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Intelligent Inspection for Digital Manufacturing* (24 hours)
In Industry 4.0, digital technologies make manufacturing more agile, flexible and responsive to the customers. Nowadays, it is able to have a smart and digital factory where advanced technologies (IoT, 5G, Machine Learning, Deep Learning, etc.) work together to optimise the manufacturing process and improve customer satisfaction.
Machine vision systems together with automated image-based analysis offer manufacturers a certain level of assurance in product quality inspection. For inspection in quality assurance process, deep learning turn out to be a game changer as it is powerful in the way of mimicking human intelligence to distinguish anomalies in complex patterns.
About the Programme
Participants will become familiar with the principles of deep learning technologies. The process to develop a deep learning model which work as expected will be described in the course. Typical applications using deep learning technologies and deep learning research directions will be discussed and explained.
This course consists of 3 full-day sessions covering hands-on session using both commercial software and open source networks for developing deep learning models. This would enhance the understanding of deep learning principles. At the end of the course, the participants will be able to develop deep learning models for their potential inspection applications.
Who Should Attend
This course is relevant for business owners and management with intention to have a first understanding of or to develop capability of deep learning for industry intelligent inspection applications.
Moreover, it is applicable to Individuals and staff who are currently employed or wish to be employed in visual inspection/image processing related fields, seeking to have a first understanding of the deep learning technologies.
A typical candidate profile could be a/an:
- Quality Control Manager/Engineer
- Machine Learning Engineer
- Production Supervisor/Manager
What our trainees say
Good exposure to AI technology and how this powerful tool benefits the manufacturing industry.
Mr Pua Shun Jie,
Participant from Oct 2024 intake
A good insight of AI for beginners.
Mr Tan Hua Hong,
Participant from Jul 2024 intake
About the trainers
Dr Wang Zhenbiao, 
Mr Simon Chin, 
Mr Naveen Gnanaprakasam, Dr Wang Zhenbiao
Mr Simon Chin
Mr Naveen Gnanaprakasam
Contact Us
- For technical enquiries, please contact:
Dr WANG Zhenbiao,
Email: wang_zhenbiao@ARTC.a-star.edu.sg
- For general enquiries, please contact:
Ms Maria Carolina Vergo,
Email: maria_carolina_vergo@ARTC.a-star.edu.sg
Registration
- Please register for this course through our Course Registration Form for Public Classes.
- For the first question, please select "Modular Programmes (Standalone Modules)".
- Applicants will be placed on our waiting list if the course does not have an upcoming scheduled intake.
- Once the next intake is confirmed to commence, SIMTech will contact the applicants to share the class information.
Schedule
Module | Skills Course Reference Number | Next Intake(s)'s Training Period
(Click on the dates to view its schedules) | Registration Status |
| TGS-2023021043 |  21 May 2025 - 23 May 2025The May 2025 intake is postponed. We will publish a new schedule soon. |
Note: SIMTech and ARTC reserve the right to change the class/schedule/course fee or any details about the course without prior notice to the participants.
Announcement:
- From 1 Oct 2023, attendance-taking for SkillsFuture Singapore (SSG)'s funded courses must be done digitally via the Singpass App. More information may be viewed here.
: Full day
: Morning
: Afternoon
: Evening- View the full list of modular programmes offered by SIMTech and ARTC.
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