Industrial Artificial Intelligence In Manufacturing* (24 Hours)

*This is a non-WSQ module.
Industrial AI
  • This programme is in collaboration with the Sectoral AI Centre of Excellence for Manufacturing (AIMfg).
  • This module is one of five in the AI in Manufacturing (AIM) programme. Complete all five AIM modules to qualify for an exemption from one Post-Diploma Certificate (PDC) requirement of the Specialist Diploma in Smart Manufacturing at Ngee Ann Polytechnic. Find out more.

Introduction

Artificial Intelligence (AI) in manufacturing is not the same as AI in other sectors. Industrial environments demand high accuracy, reliability, and traceability, and AI must operate within complex, tightly integrated production and enterprise systems.

Organisations must move beyond point solutions toward data-driven and increasingly AI-driven autonomous manufacturing. This requires readiness across data, system integration, workforce capability, and scalable implementation.

This Industrial AI for Manufacturing programme addresses the need for applied and practical capabilities of AI within the manufacturing sector. Participants will gain practical knowledge and applied skills to explore industrial AI technologies, apply AI methods to real-world manufacturing use cases, and develop deployment approaches that support scaling.

About This Programme

This programme equips professionals with practical knowledge to understand and apply AI in manufacturing contexts.

Participants will learn how to:

  • Understand key AI foundations relevant to manufacturing applications
  • Identify viable industrial AI opportunities
  • Design predictive shopfloor analytics workflows using data mining methods
  • Apply agentic and generative AI concepts in manufacturing contexts
  • Link AI use cases across manufacturing production and enterprise layers
The programme combines conceptual understanding with structured case-based application aligned to realistic manufacturing scenarios.

Who Should Attend

This programme is intended for leaders, engineers, and transformation practitioners who are responsible for identifying, designing, and deploying industrial AI solutions within a manufacturing environment. Suitable participants include:

  • Operations and Production Managers
  • Process, Quality and Maintenance Engineers
  • Manufacturing Systems / Automation Engineers
  • Data and Analytics Professionals in Manufacturing
  • Digital Transformation and Industry 4.0 Leads
  • Technical Managers responsible for AI initiatives

It is relevant for organisations in precision engineering, electronics, semiconductor, process and discrete manufacturing sectors seeking to move from AI experimentation toward integrated and scalable AI deployment.

Course Outline

This programme adopts the Learn-Practise-Implement™ (LPI™) pedagogy where participants learn the main concepts in deep learning, practise their skills through exercises, and implement solutions to real-world business problems.

Key focus areas or applications:

  • AI Foundations relevant to manufacturing
  • Predictive shopfloor analytics and data mining workflow
  • Operations integration and enterprise linkages
  • Framing viable industrial AI use cases
  • Agentic and generative AI in manufacturing (RAG, Copilots, Agents)
  • AI transformation, workforce upskilling

Upon Completion Of This Course

Participants will be awarded with a Certificate of Attendance (COA) by SIMTech and/or ARTC if they meet the following criteria:

  • Achieve at least 75% course attendance;
  • Take all assessments; and
  • Pass the course.

Note: Trainees will have to bear the full course fee upon failure to meet either one of the criteria.

Pre-Requisites

  • Applicants should possess a degree in any discipline or a diploma with a minimum of 3 years of related working experience.
  • Applicants who do not have the required academic qualifications are still welcome to apply, but shortlisted candidates may be required to attend an interview for special approval.
  • Proficiency in written and spoken English.
  • Familiar with the fundamentals of machine learning.
  • Comfortable reading and writing code.
  • Ideally have experience with Python programming language.

Full Course fee

The full course fee for this course is $2,400 before funding and prevailing GST.

Nett Course Fee

International
Participants		 Singapore Citizens aged 39 years and below, Singapore Permanent Residents and LTVP+ Holders Employer-sponsored and self-sponsored Singapore Citizens aged 40 years and above
(MCES) ²		 SME-sponsored local employees (i.e Singapore Citizens, Singapore Permanent Residents and LTVP+ Holders) (ETSS) ¹
$2,616 $784.80 $304.80 $304.80
All fees are inclusive of GST 9%.
Please note that fees and funding amounts are subject to change.
Long Term Visit Pass Plus (LTVP+) Holders

The Long Term Visit Pass Plus (LTVP+) scheme applies to lawful foreign spouses of Singapore Citizens with 
(i) at least one Singapore Citizen child or are expecting one from the marriage, or at least three years of marriage, and
(ii) where the Singapore Citizen sponsor is able to support the family.

All LTVP+ holders can be identified with their green visit pass cards, with the word 'PLUS' printed on the back of the card.
¹ Enhanced Training Support For Small & Medium Enterprise Scheme (ETSS)

The ¹Enhanced Training Support for Small & Medium Enterprises scheme (ETSS) supports company-sponsored participants with up to 90% course fee subsidies.  To qualify, both the employers and trainees must meet the following eligibility criteria.

