The global manufacturing sector is going through an important phase of digitalisation, driven by the changes brought by the 4th Industrial Revolution. This is impacting on how many manufacturing organisations organise their businesses and the technologies that drive it.
This has led to the need to develop new type of engineers for working in these new areas where significant advances in automation and digital manufacturing are taking place.
Many organisations are using automation to drive up productivity and implementing digital technologies in their operations. By combining the two, we are seeing very different approaches to how manufacturing organisations run their factories and businesses and also benefiting from better planning and decision-making using technologies such as Digital Twins.
The MSc Automation and Digital Manufacturing is designed to provide these new approaches which are highly sought after by organisations on a global scale. To ensure the course content remains current, the programme has been designed in collaboration with strong industry partnerships with companies such as Siemens and Festo. The course also benefits directly from this relationship by being a founding member of the Connected Curriculum project devised by these two organisations, bringing industry practices to academic courses.
The main focus of the MSc Automation and Digital Manufacturing is developing competent and highly sought after engineers with broad academic knowledge and high level of practical skills in automation systems coupled with relevant digital technologies in high-tech manufacturing industries.
The course will suit graduates who aspire to work as automation and digital manufacturing engineers in high-tech organisations operating in sectors such as automotive, food and beverage production, advanced manufacturing, robotics and automation, nanotechnology, systems integration, aerospace, bio-engineering and healthcare, pharmaceuticals and renewable energy.
The course is directly supported by companies such Siemens, Festo, Omron, ABB, National Instruments, Altium and WorldSkills UK.
The course also benefits from the department being a member of:
Graduates joining the programme will gain high level practical skills and knowledge in:
New manufacturing technologies such as additive manufacturing, AR/VR technologies and their application.
Sign up to receive the latest information about studying at Middlesex University London.
Our communications are designed to support you in deciding your future and keep you up to date about student finance, employment opportunities and student activities available at Middlesex University.
The programme is formed of three academic terms, each of 12 weeks of duration. Term 1 will be devoted to drives, sensors and controllers including PLCs, robotic applications and their programming techniques, software modelling of automation systems and additive manufacturing technologies along with AR and VR applications.
Term 2 will feature a group project where the knowledge and skills developed in term 1 will be applied to a digital enterprise. There will also be further input into PLM solutions and process simulation and analytics and how organisations could use these to manage their products and services, as well as technologies in Industry 4.0 such as Digital Twin and their applications.
Term 3 will be an individual project that can be proposed by the student or selected from a choice of projects offered by our research centres or industry partners.
A successful graduate will leave with highly sought after practical skills and advance knowledge in working with automation systems involving the state of the art technological solutions, ability to devise and work with Digital Twins, be able to carry out process optimisation and analytics using discrete event modelling and ability to implement digitalisation in manufacturing organisations.
This module will cover latest techniques in digital product modelling applied to manufacturing systems. The module also will also cover modelling of components, assemblies and systems including their physical behaviour in virtual space. There will also be visualisation techniques (VR, AR etc.) of such systems as well as design strategies for digital manufacture, including additive manufacturing.
This module equips students with knowledge of fundamental concepts of robot manipulators, such as coordinate systems, transformations, kinematics, motion planning. Students will put the knowledge of these principles into practice by modelling, simulating, programming, and operating robot arms. They will gain experience of specialised software frameworks for robotic manipulation.
This is a hands-on module, giving the student the opportunity to experience the cutting-edge technologies found in factory automation and digitalisation. The module will visit fundamentals such as drives and control techniques, industrial controllers, sensor networks, communication protocols and swiftly move onto integrated systems to deliver total automation solution using Industry 4.0 technologies and digital manufacturing found in Smart Factory and Cyber-Physical systems.
This module will enable the student to understand the scientific methods underlying the modelling of real systems. Following on from the modules taught in preceding term, the module will further expand their understanding of a range of sophisticated simulation techniques and simulation methods using the examples facilitated by manufacturing systems. Case studies will be used to illustrate how models can be validated against real measurements. The module will also explore data analysis and decision making following experimentation using what-if scenarios and continuous data monitoring using cloud-based tools and techniques (Industrial IoT).
This module will consider organisations as an enterprise and how this could benefit from digitalisation, and the steps involved in achieving this. Case study examples will be used to explore these. Module will also cover analysing such organisations, particularly SMEs, and explore routes to digitalisation for maximum benefit while considering issues such as cost, timescales and readiness for digital transformation and implementation, particularly for Industry 4.0.
This module aims to introduce the students to the concept and fundamentals of Digital Twin, the key functionalities they provide in the context of automation and manufacturing. Several examples and case studies will be used to highlight the opportunities and challenges of implementing digital twins across various industries. The module will also provide a general understanding of the Manufacturing Execution System (MES) and its purposes. Students will have the opportunity to discover the specific functionality and operation of MES for the Festo Cyber-Physical (CP) Factory through a practice-based approach.
The module will introduce Product Lifecyle Management and how this can be implemented in a product-based organisation to add value to the business. The module will also cover Industry 4.0 technologies and how these relate to an organisation’s PLM environment.
This module consolidates the knowledge and advanced skills gained in the preceding part of the programme and provides students with the opportunity to develop and demonstrate mastery in undertaking projects on their own. Students will be required to use a systematic, effective, and efficient research and development processes employing formal project management techniques in executing a practical project to prepare them for their future employment. The module aims to develop advanced skills and practical experience in research methods, project planning, problem solving, written and oral communication on projects within the scope of the programme.
The programme is designed to be taught using practice-led teaching and learning approaches and is intended to replicate the current practice in industry. The sessions are delivered in labs and workshops supplemented by guest lectures with speakers from industry on a weekly basis. The labs and workshops are in blocks of 3-hour sessions, providing ample opportunity to gain practical skills in the subject’s natural environment.
As the programme pedagogy is based on practice-led approaches, this then follows an appropriate assessment strategy based on project work, demonstrations, and presentations. Some CW elements will include technical report writing as well as multimedia content such as blogs and video recordings. Developing a repository of online content will be highly encouraged as this will also help with employment opportunities. The programme does not contain any traditional written examinations.
Graduates from the programme will be expected to enter into employment that require high level skills in automation systems incorporating digital technologies with highly specialised practical skills in automated production solutions that are much sought after worldwide. The programme content will be enriched by keeping industrial partners’ engagement active and offering sponsored projects. This will also help to support the students regarding current opportunities and future trends in their relevant employment sectors.
Typical sectors for employment:
Dr Huan Nguyen is a Specialist in telecommunications, digital twins and computer networks and network communications. He joined Middlesex in 2011 as a Senior Lecturer, and is now a Professor and Chair of Digital Communications Engineering. Dr Nguyen holds a PhD in Electrical Engineering from The University of New South Wales in Sydney, Australia.
Prof Mehmet Karamanoglu is a specialist in automated system, mechatronics, industrial control, systems modelling, discrete event simulation. He's served as the Head of the Design, Engneering and Mathematics department since 2012, but has been with Middlesex university since 2016.
Dr Ramona Trestian is a specialism in Digital Twin technologies and smart systems. She joined the School of Science and Technology at Middlesex University in August 2013 where she currently is a Senior Lecturer in Computing and Communications Engineering. She was previously an IBM-IRCSET Exascale Postdoctoral Researcher with the Performance Engineering Laboratory (PEL) at Dublin City University (DCU). In March 2012 she was successfully awarded the PhD from Dublin City University.