Ahmed Mujtaba
Papers
2
Total Citations
36
H-Index
2
About
Ahmed Mujtaba is a researcher at the forefront of intelligent manufacturing, specializing in the intersection of machine learning, automated composites processing, and digital twin technology. His work focuses on enhancing the quality and reliability of automated fibre placement (AFP), a robotic technique critical for producing high-performance composite materials used in aerospace and automotive industries. Mujtaba’s major contribution lies in developing machine-learning-based process monitoring systems that analyze in-situ thermal histories during manufacturing, directly addressing the challenge of interlaminar strength variability in composites. His most-cited paper, "Machine-learning based process monitoring for automated composites manufacturing" (2023, 31 citations), demonstrates how real-time data can predict and optimize material properties, laying the groundwork for smarter, more adaptive production lines. A follow-up study (2022, 5 citations) extends this work toward digital twin development, envisioning fully virtualized manufacturing environments. Though early in his career, Mujtaba’s research has already garnered attention for its practical impact on reducing defects and waste in advanced manufacturing, positioning him as a rising voice in Industry 4.0 innovation.
Research Focus
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Top Papers
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