Module Database Search



MODULE DESCRIPTOR
Module Title
Mechatronics and Automation
Reference EN3551 Version 4
Created May 2022 SCQF Level SCQF 9
Approved June 2021 SCQF Points 15
Amended June 2022 ECTS Points 7.5

Aims of Module
To provide student the ability to demonstrate mechatronics and its automation systems.

Learning Outcomes for Module
On completion of this module, students are expected to be able to:
1 Demonstrate a comprehensive understanding and design process of mechatronic systems and their relationship with automation applications.
2 Critically analyse various components such as electrical and mechanical sensors, actuators, and electrical motors for mechatronics and automation systems.
3 Demonstrate the design and analysis of mechatronic systems and its implementation in the form of automation systems in either laboratory or software based settings.

Indicative Module Content
Introduction to mechatronics: examples of mechatronic systems, automation concepts, design approaches. Mechanical components of motion, hydraulic, pneumatic, and mechanical actuation systems. Modelling of mechatronic systems. Sensors & Actuators: theory and operation, types of sensors and transducers, sensor/actuator selection, technologies and applications, MEMS. Motors: Special motors; Stepper motors, types, principles, characteristics, and control; Switched reluctance motors, principles and applications; Brushless dc motors; Universal motor; Hysteresis motor; Synchronous reluctance motor; Servomotors and drives; Motor selection. PLCs: Configuration and programming.

Module Delivery
Full-time students: This module is delivered by a combination of lectures and tutorials. It will be supported by practical examples and activities including computer based laboratory exercises. Part-time students: This module is delivered by a combination of lectures and tutorials online. It will be supported by drop-in evening sessions and labs on campus. Assessments will primarily be online although exams will be held on campus with the full-time cohorts.

Indicative Student Workload Full Time Part Time
Contact Hours 48 48
Non-Contact Hours 102 102
Placement/Work-Based Learning Experience [Notional] Hours N/A N/A
TOTAL 150 150
Actual Placement hours for professional, statutory or regulatory body    

ASSESSMENT PLAN
If a major/minor model is used and box is ticked, % weightings below are indicative only.
Component 1
Type: Coursework Weighting: 75% Outcomes Assessed: 2, 3
Description: Lab-based coursework exercises and reports.
Component 2
Type: Examination Weighting: 25% Outcomes Assessed: 1
Description: Closed book examination.

MODULE PERFORMANCE DESCRIPTOR
Explanatory Text
The module has 2 components and to gain an overall pass a minimum D grade must be achieved in each component. The component weighting is as follows: C1 is worth 75% and C2 is worth 25%.
Examination:
Coursework: A B C D E F NS
A A A A B E E
B B B B B E E
C B C C C E E
D C C D D E E
E E E E E E E
F E E E F F F
NS Non-submission of work by published deadline or non-attendance for examination

Module Requirements
Prerequisites for Module EN2510 or equivalent (Electronic and Electrical Engineering students). EN1562 or equivalent (Mechanical and Electrical Engineering students).
Corequisites for module None.
Precluded Modules None.

INDICATIVE BIBLIOGRAPHY
1 Isermann, Rolf. Mechatronic Systems. London: Springer London, Limited, 2007. Web.
2 Regtien, Paul P. L, and Dertien, Edwin. Sensors for Mechatronics. 1st ed. San Diego: Elsevier, 2018. Elsevier Insights.
3 Crowder, Richard M. Electric Drives and Electromechanical Systems : Applications and Control / [internet Resource]. Second ed. Kidlington, Oxford; Cambridge, MA: Butterworth-Heinemann, 2020.
4 Hughes, Austin, and Drury, Bill. Electric motors and drives: fundamentals, types, and applications. 5th ed. Kidlington: Newnes, an imprint of Elsevier, 2019.
5 Bolton, W. Programmable Logic Controllers. 6th ed. Cambridge: Elsevier Science & Technology, 2015.
6 Awrejcewicz, J, et. al. Mechatronics: Ideas, Challenges, Solutions and Applications. Springer, 2015.
7 DORF, R.C. and BISHOP, R.C., 2017. Modern Control Systems. 13th ed. London: Pearson Education.
8 DU, K.L. and SWAMY, M.N.S., 2006. Neural Networks in a Softcomputing Framework. London: Springer.


Robert Gordon University, Garthdee House, Aberdeen, AB10 7QB, Scotland, UK: a Scottish charity, registration No. SC013781