30 AUs coursework or 24 AUs coursework and a dissertation.

 

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MAE Graduate Study Grant

The MAE Graduate Study Grant is awarded to outstanding graduate students seeking admission to MAE’s Master of Science programmes. On top of the admission requirements of each programme, applicants will be assessed based on multiple factors that include academic record, working experiences, past achievements and awards, financial needs etc.

Shortlisted applicants will be invited for interviews, and successful applicants will be informed of the outcome shortly after the offer of admission. Recipients of the grant will be given co-funding (25% or more) of tuition fees.

Recipients are expected to maintain a CGPA of 3.50 each Semester to maintain the eligibility for the Grant.

If you are interested, please complete and submit the MAE Graduate Study Grant Form to MAE Graduate Studies Office ([email protected]). Deadline for submission [August 2025 intake] will be announced soon.

 

Candidates must possess 

(A) A good bachelor’s degree in Mechanical or Industrial engineering or a related discipline with mathematical and production training, or 

(B)  A bachelor's degree in engineering or a related discipline with mathematical training and 2 years relevant industry experience, and

(C) A good TOEFL score (iBT = 85 or more, PBT = 563 or more, CBT = 223 or more) or IELTS score (6.0 or more) for graduates of universities in which English is not the medium of instruction. Please ensure that you upload a scanned copy of TOEFL/IELTS along with your application (hardcopy is not required).

Related disciplines include but are not limited to bachelor's programmes offered by the College of Engineering, Nanyang Technological University, Singapore.

Applicants are recommended to also provide letters of reference from academic or professional supervisors and a clear statement of purpose in support of their application.​

Admissions Application period for August 2025 intake will commence from 4 November 2024 to 28 February 2025.

By application, on a case-by-case basis.

Full-Time (min. 1 year, max. 2 years) and Part-Time (min. 2 years, max. 4 years);

30 AUs coursework or 24 AUs coursework and a dissertation 

 

Option	Description	No. of Courses	Core	Electives
1	Coursework and Dissertation#	8 Courses + Dissertation​	4	4
2	Coursework Only (*Default Option)	10 Courses	4	6

^#Full-time students choosing the dissertation option typically require 1.5 years instead of 1 year to graduate.

*Please note that ALL students will automatically be assigned the default Option 2 - Coursework Only. If you wish to apply for Option 1: Coursework and Dissertation, you must apply using the "Application for Conversion of Option of study" form during your first Semester.

Core Courses

Course Code	Title	AUs	Prerequisite(s)	Semester
MA6501	Manufacturing Control and Automation	3	NIL	1
MA6502	Fundamentals and Advances in Additive Manufacturing	3	NIL	2
​MA6503	​Lasers and Optics in Smart Industry	​3	​NIL	​1 & 2
​MA6504	​Management of Global Manufacturing	​3	​NIL	​1 & 2

 

Elective Courses

 

Course Code	Title	AUs	Prerequisite(s)	Semester
MA6086	Systems Engineering Fundamentals	3	Recommended- Project Management experience	1 & 2
MA6511	Advanced Manufacturing Processes	3	NIL	1 & 2
MA6512	Fundamentals of Precision Engineering	3	NIL	1 & 2
MA6513	Advanced Design for Manufacturing	3	NIL	1 & 2
MA6514	Machine Learning and Data Science	3	Recommended- Background in programming, linear algebra, calculus and statistics	2
MA6515	3D Printing of Electronics	3	NIL	1 & 2
MA6516	Manufacturing in the Circular Economy: Processes, Technologies and Design	3	NIL	2
MA6715	Systems Simulation & Modeling	3	NIL	1
MA6802	Engineering Measurements	3	NIL	2
MA6803	Computational Methods in Engineering	3	NIL	1

Please note that course offerings are subject to review every academic year.

 

Course Synopsis

Core Courses

MA6501 Manufacturing Control and Automation

This course provides an understanding of the technology of manufacturing automation, the common manufacturing processing, mathematical modeling of manufacturing process, the sensors to measure process output variables, the actuators available on machines and the control systems that enable operation of machines.

The course covers the following topics: Manufacturing process modeling; Automation technology: robots; Automation Technology: machines; Robotic control; Machine control.

 

MA6502 Fundamentals and Advances in Additive Manufacturing

This course is designed to equip the participants with fundamental knowledge and general analysis of 3D printing processes.

The course covers the following topics: Introduction to additive manufacturing; Vat photopolymerization; Material jetting;  Material extrusion; Sheet lamination; Powder bed fusion; Directed energy deposition; Binder jetting; Design for additive manufacturing and file formats; Applications of additive manufacturing; Benchmarking and future trends; Case studies.

 

MA6503 Lasers and Optics in Smart Industry

This course on “Lasers and Optics in Smart Industry” better maps to the Industry Transformation Maps (ITMS) through Skills Framework. Necessary elements of Advanced manufacturing and Precision Engineering are included in this course. This will give the manufacturing and precision engineering industry a better assurance that our graduates are equipped with the relevant skills of the advanced and smart manufacturing techniques using lasers and optics, to meet the evolving needs of the sector.

