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, nationality, 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 will be announced with the next admissions application period.

 

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 = 100 or more, PBT = 600 or more, CBT = 250 or more) or IELTS score (6.5 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. Business graduates will also be considered if they have relevant specialisation and/or relevant experience; relevant experience needs to be supported by a letter from the employer.​

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

 

Admissions Application period for August 2023 intake :  1 November 2023 - 31 January 2024 

 

 

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

*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
​MA6504	​Management of Global Manufacturing	​3	​NIL	​2

 

Elective Courses

 

Course Code	Title	AUs	Prerequisite(s)	Semester
MA6511	Advanced Manufacturing Processes	3	NIL	1
MA6512	Fundamentals of Precision Engineering	3	NIL	2
MA6513	Advanced Design for Manufacturing	3	NIL	1
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
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

Taught by Professor Chen I-Ming, Assoc Prof Xie Ming and Dr Zhong Zhaowei  

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

Taught by Professor Yeong Wai Yee, Dr Ng Wei Long

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

Taught by Assoc Prof Murukeshan Vadakke Matham ​

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 

Taught by Assoc Prof Appa Iyer Sivakumar

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

MA6511 Advanced Manufacturing Processes 

Taught by Assoc Prof Zhou Wei and Dr Arun Prasanth Nagalingam ​

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 

Taught by Assoc Prof Yeo Swee Hock and Assoc Prof Murukeshan Vadakke Matham ​

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 

Taught by Professor Lye Sun Woh, Dr Lee Siang Guan, Stephen and Dr Narasimalu Srikanth

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

Taught by Dr Sim Siang Kok and Assoc Prof Leong Kah Fai

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 

Taught by Professor Yeong Wai Yee and Assoc Prof Tuan Tran

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.

 

MA6715 Systems Simulation & Modelling

Taught by Assoc Prof Rajesh Piplani

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 

Taught by Assoc Prof Fan Zheng David and Dr Cheng Fang

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 

Taught by Dr Lee Yong Tsui and Professor Li Hua ​

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 and Financial Aid

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

		S$
Application Fees	Non-refundable (payable when you submit your application)	21.40
Deposit Payment (The deposit will be used to offset the semester 1 tuition fees after matriculation)	Non-refundable (payable upon acceptance of offer of admission)	1000
Programme Tuition Fee (Full Programme) Inclusive of 8% GST	Singapore Citizen (SC)	38,880#
	Singapore Permanent Resident (SPR)	43,740
	International Student (IS)	48,600
Programme Tuition Fee (per AU) Inclusive of 8% GST	Singapore Citizen (SC)	1296
	Singapore Permanent Resident (SPR)	1458
	International Student (IS)	1620

To attain an MSc in Smart Manufacturing, candidates must complete ten courses, or eight courses and dissertation.

Notes on payment of fees:

Fees are subject to annual revision
Students will be billed at the commencement of each semester, and payment due date is 2 weeks after billing date.
A student who withdraws or leaves the University two or more weeks after the commencement of his candidature or the commencement of the semester is liable to pay the fees due for the semester.

^# If you are a Singaporean student, you may use up to $1000 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 NTU MSc Smart Manufacturing programme page on SkillsFuture portal
2. Click on “Claim SkillsFuture Credit”
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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