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

 

Ashish Ranjan Dash | Engineering | Best Researcher Award

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Dr. Ashish Ranjan Dash | Engineering | Best Researcher Award

Associate Professor at Centurion University of Technology and Management | India

Dr. Ashish Ranjan Dash is a highly accomplished academic and researcher in the field of electrical engineering, specializing in power electronics, multilevel inverters, and power quality improvement. With a proven track record in research, teaching, and project leadership, he has significantly contributed to advancements in smart infrastructure, renewable energy systems, and IoT-enabled agricultural automation. He has also played a pivotal role in supervising doctoral students, developing innovative solutions for industrial applications, and leading consultancy projects for technology-driven agriculture and smart systems.

Publication Profile 

Scopus

Google Scholar

Educational Background 

Dr. Dash earned his Ph.D. in Power Electronics from the National Institute of Technology (NIT) Rourkela, focusing on cascaded multilevel inverter-based shunt active filters under varying grid voltage conditions. He also holds an M.Tech. in Power Control and Drives from NIT Rourkela, where his dissertation explored control strategies for grid-connected inverter systems during fault conditions. His academic foundation is further strengthened by a B.Tech. in Electrical Engineering and a Diploma in Electrical Engineering, complemented by a strong record of academic excellence throughout his studies.

Professional Experience 

With over a decade of academic and research experience, Dr. Dash serves as an Associate Professor at Centurion University of Technology and Management, Odisha. His prior roles include research and academic positions in engineering colleges and at the Council of Scientific and Industrial Research. He has held key administrative positions such as Dean and Associate Dean of the School of Engineering and CEO of the Smart Infrastructure Research Center, where he has led interdisciplinary projects integrating IoT, automation, and renewable energy systems.

Research Interests 

His research focuses on power electronics, multilevel inverter design, power quality enhancement, electric vehicle charging infrastructure, smart grid systems, and IoT-enabled automation. He also works extensively on agricultural automation, including polyhouse automation, speed breeding chambers, and plant phenotyping systems. Emerging interests include machine learning applications for plant disease detection, robotics, and smart farming technologies.

Awards and Honors 

Dr. Dash has received multiple accolades, including the Distinguished Achiever Award at the Provost Research Awards and recognition as a session chair at IEEE international conferences. He is the founder of a technology-driven startup and actively engages in professional communities such as the IEEE Power Electronics Society, IEEE Industry Applications Society, and IEEE SIGHT.

Research Skills 

He possesses strong expertise in the design, modeling, and implementation of cascaded multilevel inverters, power quality control algorithms, and renewable energy integration. His skills extend to IoT-based system design, automation technologies, electric vehicle charging systems, and cloud-based agricultural monitoring. He is also an experienced reviewer for several high-impact international journals in power electronics and smart grid applications.

Publications 

A unified control of grid-interactive off-board EV battery charger with improved power quality

Citations: 49

Year: 2022

Reactive power compensation using vehicle-to-grid enabled bidirectional off-board EV battery charger

Citations: 34

Year: 2021

Adaptive LMBP training‐based icosϕ control technique for DSTATCOM

Citations: 33

Year: 2020

Analysis of PI and PR controllers for distributed power generation system under unbalanced grid faults

Citations: 33

Year: 2011

Design and implementation of a cascaded transformer coupled multilevel inverter‐based shunt active filter under different grid voltage conditions

Citations: 24

Year: 2019

Conclusion 

Dr. Ashish Ranjan Dash is a forward-looking researcher and educator whose work bridges advanced power electronics with practical applications in smart infrastructure and agricultural automation. His multidisciplinary expertise, leadership in funded projects, and dedication to mentoring the next generation of engineers make him a valuable contributor to both academia and industry. His continued research promises innovative advancements in electric mobility, renewable energy integration, and intelligent automation systems.