Study information

Smart Production Systems - 2023 entry

MODULE TITLESmart Production Systems CREDIT VALUE15
MODULE CODEENGM021 MODULE CONVENERDr Baris Yuce (Coordinator)
DURATION: TERM 1 2 3
DURATION: WEEKS 11
Number of Students Taking Module (anticipated) 150
DESCRIPTION - summary of the module content
The concept of a smart production systems emerged from the future factories, future cities and autonomous and adaptive robotic systems production philosophies that then has been supported with recent technological advances in IoT systems, communication technologies, high -performance computing, intelligent systems and algorithms and augmented reality. The concept initially developed and applied on the Industry 4.0 framework which is the 4th industrial revolution to digitise the manufacturing environment to provide optimal production conditions for the manufacturing environment and interoperability between cyber and physical systems. Later, this philosophy has been enhanced for different systems which has paved new enhancements and philosophies like digital twins, smart cities and 4.0 frameworks for manufacturing systems. The module is an interdisciplinary module that covers the manufacturing and production systems, applications of IoT systems, wireless communications systems and microcontroller applications, cyber-physical systems and overall smart production architectures in production systems and smart cities.
 
By the end of the module, you will have a good understanding of digitalised manufacturing and service systems, cyber and physical systems, cloud computing, digital twin concept and artificial intelligence applications in manufacturing systems and smart cities which will be underpinned with several use cases, practical applications and projects.   
 
Pre-requisite or Co-requisite modules: None. 
AIMS - intentions of the module

This module aims to provide essential knowledge in the fields of the smart systems and their application in smart production and city concepts, and detailed understanding for the Industry 4.0 framework and its applications in several enabling areas like smart logistics management, smart building and smart energy managements systems and realworld examples.  Further, students will have an opportunity to develop smart solutions using artificial intelligence techniques, high-performance computing technologies and sensory based systems for different industries including manufacturing, logistics, water, energy and built environments.

INTENDED LEARNING OUTCOMES (ILOs) (see assessment section below for how ILOs will be assessed)

This is a constituent module of one or more-degree programmes which are accredited by a professional engineering institution under licence from the Engineering Council. The learning outcomes for this module have been mapped to the output standards required for an accredited programme, as listed in the current version of the Engineering Council’s ‘Accreditation of Higher Education Programmes’ document (AHEP-V3). On successful completion of this module, the following learning outcomes will be achieved: SM1m, SM3m, SM5m, SM6m, SM1fl, SM3fl, EA1mEA5m, EA1fl, EA2fl, D3m, D4m, D7m, D8m, D1fl-D3fl, EP2m, EP4m, EP9m, EP1fl, EP2fl, G1m-G4m, G1fl-G4fl.


Module Specific Skills and Knowledge: SM1m, SM1fl, EA1m-EA5m, EA1fl, EA2fl, EA3fl, D3m, D1dl.

1 Understanding manufacturing and production systems and various business types.

2 Grasp the Industry 4.0 framework, 4.th industrial revolution, Smart Factories and Smart Cities concepts.

3 Understand the new business models in Industry 4.0 frameworks and Smart Cities concepts.

4 Understand the key elements of the Industry 4.0 framework including sensing infrastructure, IoT connectivity, and networking, cyber and physical systems.

5 Grasp the digital twin concept and overall architecture of the physical systems.  

Discipline Specific Skills and Knowledge: SM3m, SM5m, SM6m, SM3fl, D4m, EP2m, EP4m, EP9m, EP1fl, EP2fl.
 
6 Understand the concepts of Artificial Intelligence technologies and apply in Industry 4.0 frameworks and Smart Cities.

7 Demonstrate the Big Data applications in future manufacturing and engineering environment including, the industries supported with Industry 4.0 frameworks or Smart Cities technologies.

8 Understand engineering and industrial requirements of the Cybersecurity in production environment supported with Industry 4.0 frameworks and Smart Cities concepts.

9 Analyse the requirements of the new business models for the industries supported with Industry 4.0 frameworks.  

Personal and Key Transferable/ Employment Skills and Knowledge: D7m, D8m, D2fl, D3fl, G1m-G4m, G1flG4fl.

10 Apply enhanced problem-solving ability and illustrate in Industry 4.0 laboratory applications 

11 Develop communication skills.

12 Demonstrate report writing skills, project management and organizational skills.

SYLLABUS PLAN - summary of the structure and academic content of the module

Introduction to production systems.

