Pascal Vrignat | Industry 4.0 | Research Excellence Award

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Dr. Pascal Vrignat | Industry 4.0 | Research Excellence Award

Prisme Laboratory at Orleans University | France

Pascal Vrignat is a researcher specializing in operational safety, diagnostics, prognostics, and maintenance strategies for complex systems, with particular expertise in Markovian and stochastic models. His work significantly advances methods for estimating system degradation using survival laws, hidden Markov models, and Remaining Useful Life approaches. He contributes to understanding system obsolescence and managing shortages across the life cycle of industrial systems. His research bridges theory and industrial application, encompassing industrial computing, advanced process control, human–machine interfaces, SCADA systems, IoT, M2M technologies, and digital communication protocols, including OPC-based architectures. He has an extensive record of scientific output, including journal publications, conference papers, book chapters, and a widely used textbook on industrial local networks. His recent works address bearing degradation monitoring and the role of AI in sustainability-focused applications. He is active in research project development, editorial responsibilities, and academic leadership within his institution and research laboratory. His contributions to industry-oriented R&D have earned recognition in international automation competitions. His scholarly impact is reflected in 618 citations (405 since 2020), an h-index of 10 (7 since 2020), and an i10-index of 13 (6 since 2020), underscoring his sustained influence in the fields of reliability engineering, automation, predictive maintenance, and digital industrial systems.

Profiles: Orcid | Google Scholar

Featured Publications

Vrignat, P., Kratz, F., & Avila, M. (2022). Sustainable manufacturing, maintenance policies, prognostics and health management: A literature review. Reliability Engineering & System Safety, 218, 108140. https://doi.org/10.1016/j.ress.2021.108140
Cited by: 152

Pascal, V., Toufik, A., Manuel, A., Florent, D., & Kratz, F. (2019). Improvement indicators for total productive maintenance policy. Control Engineering Practice, 82, 86–96. https://doi.org/10.1016/j.conengprac.2018.09.019
Cited by: 81

Vrignat, P., Avila, M., Duculty, F., & Kratz, F. (2015). Failure event prediction using hidden Markov model approaches. IEEE Transactions on Reliability, 64(3), 1038–1048. https://doi.org/10.1109/TR.2015.2426458
Cited by: 49

Aggab, T., Avila, M., Vrignat, P., & Kratz, F. (2021). Unifying model-based prognosis with learning-based time-series prediction methods: Application to Li-ion battery. IEEE Systems Journal, 15(4), 5245–5254. https://doi.org/10.1109/JSYST.2021.3080125
Cited by: 32

Vrignat, P., Avila, M., Duculty, F., Aupetit, S., Slimane, M., & Kratz, F. (2012). Maintenance policy: Degradation laws versus Hidden Markov Model availability indicator. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 226(2), 137–155. https://doi.org/10.1177/1748006X11406335
Cited by: 21

 

Salomon Dominique Edimo Kingue | Engineering | Research Excellence Award

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Mr. Salomon Dominique Edimo Kingue | Engineering | Research Excellence Award

State University of Campinas | Brazil

Mr. Salomon Dominique Edimo Kingue is a reservoir engineer and researcher specializing in enhanced oil recovery (EOR), reservoir simulation, and sustainable subsurface energy strategies. His expertise centers on FAWAG/WAG processes, CO₂ storage modeling, and integrated reservoir–production optimization for complex carbonate systems, particularly within Brazilian pre-salt environments. He is highly skilled in using CMG (IMEX, STARS, GEM, CMOST), Petrel, Python, and advanced analytical tools to investigate flow behavior, improve recovery efficiency, and reduce greenhouse gas emissions. His research spans numerical simulation of EOR mechanisms, uncertainty analysis, carbon capture and storage (CCS), fractured-vuggy reservoir upscaling, and evaluation of production potential in hydrocarbon basins. He has co-authored studies on underground LPG storage and reservoir performance prediction, and contributed to interdisciplinary projects involving major industry partners. His work also extends to geological interpretation, multidisciplinary collaboration, and scientific communication through symposiums, poster sessions, and peer-reviewed publications. Salomon combines strong analytical reasoning with leadership, teamwork, and effective communication, reflecting his commitment to innovation-driven reservoir management and the advancement of low-carbon energy solutions.

