Ebrahim Farrokh | Engineering and Technology | Best Researcher Award

Ebrahim Farrokh | Engineering and Technology | Best Researcher Award

Assoc. Prof. Dr Ebrahim Farrokh, Amirkabir University of Technology, Iran

Assoc. Prof. Dr. Ebrahim Farrokh is a distinguished expert in rock mechanics and mining engineering, serving as the Head of Rock Mechanics and Mining Engineering at Amirkabir University of Technology. With a career spanning academia and industry, he specializes in tunnel boring machines (TBMs), underground excavation, and rock stability analysis. He has played a key role in major tunneling projects, providing expertise on TBM operations, rock fragmentation, and ground control. His research has led to numerous influential publications, advancing TBM performance prediction and tunnel design methodologies. Alongside his academic role, he consults for Tunnel Saz Machin Co. and has held managerial positions at Hyundai Engineering and Construction. Recognized with prestigious awards, including the Hardy Memorial Award and SME’s NAT Conference Scholarship, his contributions continue to shape the field of mining engineering. His work combines theoretical advancements with practical applications, ensuring safer and more efficient underground construction projects. πŸš†πŸ’‘

Publication Profile

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Education

  • Ph.D. in Mining Engineering, Penn State University (2009-2012) πŸ—οΈ
    Dr. Farrokh earned his Ph.D. at Penn State University, focusing on TBM performance evaluation, advance rate prediction, and rock behavior analysis. His research contributed to innovative methodologies for assessing TBM cutter wear and ground stability.

  • M.Sc. in Mining Engineering, Tehran University (2001-2004) ⛏️
    During his master’s studies, he specialized in underground excavation, tunnel stability, and mine planning. His thesis examined rock fragmentation techniques and their applications in mechanized tunneling.

  • B.Sc. in Mining Engineering, Yazd University (1997-2001) 🌍
    He completed his undergraduate degree at Yazd University, gaining foundational knowledge in rock mechanics, mineral extraction, and geotechnical engineering. His early research explored TBM operational parameters and ground convergence in tunneling projects.

Experience

  • Associate Professor & Head, Rock Mechanics & Mining Engineering, Amirkabir University of Technology (2018-present) πŸŽ“
    Leads research and academic initiatives in TBMs, tunnel stability, and underground mining.

  • Consultant, Tunnel Saz Machin Co. (2018-present) πŸ—οΈ
    Provides technical expertise in TBM operations, ground support, and excavation efficiency.

  • TBM Specialist & Manager, Hyundai Engineering & Construction (2013-2017) 🚜
    Managed TBM operations in major tunneling projects, optimizing performance and reducing downtime.

  • Research Assistant, Penn State University (2009-2012) πŸ“Š
    Conducted cutting-edge research on TBM cutter wear, penetration rate estimation, and tunnel convergence.

Awards and Honors πŸ†

  • Outstanding Business Performance Award, Hyundai Engineering & Construction (2015) 🌟
    Recognized for leadership in TBM project execution and efficiency improvements.

  • Outstanding Research Award, Hyundai Engineering & Construction (2014, 2015) πŸ…
    Awarded for contributions to TBM performance evaluation and geotechnical risk mitigation.

  • NAT Student Conference Scholarship Award, SME (2012) πŸŽ“
    Acknowledged for excellence in mining engineering research and academic achievements.

  • Hardy Memorial Award, Penn State University (2010) πŸ†
    Prestigious recognition for outstanding research contributions in mining and rock mechanics.

Research Focus

Dr. Farrokh’s research focuses on Tunnel Boring Machines (TBMs) 🚜, specializing in performance evaluation, advance rate prediction, and cutterhead design optimization. In Rock Mechanics πŸ—οΈ, he investigates rock properties, ground convergence, and stability assessment for underground projects. His work in Mining Engineering ⛏️ explores underground mining methods, rock fragmentation, and geotechnical risk analysis. By integrating theoretical advancements with real-world applications, Dr. Farrokh enhances the efficiency and safety of tunneling and mining operations. His research contributes to optimizing excavation processes, reducing operational risks, and advancing sustainable underground construction. πŸ“ŠπŸ”¬

Publications Top Notes

  1. Tunnel Face Pressure Design and Control πŸ“Š (2020)
  2. Concrete Segmental Lining: Procedure of Design, Production, and Erection of Segmental Lining in Mechanized Tunneling πŸ“š (2006)
  3. Study of Various Models for Estimation of Penetration Rate of Hard Rock TBMs πŸ“Š (2012)
  4. Effect of Adverse Geological Conditions on TBM Operation in Ghomroud Tunnel Conveyance Project 🌎 (2009)
  5. Correlation of Tunnel Convergence with TBM Operational Parameters and Chip Size in the Ghomroud Tunnel, Iran πŸ“Š (2008)
  6. A Discussion on Hard Rock TBM Cutter Wear and Cutterhead Intervention Interval Length Evaluation πŸ’‘ (2018)
  7. Evaluation of Ground Convergence and Squeezing Potential in the TBM-Driven Ghomroud Tunnel Project 🌎 (2006)
  8. Study of Utilization Factor and Advance Rate of Hard Rock TBMs πŸ“Š (2013)
  9. A Study of Various Models Used in the Estimation of Advance Rates for Hard Rock TBMs πŸ“Š (2020)
  10. Analysis of Unit Supporting Time and Support Installation Time for Open TBMs πŸ•’ (2020)