  • Eligible Small & Medium Enterprises (SMEs) must meet all of the following conditions:
    • Registered or incorporated in Singapore
    • Employment size of not more than 200 employees, or annual sales turnover of not more than $100 million

  • SME-sponsored trainees must meet all of the following:
    • Singapore Citizen or Singapore Permanent Resident
    • Course fees are fully paid for by the employer
    • Trainee is not a full-time national serviceman
Further Information:
This scheme is intended for all organisations, including non-business entities not registered with ACRA, for example, Voluntary Welfare Organisations (VWOs), societies, etc. Only ministries, statutory boards, and other government agencies are NOT eligible under the Enhanced Training Support for SMEs Scheme. Sole proprietorships which meet all of the above criteria are also eligible.
² SkillsFuture Mid-Career Enhanced Subsidy (MCES)

The ²SkillsFuture Mid-Career Enhanced Subsidy (MCES) is meant for employer-sponsored and self-sponsored Singapore Citizens aged 40 years old and above.

Eligible Singapore Citizens can receive higher subsidies of up to 90% of course fees.
SkillsFuture Credit (SFC)

All Singapore Citizens aged 25 years old and above are eligible for SkillsFuture Credit (Opening Credit), which can be used to offset course fees (for self-sponsored registrations only).
SkillsFuture Credit (Mid-Career)

The SkillsFuture Credit (Mid-Career) is only applicable for the full A*STAR SkillsFuture Career Transition Programme (SCTP) enrolments, and cannot be used for standalone or individual module sign-ups.

How Course Fees are Calculated

TYPE CATEGORY OF INDIVIDUALS
International Participants Singapore Citizens aged 39 years and below, Singapore Permanent Residents and LTVP+ Holders  Employer-sponsored and self-sponsored Singapore Citizens aged 40 years and above  SME-sponsored local employees (i.e Singapore Citizens, Singapore Permanent Residents and LTVP+ Holders)
 FUNDING SOURCE
Not applicable for Funding Support  SkillsFuture Funding (Baseline)  SkillsFuture Mid-career Enhanced Subsidy (MCES) ²  SkillsFuture Enhanced Training Support for SMEs (ETSS) ¹
Full Course Fee $2,400 $2,400  $2,400 $2,400
Funding Support Not Applicable  ($1,680) ($2,160) ($2,160)
Nett Course Fee $2,400 $720 $240 $240
GST 9% $216  $64.80*  $64.80*  $64.80*
Total Nett Course Fee Payable to Training Provider $2,616  $784.80  $304.80 $304.80
* Based on 30% of Full Course Fee

About the Trainers

Dr Li Xiang
Mr Ng Yao Xuan
Dr Ian Chan
Dr Li Xiang
Dr Li Xiang
AI Consultant

Dr Li Xiang is currently an AI Consultant and was previously a Principal Scientist at A*STAR SIMTech, bringing over more than 25 years of experience in research focused on computational intelligence and data mining. Her expertise includes machine learning, data mining and artificial intelligence, such as neural networks, fuzzy logic systems, unsupervised data clustering, and regression modelling. Dr Li’s research areas encompass data mining and AI algorithms for in-situ process monitoring, predictive quality and predictive maintenance on the manufacturing shop floor.

Mr Ng Yao Xuan
Mr Ng Yao Xuan
Senior Research Engineer
A*STAR SIMTech

Mr Ng Yao Xuan is a Senior Research Engineer at A*STAR SIMTech, where he focuses on applying machine learning and AI to address real-world challenges in manufacturing. His work encompasses various areas, including tabular data, computer vision, and industrial time series for shop floor implementation. This includes tasks such as product inspection, anomaly detection, scheduling, predictive maintenance, and process optimisation. His expertise lies in deep learning for computer vision, time series analysis, and foundation models utilising self-supervised learning. This approach helps to reduce the development and fine-tuning cycles of models.

Dr Ian Chan
Dr Ian Chan
Principal Scientist
A*STAR SIMTech

Dr Ian Chan is a Principal Scientist at A*STAR SIMTech. He plays a leading role in strategizing research collaborations with industry to enable AI for manufacturing and engineering services. His key research interests include sensing, data analytics and machine learning to enable predictive capabilities for a broad range of applications. Dr Chan holds a Bachelor’s degree in Mechanical Engineering from the National University of Singapore and a PhD from the Stanford University. Additionally, he was a member of the Technical Committee for Enterprise Singapore Smart Manufacturing for the years 2018 to 2023 and has over 35 publications to date.

Registration

Sign up now

  • Please register for this course through our online form: 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.
  • When the next intake is confirmed, a confirmation email with payment information will be sent to applicants to finalise their participation.

Collateral

Download brochure

Industrial AI In Manufacturing

Contact Us

Technical Enquiries General Enquiries
Dr Li Xiang,
Email: li_xiang_from.tp@a-star.edu.sg		 Knowledge Transfer Office, 
Email: kto-enquiry@a-star.edu.sg

Schedule

Module
 Skills Course Reference Number Next Intake(s)'s Training Period
(Click on the dates to view its schedules)		 Registration Status
  • Industrial Artificial Intelligence In Manufacturing (24 hours)
 TGS-2020505764 EVE7 Jul 2026 - 23 Jul 2026
SIGN UP Now

Registration for the Jul 2026 intake closes on 23 Jun 2026.

Note: A*STAR SIMTech and A*STAR 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 SWDA-approved/SWDA-funded courses must be done digitally via the Singpass App. More information may be viewed here.
  • Participants will be provided with digital course materials when attending our courses. Please note that printed copies will not be available.
Sessions
FD: Full day
AM: Morning
PM: Afternoon
EVE: Evening
 

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