Issam Mallouk
Papers
1
Total Citations
4
H-Index
1
About
Driven by the imperative to modernize manufacturing in the face of global competition, Issam Mallouk’s research sits at the vital intersection of industrial decision-making and artificial intelligence. His work fundamentally addresses how manufacturers can harness machine learning to transform raw operational data into actionable intelligence. In his most cited work, "A generic model of the information and decisional chain using Machine Learning based assistance in a manufacturing context" (2023, 4 citations), Mallouk proposes a pioneering framework that integrates Condition-based Maintenance (CBM), Prognostics and Health Management (PHM), and Product Lifecycle Management (PLM). This model provides a structured pathway for factories to move from reactive repairs to predictive, data-driven strategies, significantly enhancing performance and competitiveness. By formalizing how ML assistance can be embedded into the entire decisional chain, his contributions offer a scalable blueprint for smart manufacturing. Mallouk’s research is particularly notable for its holistic approach, bridging the gap between theoretical AI models and practical industrial application, making him a key voice in the evolution of intelligent, resilient production systems.
Research Focus
Key Achievements
Top Papers
- 1