Séminaire Ramy Harik

Quand

25 novembre 2024    
14h00 - 16h00

FST - AIPL
745 Rue du Jardin Botanique, Villers-lès-Nancy

Type d’évènement

Biography:
Dr. Ramy Harik, a Fulbright Alumni, is the Director of the Clemson Composites Center and a Professor of Automotive Engineering at Clemson University. Ramy holds degrees in Mechanical Engineering (BS/MS), Automated Manufacturing (MS), and Industrial/Mechanical Engineering (PhD). His teaching focuses on Manufacturing, Smart Manufacturing, and Composites Manufacturing. Dr. Harik serves as an Associate Editor for SME Manufacturing Letters and authored the “Introduction to Advanced Manufacturing” textbook published by SAE. He has secured over 15 million USD in funding from NASA, Boeing, and others. Recognized as one of the top 20 influential professors in Smart Manufacturing by SME’s Smart Manufacturing Magazine in 2020, he has extensive teaching experience globally and has supervised over 20 graduate students and founded research initiatives. His book “Manufacturing vs Corruption: Who Wins?” won the 2023 Independent Press Award Distinguished Favorite for Social/Political Change books. In June 2024, Dr. Harik received the SC Governor’s Award for Excellence in Scientific Awareness, South Carolina’s highest honor for promoting science education and supporting the future workforce.

Talk abstract :
Manufacturing is essential for economic prosperity, prompting nations to advance their production capabilities for global competitiveness. This progress must prioritize worker well-being by providing engaging roles and preventing labor exploitation. Future factories will achieve this through automation and intelligent systems that eliminate repetitive manual tasks, allowing human workers to focus on complex and cognitively demanding activities. This presentation examines the characteristics of these factories and presents our recent research towards their realization. We will discuss cognitive manufacturing, robust cybersecurity protocols and the application of blockchain technology to establish trust and transparency in manufacturing processes. Additionally, we will explore how independent validation, automated quality assessments, and the integration of mixed reality can optimize production. Safety leveraging computer vision will ensure secure industrial environments, while advancements in autonomous industrial facilities will increase efficiency. Finally, we will introduce publicly available datasets to accelerate AI adoption in manufacturing, promoting innovation and a human-centric industrial sector.

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