4th Industrial revolution, Production Industry 4.0 framework, Smart Factories and Smart Cities concepts.

Manufacturing process, Quality Control and Supply Chain Management in Industry 4.0 framework.

Introduction to sensing and actuation, and IoT technologies (connectivity and networking).

Digital twins and Cyber-Physical systems.

Artificial Intelligence technologies, (Artificial Neural Network, Fuzzy Logic, Genetic Algorithm and others).

Big Data Analytics in Industry 4.0 framework and Smart cities.

Cybersecurity in its applications Industry 4.0 and Smart cities.

Industry 4.0 framework laboratory applications
 
 

LEARNING AND TEACHING
LEARNING ACTIVITIES AND TEACHING METHODS (given in hours of study time)
Scheduled Learning & Teaching Activities 33 Guided Independent Study 117 Placement / Study Abroad
DETAILS OF LEARNING ACTIVITIES AND TEACHING METHODS
Category                                                                  Hours of Study Time         Description       
Scheduled learning and teaching activities 22 Lectures
Scheduled learning and teaching activities 7 Tutorials
Scheduled learning and teaching activities 4 Laboratories
Guided independent study 117 Guided independent stud

 

ASSESSMENT
FORMATIVE ASSESSMENT - for feedback and development purposes; does not count towards module grade
SUMMATIVE ASSESSMENT (% of credit)
Coursework 0 Written Exams 100 Practical Exams
DETAILS OF SUMMATIVE ASSESSMENT
Form of assessment % of credit          Size of the assessment e.g. duration/length       ILOs assessed     Feedback method
Written exam - closed note 100 3 hours - summer exam period All Oral, by request

 

DETAILS OF RE-ASSESSMENT (where required by referral or deferral)
Original form of assessment     Form of re-assessment     ILOs-reassesed   Time-scale for assessment
All above Written exam (100% - 3 hours) All August Ref/Def period

 

RE-ASSESSMENT NOTES

Reassessment will be by a single written exam only worth 100% of the module. For deferred candidates, the mark will be uncapped. For referred candidates, the mark will be capped at 50%.

RESOURCES
INDICATIVE LEARNING RESOURCES - The following list is offered as an indication of the type & level of
information that you are expected to consult. Further guidance will be provided by the Module Convener

Web-based and electronic resources:  ELE – https://vle.exeter.ac.uk/

Reading list for this module:

Type Author Title Edition Publisher Year ISBN
Set Armendia, M, Ghassempouri, M, Ozturk, E and Peysson F Digital Twin Approach to Improve Machine Tools Lifecycle Springer Nature 2019
Set Bessis, N and Dobre, C Big Data and Internet of Things: A Road map for Smart Environments Springer International Publishing 2014
Set Dehghantanha, A and Raymond Choo, K K Handbook of Big Data and IoT Security Springer International Publishing 2019
Set Ejaz, W and Anpalagan, A Internet of Things for Smart Cities: Technologies, Big Data and Security Springer International Publishing 2019
Set Guo, S and Zeng, D Cyber-Physical Systems: Architecture, Security and Application Springer International Publishing 2019
Set Mathur, P Machine Learning Applications Using Python: Case Studies from Healthcare, Retaila and Finance Apress 2019
Set Mohammed, M, Khan, M B, Bashier, E and Bashier, M Machine Learning Algorithms and Applications CRC Press 2017
Set Sendler, U The internet of Things: Industrie 4.0 Unleashed Springer-Verlag 2016
Set Slack, N, Brandon-Jones, A and Johnston, R Operations Management 7th Pearson Education 2013
Set Sun, H, Wang, C and Ahmad, B From Internet of Things to Smart Cities: Enabling Technologies CRC Press; Chapman and Hall 2017
CREDIT VALUE 15 ECTS VALUE
PRE-REQUISITE MODULES None
CO-REQUISITE MODULES None
NQF LEVEL (FHEQ) 7 AVAILABLE AS DISTANCE LEARNING No
ORIGIN DATE Tuesday 14th May 2019 LAST REVISION DATE Thursday 26th January 2023
KEY WORDS SEARCH Industry 4.0, smart cities, cyber physical systems, production systems

Please note that all modules are subject to change, please get in touch if you have any questions about this module.