Program Overview

Smart Manufacturing Systems - MSc

Overview

The MSc in Smart Manufacturing Systems is a collaboration between the School of Computing, Engineering and Intelligent Systems in the Faculty of Computing, Engineering and the Built Environment, and the Department of Global Business and Enterprise in the Ulster Business School. The overall aim of the course is to provide postgraduate education and training in the concepts and methods within the area of manufacturing and mechanical engineering with the application of industrial robotics, data analytics and artificial intelligence (AI)/machine learning to meet the needs of manufacturing in Industry 4.0.

About

The programme aims to equip students with expert knowledge across multi-disciplines in both the underlying science and application of manufacturing and mechanical engineering with the computing topics of intelligent data analytics and robotics. In addition, the programme develops knowledge and skills to understand the nature of the global business environment and global business operations.

Modules

• BUS700 - The Global Business in Context
• COM735 - Business Intelligence and Analytics
• COM738 - Data Science Foundations
• MEC702 - Advanced Manufacturing and Industrial Robotics
• MEC703 - Smart Factories
• MEC704 - Computer Aided Engineering and Manufacturing
• COM865 - Masters Project (Research)

Attendance

Beginning in September, the degree will normally be completed in three semesters across a single academic year. Each lecture will be hosted at the Magee campus. The project is completed in the third semester.

Start dates

• September 2026

Teaching, Learning and Assessment

The aims and learning outcomes of the programme are achieved through the application of a variety of teaching and learning methods across the modules. The modules allow a varied and interesting mix of methods to be used to enhance knowledge and understanding as well as allowing students to practise and develop their professional skills.

Assessment and Feedback

In 2011 the University adopted 7 Principles of Assessment and Feedback for Learning, based on the Reengineering Assessment Practices (REAP) principles.

Academic profile

The University employs over 1,000 suitably qualified and experienced academic staff - 60% have PhDs in their subject field and many have professional body recognition.

Standard entry conditions

Applicants must:

• have gained a second class honours degree or better in the subject area of Mechanical Engineering, Electrical/Electronic Engineering, Computer Engineering, or a related discipline, from a university of the United Kingdom or the Republic of Ireland, or from a recognised national awarding body, or from an institution of another country which has been recognised as being of an equivalent standard; or
• an equivalent standard (normally 50%) in a Graduate Diploma, Graduate Certificate, Postgraduate Certificate or Postgraduate Diploma or an approved alternative qualification and the qualification must be in the subject area of Mechanical Engineering, Electrical/Electronic Engineering, Computer Engineering, or a related discipline

and

• provide evidence of competence in written and spoken English (GCSE grade C or equivalent).

English Language Requirements

The minimum requirement for this course is Academic IELTS 6.0 with no band score less than 5.5. Trinity ISE: Pass at level III also meets this requirement for Tier 4 visa purposes.

Exemptions and transferability

Studies pursued and examinations passed in respect of other qualifications awarded by the University or by another university or other educational institution, or evidence from the accreditation of prior experiential learning, may be accepted as exempting candidates from part of the programme provided that they shall register as students of the University for modules amounting to at least the final third of the credit value of the award, at the highest level.

Careers & opportunities

Smart Manufacturing is a rapidly developing field of study within both academia and industry. The MSc Smart Manufacturing Systems aims to prepare students for a successful career as a modern manufacturing engineer where Industry 4.0 machine-to-machine (M2M) communication (products talk to machines) is producing large amounts of collected data, where analytics now plays a key role in understanding and modelling process improvements, alongside competitive demands within a global business context.

Work placement / study abroad

There is no work-based learning or supervised work experience/placement within the MSc programme.

Fees and funding

Postgraduate fees are subject to annual review, 2026/27 fees will be announced in due course.

Additional mandatory costs

It is important to remember that costs associated with accommodation, travel (including car parking charges) and normal living will need to be covered in addition to tuition fees.

Terms and Conditions

The University prepares its prospectus and online information about its courses with care and every effort is made to ensure that the information is accurate. The printed version of the prospectus is, however, published at least a year before the courses begin. Information included in the prospectus may, therefore, change. This includes, but is not limited to changes to the terms, content, delivery, location, method of assessments or lengths of the courses described.