Smart Manufacturing Systems MSc

Program Overview

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The MSc in Smart Manufacturing Systems at Ulster University equips students with expertise in smart manufacturing principles and applications, including AI, robotics, and data analytics. Graduates are prepared for careers in the rapidly developing field of smart manufacturing, where they can design and implement efficient, sustainable, and responsive manufacturing systems. The program emphasizes multi-disciplinary knowledge and skills, including global business and enterprise, to meet the challenges and opportunities of Industry 4.0.

Program Outline

The MSc in Smart Manufacturing Systems is a collaborative program offered by 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 program focuses on providing postgraduate education and training in the concepts and methods within manufacturing and mechanical engineering with the application of data analytics, artificial intelligence (AI), and machine learning. The overall objective of the program is 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. Additionally, the program develops knowledge and skills to understand the nature of the global business environment and global business operations.

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Program Aims:

The MSc in Smart Manufacturing Systems aims to:

• Equip students with expertise in the principles and applications of Smart Manufacturing.
• Provide students with a deep understanding of the key technologies driving Smart Manufacturing, including AI, robotics, automation, the Internet of Things (IoT), and industrial digital technologies.
• Develop students' ability to apply data analytics and machine learning in industrial settings.
• Prepare students for successful careers in the rapidly developing field of Smart Manufacturing.
• Provide students with the knowledge and skills needed to design and implement smart manufacturing systems.
• Equip students with the ability to understand and respond to the challenges and opportunities presented by the Fourth Industrial Revolution (Industry 4.0).

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Program Learning Outcomes:

Upon successful completion of the program, graduates will be able to:

• Apply AI, robotics, automation, IoT, and industrial digital technologies to solve real-world problems in manufacturing.
• Develop and implement data analytics and machine learning models to optimize manufacturing processes.
• Design and implement smart manufacturing systems that are efficient, sustainable, and responsive to market demands.
• Work effectively in multi-disciplinary teams to solve complex engineering challenges.
• Communicate effectively with technical and non-technical audiences.
• Demonstrate an understanding of the ethical, social, and environmental implications of Smart Manufacturing.

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Outline:

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Program Content:

The MSc in Smart Manufacturing Systems curriculum covers a wide range of topics related to Smart Manufacturing, including:

• Robotics and automation
• Industrial digital technologies
• Data analytics and machine learning
• Industrial internet of things (IIoT)
• AI and machine learning in manufacturing
• Design and implementation of smart manufacturing systems
• Global business and enterprise
• Project management

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Program Structure:

The MSc in Smart Manufacturing Systems is a two-year, part-time program. Students are required to complete 180 credits, including 120 credits of taught modules and 60 credits of a research project. The taught modules are delivered across the first two semesters of each of the first two years. Students typically complete three taught modules in each semester. The course schedule is subject to change, but typically includes the following modules:

• Year 1:
• BUS700 - The Global Business in Context
• MEC702 - Advanced Manufacturing and Industrial Robotics
• MEC703 - Smart Factories
• Year 2:
• COM735 - Business Intelligence and Analytics
• COM738 - Data Science Foundations
• MEC704 - Computer Aided Engineering and Manufacturing
• Year 2/3:
• COM865 - Masters Project (Research)

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Individual Module Descriptions:

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BUS700 - The Global Business in Context:

This module provides students with a comprehensive understanding of the global business environment. Topics covered include globalization, international trade, multinational corporations, and global business strategy.

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MEC702 - Advanced Manufacturing and Industrial Robotics:

This module introduces students to the principles and applications of advanced manufacturing and industrial robotics. Topics covered include robotics, automation, computer-aided design (CAD), computer-aided manufacturing (CAM), and process control.

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MEC703 - Smart Factories:

This module explores the concept of smart factories and how they are being used to improve manufacturing efficiency and productivity. Topics covered include the Internet of Things (IoT), data analytics, artificial intelligence (AI), and machine learning.

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COM735 - Business Intelligence and Analytics:

This module provides students with the skills and knowledge necessary to analyze and interpret data. Topics covered include data warehousing, data mining, and business intelligence.

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COM738 - Data Science Foundations:

This module introduces students to the fundamental concepts of data science. Topics covered include statistics, machine learning, and data visualization.

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MEC704 - Computer Aided Engineering and Manufacturing:

This module provides students with the skills and knowledge necessary to design and manufacture products using computer-aided design (CAD) and computer-aided manufacturing (CAM) software.

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COM865 - Masters Project (Research):

The research project is a substantial piece of independent research that allows students to apply the knowledge and skills they have learned throughout the program.

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Assessment:

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Assessment Methods:

The MSc in Smart Manufacturing Systems uses a variety of assessment methods to assess student learning, including:

• Exams
• Assignments
• Presentations

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Teaching:

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Teaching Methods:

The MSc in Smart Manufacturing Systems uses a variety of teaching methods, including:

• Lectures
• Tutorials
• Practical work
• Group work
• Online learning

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Faculty:

The program is taught by a team of experienced and qualified faculty members from the School of Computing, Engineering and Intelligent Systems and the Department of Global Business and Enterprise. The faculty members have extensive experience in both industry and academia.

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Unique Teaching Approaches:

The program uses a number of unique teaching approaches, including:

• The "flipped classroom" model, where students are expected to come to class prepared having already reviewed the material.
• The use of digital technologies, such as Blackboard Collaborate and the University's Virtual Learning Environment (VLE).
• A pre-induction boot camp to help students develop the programming skills needed for the program.

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Careers:

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Career Options:

Graduates of the MSc in Smart Manufacturing Systems can pursue a variety of careers in the manufacturing industry, including:

• Smart factory manager
• Robotics engineer
• Automation engineer
• Data analyst
• Machine learning engineer
• Project manager
• Research and development engineer

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Work Placement / Study Abroad:

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

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Other:

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Attendance Requirements:

Students are required to attend all classes associated with the program and be punctual and regular in attendance.

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English Language Requirements: