Research activities

Research topics of interest:

  • PHM-Prognostics and Health Management
  • Reliability and maintenance modelling
  • Degradation modelling and failure/performance prediction
  • Reliability Importance measures and related applications for complex systems
  • Condition-based maintenance
  • Predictive and prescriptive/intelligent maintenance
  • Dynamic grouping maintenance and routing optimization for multi-component systems
  • Artificial Intelligence for prognostics of performance/failure
  • Reinforcement Learning for predictive maintenance decision-making and optimization

Research projects:

  • Industrial contracts:
    • A contract with Feedgy, France for a PhD projet (2023-2026)
    • A contract with EODev, France for a PhD projet (2022-2025)
    • A contract with AccelorMittal, France for a PhD projet (2020-2023)
    • Strong involvement (co-leader ) in a collaboration contract with Renault automotive "development of a tool for smoothing of maintenance loads", 2018/2019 (leader of the development of the algorithm and its implementation)
    • Strong involvement (scientific co-leader) in a contract with GRTGaz, in collaboration with Prédict and Sector "Feasibility study relating to the implementation of a predictive maintenance solution", contract S18143-P01B, 2018.
    • Participation (Task leader) in a collaboration contract, as part of IMdR, with Prédict and Sector "Health and Usage Monitoring System (HUMS), Contract S15309-R01H, 2017 (significant participation in the bibliographic study around advanced methods prognosis)
    • Participation in a collaboration contract with Electricité de France (EDF), 2003-2004 (significant participation in the development of a reliability important measures)
  • Academic research projects:
    • Participation (WP leader) in the european project MODAPTO (Modular manufacturing and distributed control via interoperable digital twin). 12 partners europeans, 2023-2025.
    • Participation in ANR X-IMS project – “Explainable intelligent maintenance solution for connected manufacturing systems”, 2023-2026
    • Participation (Task leader) in the european project H2020-ICT AI-PROFICIENT (Artificial Intelligence for improved PROduction efFICIEncy, quality and maintenance). 10 partners europeans, 2020-2023. My role is to develop a task in the workparkage entrusted to UL)
    • SAFEE - Fault and Reliable dynamic systems. (2011-2012,partners: CRAN, LAGIS, ICD)
    • APPRODYN - DYNamic reliability approaches for modeling systems critics (2010-2012, partner: EDF R&D/MRI, CRAN, INRIA Bordeaux Southwest, and UTT)
    • Participation in the european project MoDe - Maintenance on demand (8 partners europeans, 2009-2012). My role was to develop a task in the workparkage entrusted to UTT)
    • Participation in the VITTEL project (fonctional degradation modelling: Assessment of its impact on the competitiveness and reliability of the industry of
      future) funded by the Lorraine region, 2016-2017. My contribution was the degradation modeling using gamma process
    • Leader of prognostic algorithms and implementation axis of ANR LABCOM PHM-Factory ANR-15-LCV1-0005-01 (Manufactur of cyber physical technologies for PHM (prognostics and Health Management), a joint laboratories between research organizations and SMEs CRAN/Predict.
    • Leader of the CAPE-COFECUB project - towards an intelligent autonomous system for maintenance optimization in an industry 4.0 context, (project Ph950 / 19) co-funded by the ANR in collaboration with the UFPE team (University Federal Republic of Pernambuco), Brazil, 2019-2022.

Supervision:

  • In progress (5):
    • Thanh Thai (01/2024-1/2026. Failure prognostics and predictive maintenance for manufacturing system with sensor data uncertainty (Supervisor: Phuc Do; Co-supervisor: Prof. Benoit Iung)
    • Huu-Truong LE (07/2023-07/2026). Artificial Intelligence-based machine learning and reasoning for predictive maintenance in Industry 4.0 (Supervisor: Phuc Do; Co-supervisor: Dr. Alexandre Voisin)
    • Jorge Ruiz Amantegui (05/2023-05/2026). Artificial Intelligence for predictive maintenance of photovoltaïc power plants  (Supervisor: Phuc Do, co-supervisor: Dr. Hai-Canh Vu)
    • Soufian Echabarri (11/2022-11/2025). Failure prognosis and decision making for predictive maintenance of a hydrogen power generator using Artificial Intelligence  (Supervisor: Phuc Do, co-supervisor: Dr. Hai-Canh Vu)
    • Waldomiro Alves Ferreira Neto (02/2021-02/2025). Reinforcement learning-based maintenance optimization for steel production line  (Supervisor: Cristiano Cavalcante (UFPE); Co-supervisor: Phuc Do)
  • Past supervisions (9 PhD + 7 Masters)
    • Van-Thai Nguyen (defended in June 2023). AI-based proactive maintenance decision-marking for industry 4.0 (Supervisor: Phuc Do; Co-supervisor: Dr. Alexandre Voisin)
    • Antony Gay (defended in June 2023) : Machine Learning-based Failure prognosis and decision support optimization for predictive maintenance combining expert knowledge and process data (Supervisor: Prof. Benoit Iung, Co-supervisor: Dr. Alexandre Voisin & Phuc Do)
    • TRUONG Minh-Tuan (defensed in March 2022). Test plan optimization method for reliability assessment of optoelectronic components. (Supervisor: Prof. Benoit Iung; Co-supervisor: Phuc Do)
    • Duc-Hanh DINH (Defended in October 2021). Predictive maintenance for multi-components with assembly/disassembly impacts (Supervisor: Phuc Do; Co-supervisor: Prof. Benoit Iung)
    • Hanser Steven Jimenez Gonzalez (defensed in December 2021). A contribution to machine learning applications in logistic and maintenance problems (Supervisor: Cristiano Cavalcante (UFPE); Co-supervisor: Phuc Do)
    • Ho-Si-Hung NGUYEN (Defended in October 2019). Dynamic maintenance grouping for geographically dispersed production systems. (Supervisor: Prof. Benoit Iung; Co-supervisor: Phuc Do)
    • Hoang Anh (Defended in July 2017). Energy efficiency-based Prognostics for maintenance of industrial systems (Supervisor: Prof. Benoit Iung; Co-supervisor: Phuc Do)
    • Kim-Anh NGUYEN (Defended in October 2015). Predictive maintenance for complex systems using importance measures (Supervisor: Phuc Do; Co-supervisor: Prof. Antoine Grall) ,
    • Hai-Canh VU (Defensed in March 2015). Dynamic and stationary grouping maintenance models for multi-component systems with complex structure (Supervisor: Phuc Do; Co-supervisor: Prof. Antoine Barros)
    • 7 Pre-Doctoral or Masters of science thesis