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 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&2 and continues as a stand-alone module in semester 3 and 4 under the guidance of an individual supervisor.Structure of the programmeIn 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.
| Course Category | Engineering, Construction & Engineering |
| Course Type | Online Learning |
| Course Qualification | Masters Degree |
| Course Start Date | 1st January 1970 |
| Course Duration | 2 years |
| Course Time | Part-time |
| Course Fee | 6300 |
| Entry Requirements | Candidates must hold level 8 Bachelor (Hons) degree or Higher Diploma in Automation & Digital Manufacturing or a B.Eng. (Hons) in Mechatronics or cognate discipline with a minimum grade classification of H2.2 or equivalent. As the research is industry based, applicants must either have the support of their employer to conduct research or have an agreement with a company to use their facilities for the purpose of their research. The outline of the project must be agreed in advance of admission and an interview to discuss the validity of the project will be conducted. All potential applicants should contact Dr. Carine Gachon carine.gachon@atu.ie English Language Requirements: English Language Requirements will be as determined by ATU and as published in the Access, Transfer and Progression code. The current requirements are as follows: Non-EU applicants who are not English speakers must have a minimum score of 6.0 (with a minimum of 6.0 in each component) in the International English Language Testing System (IELTS) or equivalent. All results must have been achieved within 2 years of application to ATU. EU applicants who are not English speakers are recommended to have a minimum score of 6.0 (with a minimum of 6.0 in each component) in the International English Language Testing System (IELTS) or equivalent. Further details on English language requirements are available Recognition of Prior Learning ATU is committed to the principles of transparency, equity and fairness in recognition of prior learning (RPL) and to the principle of valuing all learning regardless of the mode or place of its acquisition. Recognition of Prior Learning may be used to: gain access or advanced entry to the programme gain credits and exemptions from programme modules after admission in award years RPL will be considered to a maximum of 50% of the credits. Engineers with significant industry experience who can demonstrate either certified or experiential learning (or combination of both) in Lean Automation, Data Driven Decision making and/or System Integration can get exemptions from the relevant taught modules and potentially shorten the duration of the programme. |
A 60 credit masters programme designed for professionals working in areas that cater for people with palliative and/or end of life care needs.
This course is free/ funded under the Springboard+ Initiative.
This is an innovative programme that has been designed in close consultation with manufacturing industry in the western region who have identified a requirement to up-skill their employees.
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