AUTOMATED MANUFACTURING ENGINEERING

This module introduces students to casting, forming, machining, additive manufacturing, and automated production systems. Students will evaluate process capabilities, match materials to processes, integrate automation tools, and apply quality management and continuous improvement principles to optimise manufacturing performance.

This module equips students with the knowledge and skills to model, analyse, and design control systems, including PID controllers, and to evaluate performance using simulation tools. Students will gain hands-on experience in understanding system behaviour, stability, and response characteristics, preparing them for advanced engineering applications.

This module equips students with the tools and techniques to plan, monitor, and control engineering projects. Students will also explore ethical, environmental, and legal responsibilities, as well as quality and operations management principles. The module provides practical insights into managing change within engineering assets and operational contexts.

This module introduces students to industrial robotics, covering motion control, programming, safety, and system integration. Students will gain hands-on experience with robotic workcells, learning to integrate sensors and PLC signals while analysing performance and understanding the limitations of robotic systems in manufacturing applications.

This module introduces students to renewable energy technologies, sustainability principles, and the environmental and societal impacts of engineering solutions. Students will learn to assess system efficiencies, compare renewable integration strategies, and make informed, sustainable decisions in the design of engineering systems.

This module introduces students to thermodynamic cycles, heat transfer, and fluid flow in engineering applications. Students will explore fluid machine design and turbomachinery, apply analytical methods to real systems, and develop practical skills through experimental work, interpreting results with attention to accuracy and uncertainty.

You will gain valuable work experience on a 48-week work placement. This is an exciting opportunity to put what you have learned into practice, broaden your experience and demonstrate your abilities to potential employers.

This module equips students with the knowledge and skills to apply FEA and CFD techniques to real-world engineering problems. Students will develop confidence in building, validating, and interpreting complex simulation models, while critically assessing their accuracy, limitations, and role in professional engineering practice.

This module explores how digital technologies are transforming modern manufacturing. Students will investigate digital manufacturing systems, CNC integration, automation, and digital twin technologies used to optimise production performance. Emphasis is placed on data-driven analysis, system integration, and critical evaluation of risks and limitations in industrial digital manufacturing environments, preparing graduates for advanced roles in smart and automated production systems.

The Independent Major Project is the culmination of the degree programme and provides students with the opportunity to investigate and solve a significant engineering problem of their choosing. Working independently with academic supervision, students will plan and deliver a major project, applying advanced technical skills while considering ethical, sustainability, and professional requirements. The project develops the autonomy, critical thinking, and communication skills expected of graduate engineers.

This module enables students to design, implement, and optimise industrial robotic systems using industry-relevant tools and standards. Students will work with digital twins, safety frameworks, and performance metrics to evaluate and improve robotic workcells, preparing them for professional roles in robotics and automation engineering.

This module focuses on the practical integration challenges of smart manufacturing environments. Students explore smart factory architectures, industrial communication frameworks, and system interoperability between machines, robots, and enterprise systems. Through applied design and analysis, learners will evaluate system resilience, cybersecurity, and scalability, preparing them to lead smart factory deployment and digital transformation initiatives in modern manufacturing.

This module focuses on the practical integration challenges of smart manufacturing environments. Students explore smart factory architectures, industrial communication frameworks, and system interoperability between machines, robots, and enterprise systems. Through applied design and analysis, learners will evaluate system resilience, cybersecurity, and scalability, preparing them to lead smart factory deployment and digital transformation initiatives in modern manufacturing.