Topics covered are: Basic optics and lasers; Laser optics for material processing; Smart manufacturing-continuous wave and pulsed lasers; Laser beam assisted manufacturing; Interferometric patterning and feature fabrication for smart industry applications; Laser and optics for smart industry

 

MA6504 Management of Global Manufacturing 

This course serves to address broad aspects of managing global manufacturing operation namely, Strategy, Process, Organization & Technology and Industry 4.0 as an integrated framework for dealing with analysis, execution, operation and management of changes required. In this course, we look at the challenges organizations face as they go global, and the changes required on their part to deal with those challenges.

The course covers the following topics: Global manufacturing introduction; Enterprise architecture in global manufacturing; Missing link between corporate strategy & manufacturing; Industry 4.0 and computer integrated manufacturing; Industry 4.0 applications in global manufacturing; Inflection and value chain in global manufacturing; Control of value chain; Framework of manufacturing strategy formulation; Competing for the future; Technology value chain; change management.

 

Elective Courses

MA6086 Systems Engineering Fundamentals

This course introduces students to the fundamental concepts of Systems Engineering and their application to the Management of Projects. It covers a broad spectrum of Systems Engineering topics, across both from a hard systems and soft systems perspective. Primary topics covered in this course will include stakeholder identification, stakeholder analysis, requirement definition, requirements management, system design and development, life cycle Analysis, project complexity, configuration management and interface management. Students will also be introduced to understanding more about Systems Engineering Models, Principles and Best Practices. The main feature of the course is to enable the students to take a “systems approach” to project management.​

 

MA6511 Advanced Manufacturing Processes 

This course provides a graduate level understanding of manufacturing processes needed to provide shape, dimensions and properties to materials at an affordable cost. Starting from the nature of raw materials available for shaping, various methods to shape them will be described. The emphasis will be on linking the nature of the process to the shapes, dimensions and properties that can be achieved. Case studies will be utilized to facilitate the understanding of the choice of the manufacturing processes for various components. The course aims to provide students with a comprehensive coverage of modern manufacturing processes, emphasize on quantitative treatment of manufacturing by introducing manufacturing science concepts and mathematical models to describe and design the processes, and relate theoretical concepts to industrial practice through case studies and assignments.

The course covers the following sections: Overview of manufacturing; Solidification processes; Metal forming; Material addition processes; Material removal processes; Particulate processing of metals and ceramics; Assembly technologies; Manufacturing process selection and process planning.

 

MA6512 Fundamentals of Precision Engineering 

The course aims to provide a fundamental understanding of precision engineering and apply concepts to industrial situations. As a course offered is targeted at MSc Smart Manufacturing it aims to provide a firm grounding of manufacturing science in precision engineering and to enable a good grasp of the concepts that can be applied to industrial problems.

The course covers the following topics: Overview and history of precision engineering; Tolerance technology; Measurement; Principles of precision machine design; Machining.

 

MA6513 Advanced Design for Manufacturing 

The course aims to provide and familiarize students with various design methodologies and tools used in the manufacturing of products.

Topics covered include: Design overview and design principles for manufacturing; Design for manufacturing; Design for assembly; Design for maintainability; Design for customer orientation and quality; Design for automated assembly equipment and devices; Robotic assembly; Selection of materials; Selection of manufacturing processes.

 

MA6514 Machine Learning and Data Science

The purpose of this introductory course in Machine Learning is to show how to adopt ML as an important and essential paradigm in advancing a corporation’s operation and decision making processes towards Industry 4.0. Using Python, Numpy, Pandas and Colab Notebook as its development environment, the presentation of outcome of machine learning computations are achieved through visualization tool, Matplotlib. Scikit-Learn, an extensive well-documented open source suite of machine learning algorithms serves as the platform to analyse data for underlying trends, classification, identifying criteria parameters, deriving rules for decision making in real-world problem solving, thus leading to a rapid prototyping of a suitable machine learning system.

Topics included are: Context of machine learning and data science in Smart Manufacturing for Industry 4.0; Types of machine learning; Unsupervised learning; Supervised learning; Neural networks and reinforcement learning; Model evaluation and improvement.

 

 

MA6515 3D Printing of Electronics

The course covers the fundamental topics that are essential for 3D printing of electronics and smart sensors. It is suitable to prepare students for the future of smart and advanced manufacturing techniques. And this course provides a comprehensive overview of the recent progress and discusses the fundamentals of the 3D printed electronics technologies, their respective advantages, shortcomings and potential applications.

Topics included are: Introduction to conventional electronics manufacturing and 3D Printing of electronics; Conventional contact printing techniques for printed electronics; 3D freeform electronics printing techniques; Materials and inks for 3D printed electronics; Substrates and processing for 3D printed electronics; Sintering techniques for metallic nanoparticle inks; Computational design and simulation; Applications of 3D printed electronics and future trends; Lab tour; Workshop.

