Bulent Koc | Digital Lean System | Best Researcher Award

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Dr. Bulent Koc | Digital Lean System | Best Researcher Award

Researcher | Istanbul Technical University | Turkey

Dr. Bulent Koc is a Ph.D. candidate in Textile Engineering at Istanbul Technical University with more than two decades of experience in the apparel and textile industry. His expertise lies in integrating lean production principles with digital transformation strategies to enhance efficiency and sustainability in garment manufacturing. Throughout his career, he has worked in diverse roles, from production planning and product management to certification and digital productivity systems. His current research focuses on designing sustainable digital lean models for ready-made garment enterprises, particularly in labor-intensive sewing operations. He has collaborated with multiple organizations, implementing projects on workflow optimization, efficiency enhancement, and the use of real-time Process Monitoring Devices (PMDs). By bridging academic research with industrial applications, Koc contributes significantly to advancing operational excellence and competitiveness in the textile and apparel sector. His work underscores the potential of digital lean transformation as a sustainable solution for future manufacturing systems.

Professional Profile

Scopus

Education

Dr. Bulent Koc pursued his academic journey entirely at Istanbul Technical University, specializing in Textile Engineering. He earned his B.Sc. in Textile Engineering, where he built a foundation in fabric production, apparel processes, and material technology. He then completed his M.Sc. in Textile Engineering, focusing on production management and optimization in knitted garment manufacturing. His master’s thesis explored methods to enhance efficiency, cost-effectiveness, and lean principles in textile production environments. Currently, he is a Ph.D. candidate in the same department, expected to complete. His doctoral research centers on lean production and the development of sustainable digital lean models tailored for the ready-made garment industry. This work combines advanced lean management techniques with Industry, including real-time production monitoring, digital line balancing, and sustainability frameworks. Through this academic progression, Koc has developed a strong balance of theoretical knowledge and practical industrial insights in textile engineering.

Experience

Dr. Bulent Koc has built extensive professional experience in textile and apparel manufacturing since. He began as Production Planning Manager at Serfil Yarn and Fabric Factory, where he led efficiency projects and factory setup operations. Later, as Product Group Leader at Tars International Trade Ltd., he managed men’s wear collections and coordinated procurement. At Koton Mensucat, he advanced as a Product Manager, overseeing procurement and R&D in fabric development. he worked at Certurk Certification and Inspection Services, managing professional qualification certifications and training in textiles. His latest role was as Productivity Management Specialist at ITM Techsoft, where he developed digital lean systems, real-time data integration, and line balancing algorithms. Across his career, Koc has successfully combined lean manufacturing principles with technology-driven innovations. His projects consistently targeted productivity, sustainability, and competitiveness, making him a key contributor to both industry practices and applied textile engineering research.

Research Focus

Dr. Bulent Kocs research is centered on the integration of lean production systems with digital transformation in apparel manufacturing. His work focuses particularly on labor-intensive sewing operations, where workflow optimization and productivity are critical. He explores how real-time Process Monitoring Devices (PMDs) can track lean metrics, improve line balancing, and reduce inefficiencies. By combining lean principles with Industry such as digital data management and automation, his research offers scalable frameworks for sustainable production. He also examines the role of digital lean models in enhancing overall equipment effectiveness (OEE), minimizing waste, and promoting eco-friendly manufacturing practices. Field-based studies conducted in collaboration with Turkish textile companies validate his approaches and demonstrate measurable improvements in efficiency and sustainability. Kocs research bridges theory and practice, offering both academic contributions and real-world industrial solutions. His goal is to transform digital lean systems into a long-term driver of competitiveness in the apparel sector.

Awards and Honors

Throughout his career, Bulent Koc has been recognized for his contributions to lean manufacturing and digital transformation in apparel production. His applied research has been acknowledged at academic and industrial platforms, particularly in the field of textile engineering innovation. He has collaborated on projects supported, which emphasize efficiency, sustainability, and competitiveness in textile SMEs. His industry-driven lean transformation projects were recognized for advancing operational excellence, including notable work in digital line balancing and real-time production monitoring. He has been invited to share his expertise at professional seminars and academic discussions on lean systems in apparel manufacturing. In addition, his involvement in mechanics-related awards and conferences reflects his interdisciplinary contributions to engineering-focused production methodologies. These honors highlight his role as a bridge between academic research and industrial practice, reinforcing his reputation as an innovator in digital lean textile systems.

