Assoc. Prof. Dr Reza Vatankhah Barenji
Dr.Reza Vatankhah Barenji received a Ph.D. degree in mechanical engineering. He is currently an Associate Professor with the Industrial Engineering Department Ankara, Turkey. He is the founder and director of Smart Engineering and Health research group. He has authored or co-authored more than 50 international journal papers. His research interests include AI Applications in manufacturing, Pharma4.0, Artificial intelligence applications in healthcare, blockchain applications, smart medical production, continuous medicine production, Cyber physical-based PAT, cloud-based RTRT, and Drug development life cycle integration. He has extensive experience in process optimization (e.g. FSW, FSP, EDM) using response surface methodology , and distributed manufacturing control systems. He is an active consultant for bio-mechatronic and Industry 4.0 projects in the pharmaceutical and automotive industries.
In 2020, Dr.Reza received the Tubitak research award of Turkey in the interdisciplinary research branch for his research conducted in the past five years, and for introducing the “Pharma 4.0” context. His pharma4.0 achievement (Cyber-physical-based PAT (CPbPAT) framework for Pharma 4.0) is the first paper in the context (Published: Aug15-2019) that was reported in the world acclaimed journal “International journal of pharmaceutics”.
He is teaching Industry 4.0 and AI applications related courses including; Industry4.0, and Advance Manufacturing system.
He is delivering Industry 4.0, blockchain technology workshops for wide ranges of applicants’ form industry.
He is an active adviser for industrial projects
Teaching and leadership experiences in Mechanical and Industrial engineering education
Albert Einstein - "If you can't explain it simply, you don't understand it well enough."
Teaching Philosophy and Responsibilities
My enthusiasm and commitment to teaching are equal to my commitment to research because I envision teaching and mentoring as an integral part of my career profile. During the past years, I have had the opportunity to advise and train people at various levels, leading to rewarding feedback for both my research and teaching work. I develop my teaching philosophy from my experience as a student, teaching assistant, lecturer, senior lecturer, and associate professor at three different universities (i.e. Tabriz Azad University, Eastern Mediterranean University, Hacettepe University) in two different languages English and Farsi.
When I was a graduate student, I had the chance to be a teaching assistant at Azad University of Tabriz for the workshop courses (i.e. Machining, Welding, Casting, Heat treatment). My duties were teaching each of the facilities to a group of students and give support to them when they should repeat the task. After graduation in MS, I started to teach the “engineering graphics” course to 150 students on laboratory assignments, giving laboratory tutorials, and grading reports and exams. For the next three semesters at the same department.
When I started my Ph.D., Eastern Mediterranean University offered me a full-time teaching assistant (2007-2011). During the period I taught Technical Drawing, Computer-Aided Engineering (CAE), Manufacturing Processes, Computer Integrated Manufacturing (CIM) courses. I was responsible to lecture, supplement courses materials, and assist students in understanding the principles of the courses. Meanwhile, I taught SolidWorks software in the MENG303 course. With excellent evaluations from students, the department offered me a lecturer position (2011-2014). Teaching is one of the most rewarding experiences that contributed to my passion for research. I learned a great deal about how to strengthen students’ understanding of the principles and practice, and supervise them to conduct engineering projects, and develop their own research interests. Besides teaching at the undergraduate course level, I was also invited to give guest lectures in some graduate courses on topics related to my research. In September 2014, I started to work as a senior lecturer and was then promoted to associate professor grade in the department of industrial engineering, Hacettepe University. In this department I found the opportunity to teach graduate courses and be a module leader to my own technical elective courses for undergraduate and graduate students.
As a researcher in the engineering field, it is my responsibility to play a role in the discovery of new knowledge. As a teacher, however, I believe an even greater responsibility is the perpetuation of the field and its current body of knowledge. Teaching allows me to promote the discipline to which I have devoted a significant portion of my life, and to show people the beauty of computation in terms of science, technology, and mathematics.
Description of Teaching Methodology
My teaching methodology is based on the foundation of my educational experience, which has given me the important knowledge that I would like to apply. This knowledge can be categorized into three parts.
Firstly, one of the important responsibilities of a teacher is to provide and categorized the necessary knowledge for the career and future of learners. Well-organized lecture notes with a carefully selected example may raise students’ interests and curiosity, and motivate their further studies. To explain complex concepts or solve challenging problems, I strive to use intuitive examples related to real-industrial issues to illustrate the basic laws under them. I always encourage students to focus on fundamental principles and deductive reasoning instead of simply memorizing the results. I also assign homework and evaluate students’ performance regularly, which reflects whether or not the presented materials are well absorbed. Meanwhile, I updated my lectures to my website to expose students to state-of-the-art technologies and future trends so that students can be well prepared for their future careers.
