Master of Engineering in Automation and Digital Manufacturing

This programme is part of a suite of programmes developed with Industry to support the transition to Industry 4.0. The Master is a part-time programme specifically designed for engineers working in the manufacturing industry who wish to up-skill in the field of Automation and Digital Manufacturing. Students will take 40 credits of taught modules which will have assessments contributing to their 50 credits work-based research project.

The programme will be delivered on a part-time basis over 2 years divided in 4 semesters. In semester 1 and 2, students attend 4 hr of online synchronous workshops per week and engage in 6 hr of asynchronous material per week. The Research Project is fully integrated in the taught modules in semesters 1&2 and continues as a stand-alone module in semester 3 and 4 under the guidance of an individual supervisor.

Structure of the programme

In semester 1, students take on three taught modules concentrating on:

• Research Methods where they will conduct a literature review and develop a project plan for their Research Project by the end of the semester,
• Lean Automation where they will analyse and optimise flow and variation in the manufacturing process they are planning to automate/digitalise.
• Data Driven Decision-Making that will work in parallel with Lean Automation to identify the key data that needs to be captured from the manufacturing process and determine how these data should be utilised to support decision-making.

In Semester 2, students take on a new taught module and continue with two of the first semester modules, concentrating on:

• Lean automation is integrated with the Research Project to ensure that the automated process is optimised from a Lean and Six Sigma point of view.
• Data Driven Decision-Making is integrated with the Research Project to investigate the data analytics side of the Research Project.
• System Integration supports the Research Project in the design of the data architecture of the process and the selection of hardware and software.
• In Semester 3 and 4 The Research Project continues under the guidance of the individual supervisor.