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for a past academic year. Please see the current academic year for up to date information.
| Unit name |
Automation and Smart Manufacturing |
| Unit code |
MENGM0042 |
| Credit points |
10 |
| Level of study |
M/7
|
| Teaching block(s) |
Teaching Block 2 (weeks 13 - 24)
|
| Unit director |
Dr. Valero |
| Open unit status |
Not open |
| Pre-requisites |
None
|
| Co-requisites |
None
|
| School/department |
School of Electrical, Electronic and Mechanical Engineering |
| Faculty |
Faculty of Engineering |
Description including Unit Aims
Industrial automation is the use of the latest technology (mainly computing and IoT) to improve the efficiency and effectiveness of how product and services are produced and delivered. In this unit, the students learn about the principles of such technologies and how they can be organised in a coherent system to deliver product and services in a sustainable, ethical and economically viable manner.
Intended Learning Outcomes
On successful engagement with the unit the participants should be able to:
- Define (knowledge) and describe (comprehension) the constituents of modern intelligent manufacturing including concepts such as cloud manufacturing, cyber physical systems, smart products, big data analytics, digital twins, internet of things and industrial internet of things, through-life engineering and other relevant topics. [SM7M, SM8M, EA5m]
- Analyse (analysis) a manufacturing scenario (with uncertainties) individually and as a group and choose (application) an appropriate manufacturing system (automated or manual) considering sustainability, legal, ethical drivers for delivering the requirements of the scenario. [EA6M, EA7M, EL8M, EL9M, EL11M, EL12M, P11M]
- Design (creativity) the elements of the manufacturing system and synthesise (synthesis) the elements as a team to implement an intelligent manufacturing solution to the given scenario. [D9M, D10M, D11M]
- Evaluate (evaluation) the performance of their proposed solution and present (communication) the results. [P10M, G1, G4]
Teaching Information
A blended learning approach will be used in this unit where some aspects are delivered in a flipped framework with videos and other e-learning material being available before problem classes. Other aspects are delivered as lectures and practical sessions using manufacturing simulation kits.
Assessment Information
- e-Assessment (50%) to test the knowledge and comprehension of the technologies and the interaction of the legal, ethical and sustainability requirements with the enabling technologies (ILO1, ILO2). Time limited multiple choice quiz on Blackboard, single attempt with randomised questions from a question pool.
- Group presentation (50%) based on a project where the team is given a manufacturing scenario and they have to design a system to meet the production requirements of the scenario (ILO2, ILO3, ILO4).
Reading and References
Tao, F., Zhang, M. and Nee, A.Y.C., 2019. Digital Twin Driven Smart Manufacturing. Academic Press
Rawat, D.B., Brecher, C., Song, H. and Jeschke, S., 2017. Industrial Internet of Things: Cybermanufacturing Systems. Springer
Wang, L. and Wang, X.V., 2018. Cloud-Based Cyber-Physical Systems in Manufacturing. Springer International Publishing
Gilchrist, A., 2016. Industry 4.0: the industrial internet of things. Apress