Second, the interaction commitments between students and the instructor are very important to make teaching and learning an interesting, rich, and rewarding experience for both parties. I like to stimulate the students through my enthusiasm for the course material since I believe enthusiasm is contagious in the class. I encourage students to actively participate in the teaching and learning process. By raising questions and arguments on a subject, I try to guide students on the right way to solve problems through in-class discussions and debates for arriving at suitable communication between student and teacher.
Third, but not less important, as a teacher I believe that one of the first things I have to learn for students is searching methods on the internet and how can share his/her knowledge on a suitable platform. For example, I and my students in the computer-aided engineering course have GrabCad accounts and always we share our works on this platform, this job not only improves the motivation of the students but also improves the searching knowledge of students, that very helps for a future career.
Teaching Improvement Activities
Every academic year, I am using the students’ assessment to improve my teaching capabilities and to expand the content of the course. Moreover, along with my research, I am trying to include the newly merged topics in my courses as examples in the supply chain management course in the last two weeks of the semester I am highlighting the improvements in the “Industry4.0” context.
Future Teaching Goals
According to my research and teaching background, my current teaching interests focus principally on digital manufacturing engineering and smart manufacturing, which embodies the following topics:
Strength of materials
Mechanical Engineering Design, and Drafting
Technical course (for BS, MS, and Ph.D.)
Computer Integrated Manufacturing (CIM)
New product development (NPD)
Information communication technology in manufacturing
Modern manufacturing process
My major interest in teaching is CAD/CAM, CAE, CIM, and intelligent manufacturing at both undergraduate and graduate levels. In addition to the standard classroom experience, I have considerable interest and experience in the use of 3 Axis CNC mill, 5 Axis CNC mill, 3 Axis CNC lathe, CMM, 3D printer, 3D scanner, and EDM machines to produce industrial/research dies and parts. In addition, I am an expert on using SolidWorks and PowerMILL CAM applications.
In particular, my vision for my teaching is to:
Provide the student with professional skills which are in line with his/her future role in design and manufacturing industries;
Develop students’ professional competence in evaluating and developing various technical aspects of the multi-disciplinary activities associated with design, manufacturing, and IT technologies;
Provide the student with the opportunity to demonstrate his/her ability to design and conduct a program of work aimed at providing solutions to an appropriate industrial problem.
The philosophy of group working is particularly beneficial in promoting a systematic attitude towards combining principles of different technologies to form an optimal design concept. It promotes maturity and responsibility through a planned team effort. Teaching gives me the ability to produce the results I desire most and helps me create values for others in the process.
My teaching experience
I have been teaching as an academic since 2006. My international teaching experience spans several countries
I have taught various courses for mechanical engineering, and Industrial engineering programs at undergraduate and post-graduate levels. The list can be found below:
Department of Industrial Engineering in Hacettepe University:
(The medium of instruction at Hacettepe University is English)
EMU102-Computer Aided Technical Drawing
EMU452-Applied Petri-Nets (Course module leader)
EMU401-System analysis and design I
EMU402-system analysis and design II
EMU466-Technology and Innovation Management
EMU453-Measurement and Instrumentations (Course module leader)
EMU643-Manufacturing Processes (Post Graduate)
EMU644-Virtual manufacturing (Post Graduate) (Course module leader)
EMÜ691 - Special Problems in Industrial Engineering (Post Graduate)
Department of Mechanical Engineering in Eastern Mediterranean University
(The medium of instruction at EMU is English)
Department of Mechanical Engineering, Azad University of Tabriz:
Strength of Material I
Numerical Control Machines
MY RESEARCH HISTORY
In my Ph.D. research, I develop a novel competency-based knowledge model for potential use by small and medium-sized enterprises. To justify the applicability of the model, we used the model on a flexible manufacturing system as the ontology of the RFID-enabled distributed control system and we also examined the approach on a decision support system. In the Smart Engineering and Health Systems (SEHS) research group we extend the competency-based knowledge model by modifying the negotiation mechanism. The modified model is used to solve the dynamic scheduling problem of the manufacturing flow line in a real-life production system. Later, a testing platform is developed to simulate the approach, and then the approach is used on a production line.
I have some works on the scheduling problem of the Flexible Robotic Cell (FRC). The mathematical model of the scheduling problem is developed and the model is numerically solved using different meta-heuristic methods. Later the approach is tested and under work in a cell located in Aksan company.