Publication Top Notes

Conclusion

Dr. Bulent Koc demonstrates potential as a researcher in lean production systems and digital transformation in apparel manufacturing, with a strong practical background and research focus. His industry projects and contributions to operational excellence are notable, and his research has the potential to make a significant impact in the industry. With further development of his publication record and international collaboration, he could become a strong candidate for the Best Researcher Award.

Assoc. Prof. Dr. Nasrollah Bani Mostafa Arab | manufacturing processes | Best Faculty Award

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Assoc. Prof. Dr. Nasrollah Bani Mostafa Arab | manufacturing processes | Best Faculty Award

 Assoc.Prof. at  Shahid Rajaee Teacher Training University , Iran.

Nasrollah Bani Mostafa Arab is an esteemed Associate Professor at the Faculty of Mechanical Engineering, Shahid Rajaee Teacher Training University, Tehran, Iran 📚. With over 30 years of teaching experience and a strong research background in welding processes, manufacturing processes, and composite materials, he has established himself as a leading expert in his field 🔩.

Professional Profile

scholar

🎓 Education

– *PhD in Mechanical Engineering*: IIT Delhi, India (1993) 🎓– M.Tech. in Mechanical Engineering (Production): B.H.U., India (1988) 🎓– B.E. in Mechanical Engineering: R.E.C., Srinagar, India (1985) 🎓

💼 Experience

– *Associate Professor*: Faculty of Mechanical Engineering, Shahid Rajaee Teacher Training University, Tehran, Iran 📚– *Teaching Experience*: Over 30 years of experience in teaching mechanical engineering courses 📚– *Research Experience*: Extensive research experience in welding processes, manufacturing processes, and composite materials

🔬 Research Interests

Nasrollah Bani Mostafa Arab’s research focuses on welding processes, manufacturing processes, and composite materials 🔩. His work involves investigating the properties and applications of various materials and developing new manufacturing techniques.

🏅 Awards

– *Published over 60 journal and conference papers*: Demonstrating his expertise and contributions to the field of mechanical engineering 📄– *Translated book*: “Advanced machining processes” from English to Persian 📚– *Authored book*: “Technical English for students of production and manufactur

📚Top Noted  Publications

1. Effects of friction stir welding process parameters on appearance and strength of polypropylene composite welds 📄
GH Payganeh, NBM Arab, YD Asl, FA Ghasemi, MS Boroujeni
Int. J. Phys. Sci 6 (19), 4595-4601, 2011

2. Optimization of process parameters for friction stir lap welding of carbon fibre reinforced thermoplastic composites by Taguchi method 📊
H Ahmadi, NB Mostafa Arab, FA Ghasemi
Journal of Mechanical Science and Technology 28, 279-284, 2014

3. Optimization of welding parameters for weld penetration in FCAW 🔩
NB Mostafa, MN Khajavi
Journal of achievements in materials and manufacturing engineering 16 (1-2), 2006

4. Influence of pin profile on quality of friction stir lap welds in carbon fiber reinforced polypropylene composite 🔍
H Ahmadi, NBM Arab, FA Ghasemi, RE Farsani
International Journal of Mechanics and Applications 2 (3), 24-28, 2012

5. Effects of drilling parameters on delamination of glass-epoxy composites 🌀
FA Ghasemi, A Hyvadi, G Payganeh, NBM Arab
Australian Journal of Basic and Applied Sciences 5 (12), 1433-1440, 2011

6. Mechanical and metallurgical properties of pulsed neodymium-doped yttrium aluminum garnet laser welding of dual phase steels 🔩
M Hazratinezhad, NBM Arab, AR Sufizadeh, MJ Torkamany
Materials & Design 33, 83-87, 2012