Profile: Orcid

Featured Publications

Kingue, S. D. E., Akinmuda, O. B., Kuiekem, D., & Djitchouang, G. L. (2025). Assessing the production potential of Niger Delta reservoirs under uncertainty using numerical simulation tools. Petroleum Science and Technology.

Kuiekem, D., Kingue, S. D. E., Boroh, W., Noupa, R. K., Matateyou, J., & Ngounouno, I. (2025). Simulation study of underground LPG storage in a depleted conceptual oil reservoir. Petro Chem Indus Intern, 8(2), 1–14.

ABLA CHAOUNI BENABDELLAH | Engineering | Best Researcher Award

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Assist. Prof. Dr. ABLA CHAOUNI BENABDELLAH | Engineering | Best Researcher Award

BEST RESEARCHER at International University of rabat, Morocco

Abla Chaouni Benabdellah is an Assistant Professor of Supply Chain Management and Information Systems at Rabat Business School, International University of Rabat (UIR). She holds a Ph.D. in Industrial Engineering from Moulay Ismail University, Meknes, and a Master’s in Mathematics and Statistics from Mohamed V University, Rabat. With extensive teaching experience across various institutions including EUROMED University and Private University of Fez, she specializes in project management, risk management, and supply chain strategies.

Publication Profile : 

Scopus

🎓 Educational Background :

  • Ph.D. in Industrial Engineering (2016 – 2019), Moulay Ismail University, ENSAM, Meknes
  • Master in Mathematics and Statistics (2012 – 2014), Mohamed V University, Rabat
  • Bachelor in Applied Mathematics (2009 – 2012), Moulay Ismail University, Faculty of Science, Meknes
  • Baccalaureate in Mathematics (2008 – 2009), Moulay Ismail College, Meknes

💼 Professional Experience :

  • Assistant Professor of Supply Chain Management & Information Systems (Since 2022), Rabat Business School, International University of Rabat (UIR), Rabat
  • Human Resources Consultant (2021), Expert Human Capital (EHC), Casablanca
  • Professor (2020), School of Digital Engineering and Artificial Intelligence (EIDIA), EUROMED University, Fez
  • Professor (2020), Private University of Fez, Fez
  • Seminar Presenter (2020), “Holonic Multi-Agent Systems for Decision Making -Application to Knowledge Management-“, ENSAM, Meknès
  • Doctoral Course Instructor (2019), Statistical Modeling with R Software, ENSAM-Meknès
  • Coordinator (2018), Artificial Intelligence and Data Science Master, SUPMTI, Meknes
  • Professor (2016), Higher School of Management, Telecommunications and IT (SUPMTI), Meknes

📚 Research Interests : 

  • Supply Chain Management
  • Industrial Engineering
  • Digital Supply Chains
  • Blockchain Technology
  • Artificial Intelligence and Data Science
  • Statistical Modeling

📝 Publication Top Notes :

  1. Blockchain Technology in Supply Chains: Discusses blockchain’s role in enhancing digital supply chains and evaluates implementation barriers.
  2. Big Data Analytics in Supplier Selection: Explores a multi-agent system for supplier selection using big data analytics.
  3. Smart Product Design and Digital Agility: Develops an ontology for managing agility in digital product design.
  4. Blockchain and Smart Contracts in Automotive Supply Chains: Examines how blockchain and smart contracts can optimize automotive supply chains.
  5. Medical Waste Management Optimization: A multi-agent system approach for improving medical waste management.
  6. Sustainable Supplier Selection in Circular Economy: Uses an ontology-based model to improve supplier selection under a circular economy framework.
  7. Environmental Supply Chain Risk Management: Proposes a data mining framework for managing supply chain risks in Industry 4.0.
  8. Lean and Green Practices in Supply Chains: Integrates lean and green practices to enhance sustainable and digital supply chain performance.
  9. Digital Technologies and Circular Economy: Investigates how digital technologies support sustainable supply chain management post-COVID-19.
  10. Circular Digital Supply Chain Design: Focuses on sustainable design practices within digital supply chains.
  11. Supplier Selection Ontology: Develops an ontology for effective supplier selection in digital supply chains.
  12. Intersection of Design for X and Business Strategies: Analyzes the integration of design techniques and business strategies for product lifecycle management.
  13. Knowledge Discovery for Sustainability: Discusses methods for enhancing sustainability through knowledge discovery in design processes.