Data Analysis for Advanced Manufacturing
| Course Code: | MEC1075 |
| Mode of Delivery: | Blended |
| Cost: | €750 |
| Subsidised Cost: | €150 |
| Duration: | 12 weeks |
| Next Intake: | January 2025 |
| NFQ Level: | 9 |
| ECTS Credit Points: | 5 |
Please Note: Applicants may not apply to take more than 30 credits of micro-credentials.
In today's competitive job market, continuous upskilling and professional development has become essential for individuals seeking to stay ahead in their careers. This is especially true in the manufacturing sector, where technological advancements and industry demands are constantly evolving.
To address these needs, the School of Mechanical and Manufacturing Engineering at DCU has launched micro-credentials aimed specifically at those working in the manufacturing sector. These courses offer individuals the opportunity to acquire industry-specific skills for the 21st century, making them valuable assets in Industry 4.0/5.0 job markets.
These level 9 postgraduate modules are taught entirely online which means students can achieve a deeper understanding in a specialist area and provide a sound basis for their long-term career, without disruption to their job or other commitments. These innovative modules will deliver training on advanced manufacturing and characterisation systems using mixed reality sessions.
Data Analysis for Advanced Manufacturing
In the rapidly evolving landscape of advanced manufacturing, data analysis has become essential. Manufacturing processes generate large volumes of data, and extracting meaningful insights from this data is crucial for improving efficiency, quality, and innovation in the industry. Data analysis techniques, such as artificial intelligence and data mining, can be utilised to extract valuable knowledge and patterns from the collected data. By understanding these patterns and leveraging the power of data analysis, manufacturing processes can operate in a more intelligent way, leading to improved productivity and cost-effectiveness.
Data analysis plays a significant role in the implementation of smart manufacturing and the creation of smart factories. By integrating data analysis techniques into manufacturing processes, companies can optimise operations, reduce risks, and improve decision-making.
As the manufacturing industry embraces advanced technologies and data-driven processes, professionals with expertise in data analysis have become vital. This module aims to equip students with the data analysis skills required for Industry 4.0/5.0.
Students on this course will become familiar with the Big data and Machine Learning tools for data analysis that are being used in Industry 4.0 and advanced manufacturing. They will also get training on the use of data analysis tools for real-world challenges for specific application areas.
This course covers the following content:
| Introduction to Data Analysis for Industry 4.0 | Statistical Design of Experiments; Factorial Design; Box-Behnken Response Surface Methodology; Data Analysis Requirements for Industry 4.0/5.0 |
| Predictive Analysis | Introduction to Predictive Analysis for Industry 4.0; Artificial Neural Network and Adaptive Neuro-Fuzzy Inference System; Machine Learning in Industry 4.0 |
| Data Analysis Case Studies | Data analysis for Laser-based Material Processing Techniques; Data analysis for Defect |
On successful completion of this micro-credential, the student will be able to:
- Design data analysis tools for Advanced Manufacturing
- Formulate experimental design and analysis methods to determine processing factors impact on response
- Apply and evaluate data analysis tools for discrete advanced manufacturing scenarios
- Apply Artificial Intelligence tools for process optimisation
A Primary Honours degree, Level 8 in Electronic/Electrical/Computer Engineering, Applied Physics, Computer Sciences or other Cognate/Engineering Disciplines. Applications are also invited from diverse educational and/or employment backgrounds, with applications evaluated on a case-by-case basis.
And also to indicate the required documentation:
- Please provide Academic Transcripts for final year of study where appropriate (English translation)
- All applicants must submit a copy of their passport
There is no availability for a deferred entry onto a micro-credential.
If applicable, evidence of competence in the English language as per DCU entry requirements. Please see here.
For further information regarding the HCI learner subsidy eligibility criteria please click here. (https://hea.ie/skills-engagement/hci-pillar-3-micro-credentials-learner-fee-subsidy/).
For information on how to apply for this micro-credential, please visit our Application Guide
Closing date for applications: 13th December 2024