Abdelkader Lousdad

Papers

Total Citations

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About

Abdelkader Lousdad is a prominent researcher in mechanical and industrial engineering, with key contributions to robotics, manufacturing optimization, and machining processes. His work focuses on enhancing automation and efficiency in production systems, particularly through the application of advanced computational methods. His most cited paper, "Determination of the Optimal Path of Three Axes Robot Using Genetic Algorithm" (2019, 16 citations), addresses a critical challenge in robotic drilling—a widely used chip machining process for creating cylindrical holes in workpieces, including applications like PCB manufacturing. By employing genetic algorithms, Lousdad developed a method to optimize the path of three-axis robots, significantly improving precision and reducing cycle times in automated drilling operations. This work underscores his expertise in integrating artificial intelligence with traditional manufacturing techniques to solve real-world industrial problems. Lousdad’s research has been influential in advancing robotic path planning and machining efficiency, with his findings cited by peers exploring similar optimization challenges. His contributions are particularly valuable for students and researchers interested in the intersection of robotics, genetic algorithms, and manufacturing process improvement, offering a practical framework for enhancing productivity in modern production environments.