Webinar details
Industrial automation is rapidly evolving from traditional control systems into intelligent, connected, and data-driven industrial ecosystems. This webinar provides a practical introduction to how modern industrial systems are being transformed through the integration of sensors, PLCs, SCADA/DCS, industrial communication networks, artificial intelligence, edge AI, and digital twins.
The session will begin by explaining the foundations of industrial automation and how data is collected from machines, processes, and control systems. It will then explore how machine learning can be used to support predictive maintenance, quality monitoring, fault detection, process optimization, and smarter industrial decision-making.
A key focus of the webinar will be digital twins: virtual representations of physical assets, machines, or processes that are connected to real-time industrial data. The webinar will explain how digital twins can support monitoring, prediction, simulation, optimization, and decision support in smart manufacturing and other industrial environments.
The presentation will also discuss the importance of cybersecurity, safety, reliability, and trust as industrial systems become more connected and intelligent. The webinar is designed for engineers, technical professionals, and prospective postgraduate students who want to understand the future direction of industrial automation and the skills required to work in AI-enabled industrial environments.
- The webinar will be recorded and will be sent out to registered attendees afterwards.
- A certificate of attendance will be provided to attendees who request one near the end of the live webinar session.
- Please note: the time stated on this event is in UTC. You will need to convert this to your own time zone.
Key takeaways from this webinar
- Understand how industrial automation is evolving from traditional control systems to smart, connected, and data-driven systems.
- Learn how sensors, PLCs, SCADA/DCS, and industrial communication networks form the foundation of modern industrial automation.
- Explore how artificial intelligence and machine learning are being applied in predictive maintenance, quality monitoring, anomaly detection, and process optimization.
- Understand the role of edge AI in enabling fast, local, and real-time decision-making in industrial environments.
- Learn what digital twins are and how they connect physical industrial systems with virtual models for monitoring, prediction, and optimization.
- Recognize the importance of cybersecurity, safety, reliability, and trust in AI-driven industrial automation.
- Identify the key technical skills future automation engineers need, including instrumentation, control systems, industrial data, machine learning, communications, and systems thinking.
Related courses
This webinar/topic relates to our school of Industrial Automation and is particularly found in the following courses:
- Professional Certificate of Competency in Digital Twins and Simulation Monitoring
- Professional Certificate of Competency in Allen Bradley Controllogix / Logix5000 PLC Platforms
- Professional Certificate of Competency in Control Valve Sizing, Selection and Maintenance
- Professional Certificate of Competency in Programmable Logic Controllers (PLCs) & SCADA Systems
- 52886WA Advanced Diploma of Industrial Automation Engineering
- Graduate Certificate in Industrial Automation Engineering
- Graduate Certificate in Industrial Automation and Machine Learning
- Bachelor of Science (Industrial Automation Engineering)
- Master of Engineering (Industrial Automation)
- Master of Engineering – Applied Research (Industrial Automation)
About the presenter
Dr. Mostafa Jamshidian, Senior EIT Lecturer
Dr. Mostafa Jamshidian is a Senior Lecturer at the Engineering Institute of Technology, with more than 10 years of academic teaching experience and many years of industry-focused research and development experience. He has a strong background in engineering education, computational mechanics, data-driven engineering, digital manufacturing, and healthcare engineering.
He holds a PhD in Mechanical Engineering from the National University of Singapore, a Master of Education in Tertiary Teaching from The University of Western Australia, and Fellowship of the Higher Education Academy (FHEA). Dr. Mostafa has research experience at the Singapore Agency for Science, Technology and Research (A*STAR), where he contributed to applied projects with major international industry partners including Boeing, Johnson & Johnson, TE Connectivity, and Asahi Glass.
His work has addressed real-world engineering challenges across advanced materials, manufacturing, computational simulation, and industrial processes. His recent healthcare-related work has involved collaboration with major hospitals in Perth and Europe on projects in computations for medicine, AI in healthcare, and patient-specific biomechanics. His teaching and professional practice are strongly informed by industry engagement, applied research, and the translation of advanced engineering methods into practical solutions.