AIM-Ready: Predictive Maintenance and Shopfloor Analytics* (16 Hours)

*This is a non-WSQ module.

This programme is in collaboration with the Sectoral AI Centre of Excellence for Manufacturing (AIMfg).

Introduction

As manufacturers accelerate their digital transformation journey, AI in Manufacturing (AIM) and predictive shopfloor analytics are becoming key enablers for improving equipment reliability, product quality, operational efficiency, and overall production performance. But are you ready for AIM? Successful adoption requires more than technology—it demands the ability to identify the right business opportunities, assess organisational readiness, and develop a practical strategy for implementation and adoption.

This programme prepares and equips participants with the knowledge and practical frameworks to identify high-value use cases across predictive maintenance, automated operational monitoring, quality monitoring, and process performance improvement. Participants will learn how to translate operational challenges into clearly defined problem statements, establish measurable key performance indicators (KPIs), and determine the technical and business requirements needed for successful implementation.

Through real-world case studies, industry examples, and guided discussions, participants will explore key considerations including shopfloor data readiness, Internet of Things (IoT) and sensor connectivity, data acquisition, data mining and predictive modelling, systems integration, visualisation dashboards, business value assessment, and implementation risks.

By the end of the programme, participants will be able to identify a uitable predictive maintenance and shopfloor analytics use cases, assess its readiness and business value, and develop a practical implementation roadmap and business adoption proposal relevant to their organisation.

About this Programme

This programme enables manufacturing professionals to evaluate, plan, and lead the adoption of predictive shopfloor analytics within their organisations. Combining strategic planning with practical implementation considerations, participants will gain the confidence to identify suitable applications, assess technical and organisational readiness, prioritise investment opportunities, and formulate actionable roadmaps that support data-driven manufacturing and operational excellence.

Who Should Attend

This programme is designed for manufacturing professionals responsible for driving operational excellence and digital transformation initiatives. It is suitable for:

Manufacturing leaders and plant managers
Operations managers
Maintenance managers and engineers\Quality managers and engineers
Process and manufacturing engineers Automation and controls engineers
IT/OT leaders and industrial digitalisation teams
Project managers and business owners responsible for implementing Industry 4.0 and smart manufacturing initiatives

The programme is particularly beneficial for professionals seeking to improve equipment reliability, operational visibility, productivity, product quality, and overall process performance through predictive shopfloor analytics.

No prior programming, data science, or machine learning experience is required. Participants should, however, have a basic understanding of manufacturing operations, maintenance, quality, automation, or digital transformation within a manufacturing environment.

Upon Completion of This Course

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, Full and Nett Course Fees

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.

Full Course Fee

The full course fee for this course is $1,600 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
$1,744	$523.20	$203.20	$203.20

All fees are inclusive of GST 9%.

Please note that fees and funding amount are subject to change.

Long Term Visit Pass Plus (LTVP+) Holders

The 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.

Enhanced Training Support For Small & Medium Enterprise (SMES) Scheme (ETSS)

The ¹Enhanced Training Support for Small & Medium Enterprises (SMEs) scheme (ETSS) is for company-sponsored participants who are subject to the eligibility criteria shown below:

SMEs that meet all of the following eligibility criteria:

Registered or incorporated in Singapore
Employment size of not more than 200 or with annual sales turnover of not more than $100 million

SME-sponsored Trainees:

Must be Singapore Citizens or Singapore Permanent Residents.
Courses have to be fully paid for by the employer.
Trainee is not a full-time national serviceman.

Further Info: This scheme is intended for all organisations, including non-business entities not registered with ACRA e.g. VWOs, societies, etc. Only ministries, statutory boards, and other government agencies are NOT eligible under Enhanced Training Support for SMEs Scheme. Sole proprietorships which meet all of the above criteria are also eligible.

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.

SkillsFuture Credit

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

For more information on the funding support schemes you are eligible for, please visit www.skillsfuture.gov.sg

Note:

This course is eligible for SkillsFuture Credit (Mid-Career) only if you sign up and enrol under the SkillsFuture Career Transition Programme (SCTP).
If you are applying only for this module, you can still use your Opening SkillsFuture Credit and One-Off SkillsFuture Credit Top Up to offset the course fee as a self-sponsored participant.

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	$1,600	$1,600	$1,600	$1,600
Funding Support	Not Applicable	($1,120)	($1,440)	($1,440)
Nett Course Fee	$1,600	$480	$160	$160
GST 9%	$144	$43.20*	$43.20*	$43.20*
Total Nett Course Fee Payable to Training Provider	$1,744	$523.20	$203.20	$203.20

* Based on 30% of Full Course Fee

Course Outline

By the end of this course, participants will have developed a comprehensive set of skills and knowledge to confidently navigate the AI and IoT implementation journey. Through a hands-on and practical learning experience, participants will be equipped to tackle each critical stage of the process — from laying the groundwork to executing a well-informed adoption plan. Specifically, participants will be able to:

Define Problem Statements
Assess Sensor Connectivity
Clarify Business Values
Evaluate Data Readiness
Identify Opportunities
Plan AIM Adoption

About the Trainers

Registration

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

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)' Training Period (Click on the dates to view their schedules)	Registration Status
AIM-Ready: Predictive Maintenance and Shopfloor Analytics (16 hours)	TGS-2026065124	The schedule for the next intake is still in the planning stage.

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

: Full day

: Morning

: Afternoon

: Evening

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