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Unit information: Automation and Smart Manufacturing in 2020/21

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 Department of Mechanical Engineering
Faculty Faculty of Engineering

Description

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:

  1. 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]
  2. 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]
  3. 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]
  4. Evaluate (evaluation) the performance of their proposed solution and present (communication) the results. [P10M, G1, G4]

Teaching details

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 Details

  • 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

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