Eduardo Garcia Magraner | Engineering and Technology | Best Researcher Award

Eduardo Garcia Magraner | Engineering and Technology | Best Researcher Award

Dr Eduardo Garcia, Magraner Ford Motor Company, Spain

πŸ”§ Dr. Eduardo GarcΓ­a Magraner is a distinguished expert in industrial automation, manufacturing, and occupational safety. With a Ph.D. in Computer Engineering & Industrial Production (Cum Laude, CEU Cardenal Herrera, 2016) πŸŽ“, he has led key roles at Ford Spain πŸš—, from Electromechanical Maintenance to Manufacturing Manager. A Lean Six Sigma Black Belt βš™οΈ, he has earned multiple innovation and safety awards πŸ†, including the Henry Ford Technical Award. A sought-after speaker 🎀 and researcher πŸ“–, his contributions span Industry 4.0, predictive maintenance, and AI-driven efficiency. Passionate about smart factories 🏭, he bridges academia and industry for sustainable progress. 🌍

Publication Profile

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Academic and Professional BackgroundΒ 

Dr. Eduardo Garcia Magraner πŸŽ“βš™οΈ is an expert in industrial engineering, automation, and occupational safety. His academic journey began with vocational training in electrical and telecommunications, followed by a Ph.D. in Computer Engineering and Industrial Production (2016) πŸ…. Certified in Lean Six Sigma (Black Belt) and occupational risk prevention, he has mastered integrated management systems πŸ­βœ…. With expertise in robotics πŸ€–, energy efficiency 🌱, and human resources 🀝, he has undertaken extensive additional training in automation and safety. His research explores machine deterioration and throughput optimization πŸ“Š. A leader in engineering and innovation, he continuously enhances industry standards πŸš€.

Experience

Dr. Eduardo Garcia Magraner has built an impressive career at Ford S.L, starting as a First-Class Electromechanical Maintenance Operator (1990-2001) βš™οΈ. He advanced to Equipment Engineer (2001-2006) and later became a Maintenance Supervisor (2006) πŸ”©. His expertise led him to roles such as Senior Equipment Engineer in Maintenance & Automation (2007-2012) and Production Supervisor (2012) 🏭. He progressed to Manufacturing Manager for Body & Stamping (2014) and Champion of M.O.S. (2016) πŸ”§. As SPOC for Cyber Security (2019) and now Manufacturing Manager for Assembly & Battery Plants (2023), he continues shaping Ford’s production excellence βš‘πŸš—.

Awards and RecognitionsΒ 

Dr. Eduardo Garcia Magraner has been recognized for his outstanding contributions to safety, productivity, and innovation at Ford Spain πŸš—πŸ†. His accolades include multiple Maximum Awards for enhancing press line efficiency (1997, 1999, 2002) and the prestigious Henry Ford Technical Award (2019) for IIoT-based predictive maintenance πŸ”§πŸ“Š. He received honors for workplace safety (1995, 2010, 2012) and academic mentorship at the Polytechnic University of Valencia (2014) πŸŽ“πŸ‘. His work in AI and cybersecurity earned global recognition (2019, 2020) πŸ€–πŸ”. A leader in industrial innovation, he continues to push the boundaries of engineering excellence πŸš€βš™οΈ.

Academic ImpactΒ 

Dr. Eduardo Garcia is a distinguished researcher in automation and smart manufacturing πŸ€–πŸ­. Beyond his groundbreaking research, he has delivered keynote presentations at global conferences, sharing insights on smart factories and AI-driven manufacturing πŸ”πŸŽ€. His expertise has influenced industry advancements, making him a sought-after speaker in the field. In recognition of his contributions, he was honored with the prestigious CEU Ángel Herrera Prize in 2023 πŸ†πŸŽ“, further solidifying his reputation as a leading researcher. Through his work, Dr. Garcia continues to shape the future of industrial automation, bridging innovation and practical applications for smarter, more efficient production systems βš™οΈπŸŒ.

Presentation

Dr. Eduardo GarcΓ­a is a distinguished expert in industrial robotics and Industry 4.0 πŸ€–πŸ­, actively contributing to global conferences and forums. He has delivered impactful presentations at events like EVERii2020, PENTEO2020, and INNOVATION TALKS 2020, addressing smart manufacturing and supply chains πŸš€πŸ“¦. A sought-after speaker, he has shared insights at Advanced Factories, the Global Robot Expo, and the International Conference on Big Data, AI, and IoT πŸŒπŸ“Š. As a Master Professor at PEAKS BUSINESS SCHOOL, he fosters innovation in Industry 4.0. In 2023, he received the prestigious CEU Ángel Herrera Prize for outstanding research excellence πŸ†πŸ“–.

Research Focus

Dr. Eduardo GarcΓ­a Magraner’s research focuses on Industrial Internet of Things (IIoT) πŸ­πŸ“‘, smart manufacturing πŸ€–, and predictive maintenance πŸ”§βš™οΈ within Industry 4.0. His work includes real-time condition monitoring πŸ•’, virtual sensors πŸ“Š, and AI-driven automation πŸ€–πŸ” to enhance efficiency in industrial environments. Key contributions involve sub-bottleneck detection πŸš€, autonomous mobile warehouses πŸš—πŸ­, and manufacturing process optimization πŸ“ˆ using big data and simulation tools πŸ“‘πŸ’‘. His research advances smart factory management πŸ­πŸ’», ensuring reliability, reducing downtime, and boosting productivity. His innovations drive next-gen industrial automation πŸš€πŸ—οΈ for intelligent and self-optimizing manufacturing ecosystems.

Publication Top Notes