30 AUs coursework or 24 AUs coursework and a dissertation.

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.
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 2022 - 31 January 2023  

 

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.

Core Courses

Course Code	Title	AUs	Prerequisite(s)	Semester	Availability to Exchange Students
MA6501	Manufacturing Control and Automation	3	NIL	1	Yes, but subject to the School's approval & class availability
MA6502	Fundamentals and Advances in Additive Manufacturing	3	NIL	2	Yes, but subject to the School's approval & class availability
​MA6503	​Lasers and Optics in Smart Industry	​3	​NIL	​1	​Yes, but subject to the School's approval & class availability
​MA6504	​Management of Global Manufacturing	​3	​NIL	​2	​Yes, but subject to the School's approval & class availability

 

Elective Courses

 

Course Code	Title	AUs	Prerequisite(s)	Semester	Availability to Exchange Students
MA6511	Advanced Manufacturing Processes	3	NIL	1	Yes, but subject to the School's approval & class availability
MA6512	Fundamentals of Precision Engineering	3	NIL	2	Yes, but subject to the School's approval & class availability
MA6513	Advanced Design for Manufacturing	3	NIL	1	Yes, but subject to the School's approval & class availability
MA6514	Machine Learning and Data Science	3	Background in programming, linear algebra, calculus and statistics	2	Yes, but subject to the School's approval & class availability
MA6515	3D Printing of Electronics	3	NIL	1	Yes, but subject to the School's approval & class availability
MA6715	Systems Simulation & Modeling	3	NIL	1	Not Available
MA6802	Engineering Measurements	3	NIL	2	Yes, but subject to the School's approval & class availability
MA6803	Computational Methods in Engineering	3	NIL	1	Yes, but subject to the School's approval & class availability

Please note that the courses offered 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 Assoc Prof Zhong Zhaowei  

The course covers the following sections: Manufacturing process modeling; Manufacturing automation: CNC / NC machines and industrial robots; Devices for manufacturing automation (drives, feedback sensors, control loops); Control methodologies applicable to manufacturing systems.

MA6502 Fundamentals and Advances in Additive Manufacturing

Taught by Professor Yeong Wai Yee, Dr Ng Wei Long

The course covers the following sections: An introduction to additive manufacturing processes and systems based on ASTM/ISO standards; Design and applications in various high value industries including aerospace, biomedical and manufacturing; Current potentials and challenges in additive manufacturing for industrial 4.0.

MA6503 Lasers and Optics in Smart Industry

Taught by Assoc Prof Murukeshan Vadakke Matham ​

Basic knowledge in optics and lasers is very essential in Smart Manufacturing. The objectives of the course are to familiarize the learners with different optical and Laser concepts, light sources and how they can be applied in smart industry applications.

MA6504 Management of Global Manufacturing 

Taught by Assoc Prof Appa Iyer Sivakumar

The course covers the following sections: Introduction and overview; Global manufacturing operations: planning and implementation; Justification and evaluation of global manufacturing; Global manufacturing operations: management; Case study. 

 

Elective Courses

MA6511 Advanced Manufacturing Processes 

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

The course covers the following sections: Manufacturing processes; Nature and various methods of raw materials for shaping; Emphasis on the link between the nature of the process to the shapes, dimensions, and properties that can be achieved; Case study.

MA6512 Fundamentals of Precision Engineering 

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

The course covers the following sections: History of precision engineering. Principles and definitions of precision machine design; State-of-the-art in research, prototyping and full production from ultra-precision machining through micro-engineering, microelectronics and molecular manipulation; Application of displacement transducers to machines and instruments; Tolerance technology.

MA6513 Advanced Design for Manufacturing 

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

The course covers the following sections: DFM principles and strategies; Classification system for manual, automatic and robotic assemblies; Evaluation of assembled parts; Analysing products for high-speed automatic assembly; Procedure for redesign; Design of parts for feeding and orienting; Vibratory and non-vibratory feeders; QFD process; Reliability analysis for product design; Selection of materials and processes; Design for repair and recycling.

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 (ML) 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.

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.

MA6715 Systems Simulation & Modelling

Taught by Assoc Prof Rajesh Piplani

The course covers the following sections: Discrete-event simulation; Basic model-building blocks; Simulation of global manufacturing facilities; System life cycle analysis; Simulation validation and verification; Continuous Simulation; Supply Chain Modelling; Simulation Case Study.

MA6802 Engineering Measurements 

Taught by Assoc Prof Fan Zheng David and Dr Cheng Fang

The course covers the following sections: Advanced principles of measurement that examine the static and dynamic characteristics of instruments; The design of measurement system through the application of sensing and signal conditioning elements for data acquisition; Overview of the operations of some specialised measurement systems which have important industrial applications; Advanced principles of measurements which examine the static and dynamic characteristics of instruments.

MA6803 Computational Methods in Engineering 

Taught by Dr Lee Yong Tsui and Professor Li Hua ​

The course covers the following sections: Overview of computational requirements in engineering; Object modeling and algorithms; Optimisation; Approximation and Interpolation; Large-Scale Systems of Linear Equations; Numerical Differentiation; Numerical Integration; Numerical Methods for ODEs; Numerical Methods for PDEs.

 

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) Exclusive of GST	Singapore Citizen (SC)	36,000#
	Singapore Permanent Resident (SPR)	40,500
	International Student (IS)	45,000
Programme Tuition Fee (per AU) Exclusive of GST	Singapore Citizen (SC)	1200
	Singapore Permanent Resident (SPR)	1350
	International Student (IS)	1500

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. 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. As your e-bill for the upcoming Semester would not be available yet, take note of your SFC Claim ID.
5. Notify School (mae.msc@ntu.edu.sg) and NTU NSS-Finance (pbs@ntu.edu.sg) of your SFC Claim ID and the amount to be claimed through SFC.
6. When you receive your e-bill for the Semester, leave the SFC amount to be claimed out of your payment.