In 2017, I got the chance to be an academic adviser for Cloud Manufacturing (CMfg) project. We design and develop the first cloud manufacturing platform in Turkey. According to the feedbacks of the project; “Trust” was the main concern of the platform along with this concern, I used blockchain technology to address the trust issues of the CMfg platform. A distributed blockchain-based trust system for cloud manufacturing is developed. Started in 2021, as an adviser I am working on the first real-life cloud manufacturing platform project that is funded by Ankara Development Agency and coordinated. Recently aiming to provide adaptive interventions and content for the learners, we developed a blockchain technology-based metacognitive tool to store, and manage the self-regulation scores of the learners. This work is the first step in my research to work on the cognitive cyber-physical system context which I believe will be the main enabler of the next industrial revolution (i.e. Industry 5.0).
Besides, since 2015, I along with my graduate students are working on manufacturing process optimization context focusing on Friction Stir Welding (FSW) and Friction Stir Processing (FSP), Electric Discharge Machining (EDM), and coating processes using response surface, AI, and fuzzy logic methods. The aims in all the works were optimal parameters prediction of the processes and then through experimental methods examining the variance of the prediction to extract the real practical optimal process parameters. Almost all of the considered problems are real and industry-oriented.
Since 2018, I am giving consultancy services to drug companies. I was involved in several AI application-related works to optimize the process parameters in the pharmaceutical industry sadly none of these works are presented to publication due to publication restrictions of the companies. Later, I have collaborated with our pharmaceutical technology department to introduce and justify the potential applications of Cyber-Physical System (CPS) technology on drug manufacturing. The results of this work is the first paper on Pharma 4.0 context published by the international journal of Pharmaceutics and I was the main author for the paper. We develop a cyber-physical-based PAT framework for drug manufacturing. To justify and illustrate the application of our framework we used a part of the pharmaceutical manufacturing system shown in “ quality by design for ANDAs”. This work met the attention of many pharmaceutical technology researchers from academia and industry. In December 2019, I started to work with the center of pharmaceutical engineering at the University of Bradford to contribute to the Pharma4.0 field. In the first work with this center, the merging computerized technologies related literature such as artificial intelligence, machine learning, deep learning, Internet of things, cloud computing, and cyber-physical technology and their potential fruits, applications, and capabilities in clinical research is reviewed and then by overlapping these technologies we propose an integral Pharma 4.0 perspectival framework for clinical trials. We foresee the possible impacts of Pharma 4.0 on three key contributors to clinical trials (i.e. sponsors, CROs, and regulators). In the second work, the literature related to digital technology applications in all stages of the drug development life cycle is used to develop the Pharma 4.0 ecosystem. The result of this work is accepted to publication as a book chapter in “ Handbook of Smart Materials, Technologies, and Devices - Applications of Industry 4.0”. In the third work, we proposed a blockchain-based quality management system for the clinical trial stage of drug development. In this work quality by design approach is employed to boost the safety of the participants and blockchain ledgers are used to protect the sensitive data of the project. In our recent work, in the hot-melt extruder, we are using deep learning to predict the outcome of the solid dispersion to overcome limitations associated with the poor solubility of an active pharmaceutical ingredient during drug development.
Over the next five years, I wish to continue my carrier and work in the multi-disciplinary field of AI application in manufacturing, process optimization, and drug production. My particular focus will be on pharmaceutical process optimization. I wish to collaborate with some organizations to find the chance to implement our newly developed blockchain-based quality management system in a real-life project aiming to make the system much better and applicable. I believe if the blockchain-based quality management system finds the chance to test on at least two projects it will be a good starting point to develop a blockchain-enabled cyber-physical-based quality management system for drug development. This system will be able to monitor the health issue of participants during the trial conduction before and after drug administration and using deep learning will be able to act as an awareness system to the research centers, sponsors, and regulators. Using this system which will be remotely available from any company in the world, the quality of the drug development will be raised by well protecting the participants and data integration.
1. University project, Agent-based scheduling system for SMEs (2009-2011). Budget: $50,000, Position: researcher.
2. Industry Project, Iran Pump; Pump impeller reengineering(2013-2014) Budget: $45,000, Position: PI.
3. Industry project, Archelik,;Dynamic rescheduling (2014-2017) Budget: $36,600, Position: PI
4. H2020 project, SME Phase2, Sustonable ; Sustainable Artificial Stones (2019-2021) Budget: MEURO 2.2, Position: Academic adviser
5. KOSGEB, Level Technology , Cloud manufacturing Platform (2019-2020) Budget: $113,000 Position: Academic adviser
6. KOSGEB, Level Technology , QR chef (2020-2022) Budget: $56,000 Position: Academic adviser
7. Four Industry Projects, Manufacturing Process optimization (2015-2020) 4 Budget:$149,300, Position in all: PI.
8. ADA , SME digitalization (2021-2022) Budget:$598,800 Position: Academic adviser