Engineering - Automation & Digital Manufacturing - Galway

Course code: GA_EADMG_V09
QQI level: Level 9
NFQ type: Level 9 NFQ
Duration: 2 years part-time, online delivery. Study Hours In semesters 1 and 2, students attend 4 hours of online synchronous workshops per week and engage in 6 hours of asynchronous material per week. The Research Project is fully integrated in the taught modules in semesters 1 and 2 and continues as a stand-alone module in semesters 3 and 4 under the guidance of an individual supervisor. On-Campus Attendance: No attendance required.
Attendance: Online or Distance
CAO points: —

Degree - Masters (Level 9 NFQ)

Galway

NFQ Level 9

Course summary

This programme is part of a suite of programmes developed with Industry to support the transition to Industry 4.0. It is specifically designed for engineers working in the manufacturing industry who wish to upskill in the field of Automation and Digital Manufacturing.

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.