Through hands-on learning, students will develop the knowledge and skills needed to effectively operate and manage enterprises based on intelligent manufacturing and industry 5.0.

Students aspiring towards leadership roles in manufacturing are encouraged to join the course. Students will be given an opportunity to develop this vision by taking modules in Enterprise Simulation for Digital Twinning, Intelligent Data-enabled Manufacturing, and Robotics and Automated Systems.

At the end of the course, students will be able to:

• Identify cases in an industry where intelligent manufacturing is possible in the near or medium term.
• Implement a pathway towards intelligent manufacturing and industry 5.0.
• Analyse how autonomous decision-making is made using real-time data in intelligent manufacturing systems.
• Diagnose problems by thinking critically, innovating and collaborating through team-based work.
• Evaluate, through written and oral communication, technical findings concerning Industry 5.0.
• Value life-long personal and professional attributes including communication, interpersonal, analytical, enterprising and problem-solving skills in vibrant, technologically advanced economies.

The Manufacturing Process
The manufacturing process involves transforming materials into functional components, which are assembled through sustainable, intelligent, manufacturing systems into products. These products are designed to meet specific market needs. Our new advanced manufacturing diplomas respond to employee skills needs at every stage of this process. See the chart below for an overview of related courses and how they align within the overall manufacturing process.

The course consists of three 10 ECTS modules:  

• Enterprise Simulation for Digital Twinning with Project
  Enterprise simulation is the process of building digital models of whole or part of an enterprise with process models, data models, resource models and/or new processes etc. Digital Twinning deals with the process of understanding an enterprise and improving its performance through creation of computer simulations. It is based on knowledge of the enterprise, its infrastructure, technology and human resources. 
  
  
• Robotics & automated systems with Project 
  This module aims to enable the learner to describe core elements of automated systems including Robotics, AGVs and Medical device processing equipment, understand project management techniques used in automation and learn some basic robotic programming.  
  
  
• Intelligent Data-Based Manufacturing with Project 
  The transformation of manufacturing by Machine Learning and Artificial Intelligence is inevitable. This module presents a methodology to accelerate ways to smarter, sustainable and digital manufacturing using intelligent manufacturing systems. 

NB: You can take some of the modules listed above as individual standalone micro-credentials. Please see related courses section at the bottom of the webpage. 

Curriculum Information

Each module features a substantial workplace project component, and students are encouraged to join the course with an industry-based project concept. This approach provides valuable opportunities to build transferable skills that can be applied directly in professional settings.

Dr Adam Collins
Lecturer, School of Natural Sciences, Physics

Padraig Conneely
Lecturer, School of Engineering, Mechanical Engineering

The course is delivered part-time through a blended learning approach. Learners will be provided with online materials for each module, specifically developed for independent study. These will be complemented by recommended readings and interactive resources where relevant. In-person attendance is required for approximately 10 hours per module, typically scheduled on Saturdays.

Assessment is carried out through a combination of assignments, written examinations, and, where applicable, practical laboratory work. Examinations are scheduled at the end of each semester, and each module is assessed individually.

Course Administrator
Tel: 091 493909 
Email: sciencetech@universityofgalway.ie

If you do not meet the standard entry criteria for this course, you may gain entry through our Recognition of Prior Learning (RPL) policy. Applicants may also be able to earn module exemptions based on their prior learning. Find out more here.

Job readiness is integrated across all modules through group work, problem-solving assignments, conflict resolution discussions, and leadership opportunities in team projects. 

Experiential learning, including immersion in labs and opportunities for work-based projects, helps learners develop essential transversal skills such as teamwork, communication, creativity and innovation.

Applicants should have a Diploma at NFQ Level 7 of 90 ECTS minimum, in a Science, Engineering or Technical area, or otherwise prove that they satisfy the modules' prerequisites as listed in the course outline section.

Entry requirements for part-time students can be found here (i.e. Age, English language requirements, etc.). 

Applications are made online via the University of Galway Applications System. This course is listed under Adult Learning Undergraduate\Postgraduate, CPD, Micro-credentials & Summer School Applications.

Please visit our How to Apply page for Application tips and Supporting Documents information.

Fees for Academic Year 2026/27

The HEA Micro-credential Learner Fees Subsidy funds this course for micro-credentials and Diplomas between 5 and 30 credits. Candidates who satisfy the HEA eligibility criteria are funded at 80% for this course. Funding is subject to availability of places at the time of application.