BIO09093 2021 Introduction to BioIndustry 4.0
Full Title
Introduction to BioIndustry 4.0
Transcript Title
Introduction to BioIndustry 4.
Code
BIO09093
Attendance
N/A %
Subject Area
BIO - Bio Tech/Eng/Chem
Department
LIFE - Life Sciences
Level
09 - Level 9
Credit
05 - 05 Credits
Duration
Semester
Fee
€
Start Term
2021 - Full Academic Year 2021-22
End Term
9999 - The End of Time
Author(s)
Mary Butler
Programme Membership
SG_SBIOI_E09 202100 Postgraduate Certificate in BioIndustry 4.0
SG_SVALI_O09 202300 Postgraduate Diploma in Science in Validation and Digitalisation Technologies
SG_SVALI_M09 202300 Master of Science in Validation and Digitalisation Technologies
SG_SBIOI_M09 202300 Master of Science in BioIndustry 4.0
SG_SVALD_O09 202300 Postgraduate Diploma in Science in BioPharmaceutical Validation and Digitalisation
Description
This module aims to provide students with the background of Industry 4.0 and how this conceptual framework can be applied in the biopharmaceutical sector. The course will provide students with the knowledge and understanding of the emerging needs of the biopharmaceutical sector as it progresses towards greater integration of technology and data, to become more agile, to increase productivity and competitiveness.
Learning Outcomes
On completion of this module the learner will/should be able to;
1.
Demonstrate they have detailed knowledge and understanding of the background to Industry 4.0 and emerging needs in the biopharma sector, the source and quality of existing data and applicability of industry4.0
2.
Demonstrate they have detailed knowledge and understanding of the application of predictive modelling, automation systems, PLCs, robotics, vision systems
3.
Evaluate embedded systems, the internet of things (IoT) and the cyber-physical systems (sensors, control boards) necessary for data acquisition
4.
Formulate judgements on the relevant value and application of existing data sources, design tools, digital twins, simulation models, and augmented reality/virtual reality.
5.
Integrate knowledge and formulate judgements on the application of robotics and industrial vision systems to biomanufacturing operations.
Teaching and Learning Strategies
This module will be taught using on‑line lectures. A range of Computer‑Aided Learning (CAL) packages are also used to support this module (e.g. Moodle,Adobe Connect, Panopto, Camtasia). Students are provided with electronic materials for self‑assessment and preparation for assessments/assignments. Self‑directed, student‑centred, independent learning is a core aspect through completion of module coursework.
Module Assessment Strategies
The assessment approach for this module will be 100% continuous employed including some of the following: Enquiry based Projects, Assignments/mini projects including Viva/Presentation Short-form assessment exams incl. MCQs, Short answer and Long Answer Questions.
Repeat Assessments
Students will have opportunities to re-submit work as agreed with their lecturer.
Indicative Syllabus
The following is a summary of the main topics included in this module: Industry 4.0 and the Industrial Revolutions, Regulatory Considerations, Automation & Process Control, Networking and Cloud Computing, AR & VR, Collaborative Robotics & Machine Learning, Data Analytics and Visualization, Cyber-Physical systems, Blockchain & Location systems (RFID).
Coursework & Assessment Breakdown
Coursework & Continuous Assessment
100 %
Coursework Assessment
| Title | Type | Form | Percent | Week | Learning Outcomes Assessed | |
|---|---|---|---|---|---|---|
| 1 | MCQ 1 | Coursework Assessment | Multiple Choice/Short Answer Test | 20 % | Week 8 | 1,2,3,4 |
| 2 | End of Semester Assessment | Coursework Assessment | Assignment | 30 % | Week 11 | 1,2,3,4,5 |
| 3 | Project & Viva | Project | Project | 50 % | Week 12 | 1,2,3,4,5 |
Part Time Mode Workload
| Type | Location | Description | Hours | Frequency | Avg Workload |
|---|---|---|---|---|---|
| Lecture | Online | Lecture | 2 | Weekly | 2.00 |
| Independent Learning | Not Specified | Self Study | 5 | Weekly | 5.00 |
Total Part Time Average Weekly Learner Contact Time 2.00 Hours
Module Resources
Non ISBN Literary Resources
Journal Resources
URL Resources
|
German Federal Government Digital Strategy, 2015.
Industry 4.0 – Strategy Implementation Recommendation to German Government.
Study on digitalisation of the manufacturing sector and the policy implications for Ireland 2018.
Ireland’s Industry 4.0 Strategy 2020-2025
Maher, M. (2021) MSD Brinny Focused on Creating an Exciting Digital Future. The Irish Times.
Sanofi.com. (2018) Digital Transformation in Healthcare. |
Other Resources
None
Additional Information