Revolutionizing Dairy Production: A Comprehensive Analysis of Industry 4.0-based Optimization Strategies in Yogurt Filling Systems

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Published: Dec 30, 2025

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Asad Ali
Engineering Management Program, Department of Industrial Engineering, University of Engineering and Technology, Peshawar (Sub Campus Swat), Pakistan.
https://orcid.org/0009-0000-6475-0183
Razaullah Khan
Engineering Management Program, Department of Industrial Engineering, University of Engineering and Technology, Peshawar (Sub Campus Swat), Pakistan.
https://orcid.org/0009-0002-0046-5003
Bashir Salah
Department of Industrial Engineering, College of Engineering, King Saud University, Saudi Arabia.
https://orcid.org/0000-0003-2709-760X

Abstract

This study introduces a unique approach to yogurt and flavour-filling systems, presenting Case IV and a circular conveyor belt configuration. Unlike traditional linear setups, Case-IV revolutionizes yogurt and flavour-filling processes by optimizing processing time and space usage. The innovative system incorporates a Fanuc LR Mate 200ic robotic arm, NFC technology, and diverse conveyor belts, enhancing automation and energy efficiency, which are critical aspects of Industry 4.0. A mathematical model is developed, encompassing cup filling and shared movement along the conveyor belt. The model's results are compared with established methodologies, pushing the boundaries of efficiency and promoting sustainable production. Comparative analysis demonstrates the system’s superior performance, showcasing its flexibility and adaptability to evolving production needs.

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How to Cite
Ali , A., Khan, R., & Salah, B. (2025). Revolutionizing Dairy Production: A Comprehensive Analysis of Industry 4.0-based Optimization Strategies in Yogurt Filling Systems. Journal of Workplace Behavior, 6(2), 29–48. Retrieved from https://charisma-jwb.com/index.php/jwb/article/view/293
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Vol. 6 No. 2 (2025): Journal of Workplace Behavior (JoWB)
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Articles
Author Biographies

Asad Ali , Engineering Management Program, Department of Industrial Engineering, University of Engineering and Technology, Peshawar (Sub Campus Swat), Pakistan.

Engr. Asad Ali is a Mechanical Engineer who earned his B.Sc. degree from UET Peshawar, Pakistan. He also completed a degree in the MS Engineering Management program at the UET Peshawar, Swat Sub-Campus. His academic focus and research interests lie in Operations Research and Supply Chain Network Optimization. He is currently pursuing doctoral studies in Industrial Engineering in the United States.

Razaullah Khan, Engineering Management Program, Department of Industrial Engineering, University of Engineering and Technology, Peshawar (Sub Campus Swat), Pakistan.

Engr. Dr. Razaullah Khan is a Mechanical and Industrial Engineer from Pakistan with more than 15 years of academic and industrial experience. He holds a PhD in Industrial Engineering from UET, Peshawar, Pakistan (2018). His expertise includes Operations Research, scheduling, sequencing, supply chain network design, and optimization modeling. He has authored more than 40 research articles with around 1000 citations and an i10-index of 20. Dr. Razaullah has contributed to diverse domains, including manufacturing optimization, cold chain logistics, CCS-related logistics, and Industry 4.0-based production systems. He has worked as an Assistant Professor, Lecturer, QC Engineer, and Technical Instructor. His research emphasizes optimization-driven decision support for industrial and crisis logistics systems. He has attended international IEEE conferences in South Korea, Singapore, and Saudi Arabia.

Bashir Salah, Department of Industrial Engineering, College of Engineering, King Saud University, Saudi Arabia.

Prof. Dr. Bashir Salah is a Professor of Industrial Engineering at King Saud University, Riyadh, Saudi Arabia, specializing in automation and control, industrial facility planning, and smart manufacturing systems. He holds a B.Sc. in Mechanical Engineering, an M.Sc., and a PhD in Transportation and Logistics from the University of Duisburg-Essen, Germany. He completed advanced professional training in Mechatronics under the invitation of the German Government. Prof. Salah has contributed to Industry 4.0, CIM, PLC automation, and reverse logistics, with applications in customized production systems. He has authored numerous high-impact journal and conference publications in English and German. He was recognized among Stanford University’s Top 2% Scientists (2024). He has received prestigious awards, including a DAAD scholarship and 1st place at IEOM Rabat 2017. He served in academic leadership roles, including Vice Dean for Technical Affairs at the Advanced Manufacturing Institute. He led funded national research projects as Principal Investigator with a completed project budget of 2 million SAR. He actively supports thesis supervision, professional consultation, and smart automation-driven logistics research.