7. The systematic parameter optimization in the Nd: YAG laser beam welding of Inconel 625 🔍
MR Jelokhani-Niaraki, N B. Mostafa Arab, H Naffakh-Moosavy, …
The International Journal of Advanced Manufacturing Technology 84, 2537-2546, 2016

8. Application of response surface methodology for weld strength prediction in laser welding of polypropylene/clay nanocomposite 📊
MR Nakhaei, NB Mostafa Arab, G Naderi
Iranian Polymer Journal 22, 351-360, 2013

9. Numerical and experimental investigation of defects formation during friction stir processing on AZ91 🔍
H Agha Amini Fashami, N Bani Mostafa Arab, M Hoseinpour Gollo, …
SN Applied Sciences 3, 1-13, 2021

10. Experimental study on optimization of CO2 laser welding parameters for polypropylene-clay nanocomposite welds 🔩
MR Nakhaei, NB Mostafa Arab, G Naderi, M Hoseinpour Gollo
Journal of Mechanical Science and Technology 27, 843-848, 2013

 

Conclusion

Dr. Nasrollah Bani Mostafa Arab’s research experience, publication record, teaching experience, and book publications make him a strong candidate for the Best Researcher Award. With some further emphasis on international collaboration and interdisciplinary research, Dr. Arab could further solidify his position as a leading researcher in his field.

Sabum Jung | Smart factory | Best Researcher Award

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Mr. Sabum Jung | Smart factory | Best Researcher Award

Research engineer, Lg energy solution,South Korea

Sabum Jung is a seasoned Data Scientist and Machine Learning Engineer with over 23 years of expertise in predictive modeling, deep learning, and AI-driven optimization. His career spans LG Energy Solution, SK Holdings, and LG Production Engineering Research Institute, where he pioneered AI applications in high-tech manufacturing, including semiconductor, battery, and display industries. A former Military Intelligence Analyst for the U.S. Army, he has authored research papers and books on AI, machine learning, and Industry 4.0. Fluent in English, Korean, and Japanese, he continues to drive AI innovations in industrial applications.

Profile

🎓 Education

Sabum Jung holds a B.A. (3.9/4.5) and an M.S. (4.2/4.5) in Industrial Engineering from Sung Kyun Kwan University, South Korea. His academic journey focused on advanced analytics, AI-driven optimization, and industrial process improvements. His research contributions in artificial intelligence, reliability engineering, and digital transformation have shaped his expertise in machine learning, deep learning, and predictive modeling, positioning him as a leader in AI applications for manufacturing and industrial systems.

💼 Experience

Currently a Data Scientist at LG Energy Solution, Sabum Jung leads AI-driven innovations in virtual metrology, predictive maintenance, and defect analysis. Previously at SK Holdings, he optimized renewable energy predictions, semiconductor material discovery, and AI-powered industrial operations. His 20-year tenure at LG Production Engineering Research Institute saw groundbreaking work in machine learning for smart appliances, battery systems, and industrial automation. His early career as a Military Intelligence Analyst in the U.S. Army honed his analytical prowess, setting the foundation for his AI-driven problem-solving approach.

🏆 Awards & Honors

Sabum Jung has been recognized for his contributions to AI, machine learning, and industrial automation. His accolades include leadership in AI-driven manufacturing optimization, predictive maintenance, and reinforcement learning applications. He has received industry recognition for his research and innovation in deep learning, active learning, and process optimization in high-tech sectors, further cementing his influence in AI-driven industrial advancements.

🔬 Research Focus:

Sabum Jung specializes in AI applications for high-tech manufacturing, focusing on predictive maintenance, virtual metrology, and defect detection. His research spans deep learning, reinforcement learning, and AI-driven industrial process optimization. Notable contributions include renewable energy prediction, semiconductor material discovery, and advanced statistical modeling. His expertise in machine learning has been instrumental in developing AI solutions for smart manufacturing, Industry 4.0, and digital transformation.

Publications

Recent progress of LG PDP: High efficiency & productivity technologies Citations1

Conclusion

Sabum Jung is a strong candidate for the Best Researcher Award, given his vast industry experience, research excellence, and technological contributions to AI and machine learning in manufacturing. Enhancing academic collaborations and increasing research dissemination could further elevate his impact and recognition.