QARTZ, Université Paris 8 | France
Naima Rahiel is a dedicated doctoral researcher in Industrial Engineering and Productics at ED CLI, Université Paris 8, where she has been engaged in advanced studies since January 2022. She holds both a Master’s degree and a Bachelor’s degree in Industrial Engineering from IMSI, Université Oran 2, Algeria, obtained in 2020 and 2018 respectively. Her academic journey reflects a consistent commitment to the development of expertise in industrial systems, process optimization, and innovative engineering solutions. Professionally, she has gained valuable experience through academic and applied research in industrial engineering, emphasizing areas such as production systems, operations management, and industrial productics. Her research interests lie in digital transformation of industries, sustainable manufacturing, quality management, lean systems, and the integration of advanced technologies to improve industrial performance. Rahiel has participated in collaborative projects and academic exchanges that highlight her capacity to work across interdisciplinary teams, bringing analytical skills and innovative thinking to complex industrial challenges. She has been recognized for her academic achievements and contributions to research, receiving distinctions that reflect her scholarly excellence. Moving forward, she aims to contribute to the advancement of industrial engineering research and to promote sustainable and efficient industrial practices in both academic and applied contexts.
Featured Publications
Rahiel, N., El Mhamedi, A., & Hachemi, K. (2024). Healthcare supply chain: Resilience qualitative evaluation. Hospital Supply Chain: Challenges and Opportunities for Improving Healthcare.
Rahiel, N., El Mhamedi, A., Hachemi, K., Aouffen, N., & Rahiel, I. (2025). Resilience of the hospital supply chain: A case study-based approach on safety stock. Environment Systems and Decisions, 45(4), 56.
Rahiel, N., Addouche, S. A., El Mhamedi, A., & Hachemi, K. (2025). Function-based modeling for reactive optimization of healthcare resource reallocation. In Proceedings of the 16th International Conference on Logistics and Supply Chain Management.