Digitalisation of Manufacturing - Research - Limerick

Masters in Digitalisation of Manufacturing
The programme is aimed at existing manufacturing, mechanical or engineering professionals, and those migrating from associated disciplines. The principal entry requirement for the Masters programme is a Level 8 honours degree, at minimum second class honours (NFQ or other internationally recognised equivalent), in a relevant engineering, computing, or technology discipline.

Study of Sole Modules
Two modules on this course can be studied seperately. These modules are Cyber-Physical Systems & IoT and Data Analytics & Machine Learning.

Year 1
Title: Cyber-Physical Systems & IoT
Credits: 5
The aim of this module is to enable the learner to programme standard ICT Boards, I/O, sensors and gateways in order to collect time-series data streams. Furthermore, the application of data stream analysis at the Board/Gateway level (edge computing) will be explored.
This module adopts an applied learning approach to understanding embedded systems, the Internet-of-things (IoT) and the cyber-physical systems (sensors, control boards) necessary for data acquisition in industrial environments.
Please note that it is possible to study this particular module on it's own.

Title: Data Analytics & Machine Learning
Credits: 5
The aim of the module is to enable the learner to program statistical, and in particular, machine learning applications, based on manufacturing data sets, using standard mathematical tools.
This module will review the application of statistics and experimental design to applications in industry. Learners will be guided through the fundamentals of the R programming language and use analytical methods to identify, analyse and solve industry related problems.
Please note that it is possible to study this particular module on it's own.

Title: Database Design & Data Visualisation
Credits: 5
This module adopts an applied learning approach to identify opportunities and work with data through the lens of the relational database model.
The aim of this module is to enable the learner to interface with standard industrial systems and collect and interpret datasets for data-driven intelligence. Therefore learners will acquire the skills necessary to design and develop database systems, collect, clean, visualise and interpret data rooted in best data analysis practice.

Title: Manufacturing Automation & Robotics
Credits: 5
This module adopts an applied learning approach to understanding the application of automation systems, Programmable Logic Controllers (PLCs), Robotics, Drives and Motors in manufacturing environments.
The aim of this module is to enable the learner to programme an industrial control system for reliable data acquisition and storage. Furthermore, the application of control system hierarchies and data exchange with Vision and Robotics Systems will be explored.

Year 2
Title: Digitalisation of Production
Credits: 5
This module will investigate the increasing digitalisation of manufacturing, from advanced product design to production process models and the use of visualisation techniques in manufacturing support. The relevant value and application of Design Tools, Digital Twins, Simulation Models, Augmented Reality/Virtual Reality, will be investigated.

Title: Integrated Database Systems
Credits: 5
This module adopts an applied learning approach to working with data integrated across a range of manufacturing systems, databases, data historians and controllers.
The aim of this module is to enable the learner to interface with distributed industry systems and collect, store and interpret datasets based at the edge, locally, remotely or on the cloud. Considerations of best practice in data security, protection, data sharing through supply-chains and data archives will be explored.

Title: Applied Research Dissertation
Credits: 60
The learner is expected to apply an innovative approach to a complex problem while collaborating with an industry partner in a professional manner. The scale of the project should be substantial and demonstrate significant added-value to the industry partner.

What are the entry requirements?
Applicants from other Level 8 degree disciplines who have a minimum of five years experiential learning in an appropriate manufacturing environment (with a demonstrable knowledge of mathematics and computing) may also apply. Their admission to the program will be determined by the Limerick Institute of Technology Recognition of Prior Learning (RPL) Process. A deep knowledge of manufacturing environments and the potential benefits and challenges facing manufacturing from digitalisation would be beneficial. An interview may form part of the selection process.

2 years