Advanced Digital Smart Manufacturing Lab
Research Field
Dr. Hariyanto Gunawan received his Ph.D. and M.Sc. in Mechanical Engineering from Chung Yuan Christian University (CYCU), Taiwan. His academic training and professional career have consistently focused on the integration of smart manufacturing, artificial intelligence, precision manufacturing, and Industry 4.0 technologies. He has over 20 years of experience spanning academia, industrial research, and international collaboration. He currently serves as an Assistant Professor in the Department of Mechanical Engineering at CYCU. In addition, he is the President of the ACMT Indonesia Smart Manufacturing Alliance (ACMT ISMA) and the Chairman of the International Faculty and Research Staff Club (IFRSC) at CYCU, where he actively promotes cross-border industry–academia cooperation and international talent cultivation.
As a Principal Investigator, Dr. Gunawan has successfully led and participated in numerous government-funded and industry-sponsored projects, including those supported by the National Science and Technology Council (NSTC) and the Ministry of Economic Affairs (MOEA) of Taiwan. He has collaborated extensively with industrial partners such as Symtek Automation Asia, SHL Medical, Delta Electronics, and China Motor Corporation. Dr. Gunawan has published over 50 academic papers in SCI journals and international conferences, holds U.S. and Taiwan patents, and continues to actively advance international industry–academia collaboration, particularly between Taiwan and Indonesia.
The Advanced Digital Smart Manufacturing Laboratory is dedicated to research in smart manufacturing and Industry 4.0 technologies, integrating artificial intelligence, Internet of Things (IoT), real-time monitoring, precision machining, robotics, and AR/MR-based smart factory applications. The laboratory focuses on data-driven machining optimization, intelligent machine tool monitoring, CNC system integration, and cyber–physical manufacturing systems, with the goal of enhancing manufacturing accuracy, operational efficiency, energy performance, and overall system intelligence, while actively supporting industry–academia collaboration and advanced talent cultivation.
- Smart Manufacturing & Industry 4.0: Cyber–physical production systems, digital transformation, and intelligent factory integration.
- Artificial Intelligence for Machining Processes: AI/ML/GenAI-based prediction and optimization of surface roughness, accuracy, energy consumption, and toolpath efficiency.
- Real-Time Monitoring & Intelligent Sensing: Vibration, cutting condition, and abnormality detection using IoT sensors and CNC data acquisition.
- Robotics & Intelligent Automation: Robotic grasping, positioning accuracy evaluation, and automation system integration for smart manufacturing.
- Machine Vision & Visual Recognition: Vision-based inspection and object detection for manufacturing automation.
- AR/MR-Based Smart Factory Applications: Smart-glasses-based real-time monitoring, human–machine interaction, and mixed-reality factory visualization.
- 2025 Bronze Medal “Smart Manufacturing Paper Award”, Symtek Automation Asia Co. Ltd
- 2024 Outstanding Contribution Award, ACMT
- 2024 Bronze Medal “Smart Manufacturing Paper Award”, Symtek Automation Asia Co. Ltd
- 2023 Silver Medal “Smart Manufacturing Paper Award”, Symtek Automation Asia Co. Ltd
- 2022 Second Prize Interdisciplinary Cross Program, CYCU
- 2021 Outstanding paper “Smart Manufacturing Paper Award”, Symtek Automation Asia Co. Ltd
- 2017 First Prize Paper Award “IEEE International Conference on Applied System Innovation”
- 2014 The Phi Tau Phi Scholastic Honor
- 2014 Bronze Medal, Taipei International Invention Show and Technomart
- 2013 Outstanding Contribution, Chung Yuan Christian University
- 2012 Silver Medal and Bronze Medal, Taipei International Invention Show and Technomart
- 2012 Outstanding Contribution, Youth Development Administration, Ministry of Education, Taiwan
- 2011 Outstanding Contribution, Youth Development Administration, Ministry of Education, Taiwan
M.Sc and Ph.D in Mechanical Engineering, Chung Yuan Christian University, Taiwan.
Job Description
- Assist in the development and integration of cyber–physical production systems, including machine–sensor connectivity, data acquisition, and digital factory modeling.
- Support digital transformation projects by implementing IoT platforms, analyzing production data, and evaluating intelligent factory integration strategies.
Preferred Intern Educational Level
- Senior undergraduate, Master’s, or PhD student in Mechanical Engineering, Industrial Engineering, Data Science, Electrical Engineering, or Computer Science.
Skill sets or Qualities
- Knowledge of machine learning (XGBoost, neural networks, etc.)
- Python programming (TensorFlow / PyTorch / Scikit-learn)
- C# programming
- Understanding of manufacturing systems, CNC machining fundamentals
- Statistical analysis and data visualization skills
- Analytical thinking and problem-solving ability
- Interest in digital transformation and smart factories
- Strong research motivation
- Hands-on laboratory skills
Job Description
- Develop vision-based inspection systems for defect detection and object recognition in manufacturing environments.
- Train and deploy deep learning models (e.g., YOLO, CNN) for industrial image analysis and quality inspection.
Preferred Intern Educational Level
- Senior undergraduate, Master’s or PhD student in Mechanical, Electrical, Robotics, or Mechatronics Engineering.
Skill sets or Qualities
- Basic robotics and kinematics knowledge
- Familiarity with Industry or collaborative robots (e.g., FANUC, TM, UR)
- Programming (ROS, Python, PLC)
- Computer vision and deep learning knowledge
- Python (OpenCV, PyTorch, TensorFlow)
- Image preprocessing and dataset labeling experience
- Strong research motivation
- Problem-solving and system integration mindset
- Logical thinking and algorithm development ability
- Hands-on laboratory skills