Certificate in Intelligent Manufacturing Systems

Cork Institute of Technology (CR_ENIMS_9)
Key Programme Details
Award

Special Purpose Award

NFQ Level

Level 9 About NFQ

Delivery Method

Online

Mode

Part Time

ECTS Credits

30

Department

CAMMs,CIT

General Information
Contact

Mike McGrath

Email

michael.mcgrath@cit.ie

Phone

021.432 6756

Address

CIT , Bishopstown Cork

Role

CAMMs Manager

Important Dates
Application Deadline

21/08/2020

Start Date

28/09/2020

End Date

07/05/2021

About this Course

The programme aspires to bridge the gap between engineering operations and information technology paradigms in the manufacturing sector. It is described as the synthesis of advanced manufacturing capabilities and digital technologies to produce highly customizable products faster, cheaper, better, and greener. A smart factory integrates data from system-wide physical, operational, and human assets to drive manufacturing, maintenance, inventory tracking & the digitization of operations. The results are more efficient and agile systems with less production downtime, and a greater ability to predict/adjust to changes in the facility or broader network leading to better positioning in the marketplace.

New roles with capabilities such as virtual or augmented reality and data extraction, organisation, analysis and visualization will be required. Managing changes to people and processes require an agile and adaptive change management plan ensuring that employees are trained in the ever-evolving new skills needed to deliver these aspirations.

The programme has been specifically designed in response to industry needs for upskilling as identified by SWRSF. A key output from this forum specifically in connection with the Industry 4.0 skills competency matrix is that all functional roles (e.g. Engineering, technician, science, quality, regulatory, IT, data science) are undergoing continual evolution, driven by the new and emerging technologies. The primary evolving and emerging skillsets include Internet of Things (IoT) systems development and integration, machine learning, data management and advanced analytics, Instrument/ sensor design, electromechanical, process optimisation and quality systems design.

Participants will acquire skills necessary to contribute effectively to operate in the factory of the future, bringing manufacturing through to the next level envisaged by Industry 4.0. They will acquire specific knowledge of the new and emerging areas and how to integrate IT with Manufacturing Technology, and how to benchmark and compare best industrial practice using data and information analytics.

Entry Requirements

Candidates will require a Level 8 qualification in Mechanical, Electrical, Electronic, Chemical Engineering, Applied Physics and Instrumentation, Mechatronics or cognate discipline.

Candidates with sufficient experience which in the judgement of CIT may be deemed equivalent to this qualification will be considered following the principles/procedures set out the Institute’s Recognition of Prior Learning service in CIT (see https://www.cit.ie/rpl ).

Long Description

The programme aspires to bridge the gap between engineering operations and information technology paradigms in the manufacturing sector. It is described as the synthesis of advanced manufacturing capabilities and digital technologies to produce highly customizable products faster, cheaper, better, and greener. A smart factory integrates data from system-wide physical, operational, and human assets to drive manufacturing, maintenance, inventory tracking & the digitization of operations. The results are more efficient and agile systems with less production downtime, and a greater ability to predict/adjust to changes in the facility or broader network leading to better positioning in the marketplace.

New roles with capabilities such as virtual or augmented reality and data extraction, organisation, analysis and visualization will be required. Managing changes to people and processes require an agile and adaptive change management plan ensuring that employees are trained in the ever-evolving new skills needed to deliver these aspirations.

The programme has been specifically designed in response to industry needs for upskilling as identified by SWRSF. A key output from this forum specifically in connection with the Industry 4.0 skills competency matrix is that all functional roles (e.g. Engineering, technician, science, quality, regulatory, IT, data science) are undergoing continual evolution, driven by the new and emerging technologies. The primary evolving and emerging skillsets include Internet of Things (IoT) systems development and integration, machine learning, data management and advanced analytics, Instrument/ sensor design, electromechanical, process optimisation and quality systems design.

Participants will acquire skills necessary to contribute effectively to operate in the factory of the future, bringing manufacturing through to the next level envisaged by Industry 4.0. They will acquire specific knowledge of the new and emerging areas and how to integrate IT with Manufacturing Technology, and how to benchmark and compare best industrial practice using data and information analytics.

Timetable Info

To be finalised during early September and shared with students at that point. Classes will be delivered two evenings per week 6.30pm - 9.30pm , ( Mon - > Thurs ) .All classes will be accessible on line thereafter. Examinations on Line also at this point.

Delivery Location

On Line

Delivery Notes

Online

Semester 1 Modules :
Automation with Python
Industrial Data Analysis

Semester 2 Modules :
Robotics and Autonomous Systems
Machine Prognostics

Application Procedures

Apply through www.springboard.ie