 

MA6516 Manufacturing in the Circular Economy: Processes, Technologies and Design

This course provides a graduate level understanding of sustainable manufacturing in the transition towards circular economy. It covers a broad range of concepts, including sustainable assessment frameworks and sustainable manufacturing, with a heavy focus on product end-of-life management to ‘close the loop’. There is a strong emphasis on the enabling tools, technologies, and processes in sustainable manufacturing, supplemented by up-to-date industry insights and illustrated by actual case studies. The course also covers the concept of remanufacturing, which is the process of restoring used products to their original condition, thereby extending their useful life and reducing waste. This course aims to empower you with practical tools and analytical skills to put sustainability at the heart of manufacturing operations and processes.

 

MA6715 Systems Simulation & Modelling

The primary objective of this course is to provide an insight into effective decision-making using simulation modeling. The bulk of the time in the course is spent on discrete event simulation modeling. Simulation model building aspects of discrete systems (such as manufacturing and logistics facilities, supply-chains) are covered in detail. The course also demonstrates the effectiveness of computer simulation to successfully model, analyze and improve systems under study. Simulation software (Arena) is used to demonstrate building and executing the models. Continuous and combined system simulation is also covered in later part of the course. The course also covers the topic of simulation life cycle analysis, and goes over issues such as model verification and validation. Additionally, it looks into the modeling of input data and analysis of model output.

The course covers the following topics: Discrete-event simulation; Basics model-building blocks; Simulation case studies; Simulation modelling of manufacturing facilities; Supply-chain simulation; Simulation workshop; Continuous simulation; Simulation in the process industry; Input-output analysis; Simulation life-cycle analysis; Model verification and validation, Simulation paradigms and languages.

MA6802 Engineering Measurements 

This course aims at introducing the students to the fundamentals of engineering measurements, discussing about various relevant concepts & terminologies. The mathematical background required to categorize & analyze various measurement devices will be presented. Subsequently several classical and modern procedures for measuring parameters of scientific interest, such as displacement, motion, stress, force, flow, pressure, temperature etc., will be discussed in detail.

The course covers the following sections: Advanced principles of measurement; Measurement system design; Advanced metrology.

 

MA6803 Computational Methods in Engineering 

This course focusses on using numerical methods to solve problems on the computer. You will get to understand the behaviour of numerical computations and learn to construct stable solutions to mathematical and engineering problems.

The course covers the following sections: Object modeling and algorithms; Optimisation; Approximation & interpolation; Large-scale systems of linear equations; Numerical differentiation; Numerical integration; Numerical methods for ordinary differential equations; Numerical methods for partial differential equations.

The programme is tailored for practicing industrial engineers, supervisors and technologists employed or seeking employment in manufacturing sectors.

 

Fees

Please note that this MSc programme is a self-financed, non-MOE subsidised programme.

		S$
Application Fees (Inclusive of 9% GST)	Non-refundable (payable when you submit your application)	50
Deposit Payment  (Inclusive of 9% GST)	Non-refundable (payable upon acceptance of offer of admission) The deposit will be used to offset the semester 1 tuition fees after matriculation	5,000
Tuition Fee (Inclusive of 9% GST)	To attain an MSc in Smart Manufacturing, candidates must complete ten courses (30 AUs), or eight courses (24 AUs) and one dissertation (6 AUs)	Academic Year 2024-2025 52,320 (Full Programme) 1,744 (Per Academic Unit)   Academic Year 2025-2026 52,974 (Full Programme) 1,765.80 (Per Academic Unit)

Fees are subject to annual revision

Notes on payment of fees:

 

Students will be billed after course registration period each semester, based on the Academic Units registered and payment due date is 2 weeks after billing date.
A student who withdraws or leaves the University after course registration period has ended is liable to pay the fees due for the semester.

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If you are a Singaporean student, you may use up to $5000 of your SkillsFuture credits towards tuition fees. The claim submission has to be completed 60 days before the start date of the next Semester (e.g. You must submit before November to claim towards Semester 2 tuition fees)

 

To do so, please follow the following steps:

1. Log in to SkillsFuture portal and click on “Make SkillsFuture Credit Claim”
2. Select NTU MSc Smart Manufacturing
   
3. To submit a claim, you should have supporting documents such as letter of offer, matriculation documents etc.
4. In your claim, indicate the course start date to be first day of the upcoming Semester in the Academic Calendar.
5. As your e-bill for the upcoming Semester would not be available yet, take note of your SFC Claim ID.
6. Notify School ([email protected]) and NTU NSS-Finance ([email protected]) of your SFC Claim ID and the amount to be claimed through SFC.
7. When you receive your e-bill for the Semester, leave the SFC amount to be claimed out of your payment.
8. Please refer to Skillsfuture FAQ at this link.

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For Intakes from Academic Year 2024-2025 onwards:

• NTU Alumni students are entitled to 10% study incentives in the form of reduction in fees.
• Students who are Singapore Citizens and Singapore Permanent Residents will receive a one-time subsidy of $5,000.