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Are you ready to start your Master of Engineering journey?
Smart manufacturing engineering
In manufacturing, the digital future is right here, right now.
Enhance your knowledge and transform your career by equipping yourself with cutting-edge skills in connecting systems and data to drive innovation and manage quality in smart manufacturing.
Gain expertise and hands-on experience in robotics and automation, AI and neural networks and cyber-physical systems for optimising lean processes and outcomes.
The dynamic and transformative field of smart manufacturing offers businesses unprecedented opportunities to enhance productivity, reduce costs, and improve overall competitiveness.
You’ll learn to optimise production systems, improve efficiency and drive innovation by harnessing the power of advanced technologies like artificial intelligence, machine learning, robotics and cyber-physical connectedness.
Use digital twin technology to simulate an entire production facility, optimising layouts, resource allocation, and workflow efficiency. Or harness and analyse real-time data to forecast equipment maintenance needs, reducing downtime.
Help shape the future of the next generation of industries as a smart manufacturing engineer.
You need to satisfy the following entrance requirements to be considered for entry to this course.
Minimum Entry Requirements
Qualifications
An Australian Bachelor of Engineering* degree (or equivalent) in a discipline relating to the specialisation to be studied within the Master course as approved by the Faculty, with at least high credit (65%) average.
*equivalent to an Australian 4 year Bachelor of Engineering degree.
Please note: the Engineering management, Renewable energy engineering and Smart manufacturing engineering specialisations are available to applicants with an Australian Bachelor of Engineering in any discipline, excluding Software engineering. For other Master's specialisations, the prior qualification must be in a related discipline.
Find further detail of the relevant undergraduate degree disciplines that align to each of the masters specialisations here.
English requirements
Applicants must also meet the English language requirements.
University entrance requirements
Minimum entrance requirements for admission to Monash University Australia.
Inherent requirements
To complete your degree, you will need to demonstrate that you have the abilities, knowledge, and skills to achieve specific core learning outcomes, these are called inherent requirements.
Find out more about inherent requirements for this course.
Use the course map alongside the Handbook to plan your studies throughout your master’s degree. If you’re unsure about your course progression, contact your course adviser.
Fees are subject to change annually.
Full fee
Fees are per 48 credit points which represents a standard full-time course load for a year. The fees for 2027 are:
- Domestic students: A$51,840
- International students: A$60,740
Note: see information on how average fee is calculated.
Fee assistance
As a full fee-paying student, you may be eligible to apply for the optional FEE-HELP to assist you to pay all or part of your tuition fees.
Other costs and fees
For information on other study costs and fees, see other study costs.
Smart manufacturing is the nexus where robotics, digital twins, cyber-physical systems and AI converge. This course equips engineers with a deeper understanding of these integrated systems, preparing them for the challenges and opportunities of modern industry.”
KEENAN GRANLAND
PhD graduate in robotics and mechatronics
Lab Manager, Monash Smart Manufacturing
Careers in Smart Manufacturing Engineering
Demand for professionals with knowledge and skills in smart manufacturing is surging as industries worldwide embrace rapid technological change and digital disruption. You could:
- Integrate robotics into manufacturing systems and design human-machine interfaces for seamless control
- Connect machines using internet of things (IoT) principles for real-time monitoring and predictive maintenance
- Implement deep learning and AI-based inspection, process optimisation and product quality assurance methods
- Develop digital twin replicas and simulations for developing new processes, optimising current processes, and product lifecycle management
- Streamline supply chain management with smart systems and AI-driven demand forecasting.
What you will learn
Smart Manufacturing Engineering stories and research
Explore other masters specialisations
Got a question?
If you have any queries about the Master of Engineering, or if you’d like to find out more, please contact us:
Domestic students
Telephone: 1800 MONASH (1800 666 274)
Domestic student enquiry form
International students
Telephone: +61 3 9903 4788
International student enquiry form