling framework for a fleet of aircraft taking into account imperfect RUL prognostics. Based on the evolution of the prognostics over time, alarms are triggered. The scheduling of maintenance tasks is initiated only after these alarms are triggered. Alarms ensure that maintenance tasks are not rescheduled multiple times. A maintenance task is scheduled using a safety factor, to account for potential errors in the RUL prognostics and thus avoid component failures. We illustrate our approach for a fleet of 20 aircraft, each equipped with 2  turbofan engines. A Convolution  Neural Network  is proposed to obtain RUL prognostics. An integer  linear program is used to schedule aircraft for maintenance. 

    Title: Predictive maintenance for multi-component systems of repairables with Remaining-Useful-Life prognostics and a limited stock of spare components.  I. de Pater, M. Mitici, Reliability Engineering and System Safety. 2021. DOI:   https://doi.org/10.1016/j.ress.2021.107761
    Description: This paper proposes an integrated approach for predictive aircraft maintenance planning for multiple multi-component systems, where the components are repairables. First, model-based Remaining-Useful-Life prognostics are developed. Then, a rolling horizon integer linear program is developed for the maintenance planning of multiple multi-component systems. This model integrates the Remaining-Useful-Life prognostics with the management of a limited stock of spare repairable components. Our approach is illustrated for a fleet of aircraft, each equipped with a Cooling System consisting of four Cooling Units.   
    Title: Online Model-Based Remaining-Useful-Life Prognostics for Aircraft Cooling Units Using Time-Warping Degradation Clustering    DOI: doi.org/10.3390/aerospace8060168    Description: This paper proposes an end-to-end approach to obtain model-based Remaining-Useful-Life prognostics by learning from clusters of components with similar degradaion trends. Time-series of degradation measurements are first clustered using dynamic time-warping. For each cluster, a degradation model and corresponding failure threshold are proposed. These cluster-specific degradation models, together with a particle filtering algorithm, are further used to obtain online remaining-useful-life prognostics. As a case study, we consider the operational data of several aircraft Cooling Units. 

    Biografie

    Ingeborg de Pater has a bachelor degree in Econometrics and Operations Research, and a Master in Operations Research and Quantitative Logistics (Econometrics and Management Science), both from the Erasmus University Rotterdam.  Currently, she is doing a PhD about predictive aircraft maintenance, with a focus on the Remaining-Useful-Life (RUL) estimation of aircraft components and the application of these probabilitic RUL estimations in predictive aircraft maintenance scheduling. 

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    Expertise

    Publicaties

    Prijzen

    • 2022

      Best Paper Award 2nd Prize, European Conference of the Prognostics and Health Management Society


      PHM Society European Conference 2022

      Lees meer Best Paper Award 2nd Prize, European Conference of the Prognostics and Health Management Society
    • 2021-9-29

      Anna Valicek Award 2021

      PhD candidate Ingeborg de Pater has received the Silver Medal for her paper on predictive aircraft maintenance at the 61st Annual Symposium AGIFORS (Airline Group of the International Federation of Operational Research Societies). Earlier this year Ingeborg’s work on aircraft maintenance has been awarded the Best Innovation at the AGIFORS Aircraft Maintenance Operations conference

      Lees meer Anna Valicek Award 2021
    • 2021-7-16

      Best Innovation award

      Promovenda Ingeborg de Pater heeft op de AGIFORS Aircraft Maintenance Operations conferentie de Best Innovation award ontvangen voor haar werk: ‘Predictive maintenance for a fleet of aircraft with Remaining-Useful-Life prognostics and the management of spare components’. De prijs is een erkenning voor "de meest innovatieve ideeĂ«n of concepten voor het oplossen van een probleem in verband met de exploitatie van luchtvaartmaatschappijen".
      AGIFORS Aircraft Maintenance Operations Special Session

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