ENG2006 | 2021/2 | University of Exeter

MODULE TITLE	Industry 4.0	CREDIT VALUE	15
MODULE CODE	ENG2006	MODULE CONVENER	Dr Halim Alwi (Coordinator)

DURATION: TERM	1	2	3
DURATION: WEEKS		11

Number of Students Taking Module (anticipated)

DESCRIPTION - summary of the module content

Industry 4.0 or the “fourth industrial revolution” is the trend towards automation and data exchange in new manufacturing technologies - to deliver so called smart manufacturing. In this module you will be given an introduction to smart manufacturing, the mathematical tools behind it and how it can be applied to real world manufacturing problems.

The teaching style in this module emphasises hands on learning. For example, you will learn how to manipulate a desktop robot to perform automated tasks. The module will build on mathematical and programming skills developed in the first year and modelling of engineering systems in the second year. Assessment in this module is 100% coursework and is based around 2 practical build activities built around real world engineering problems.

AIMS - intentions of the module

The aim of this module is to introduce the fundamental principles behind industry 4.0, with a hands on practical approach.

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

ILO #	Intended Learning Outcome	*AHEP ILO - MEng**	AHEP ILO - BEng
ILO #1	Understand the key economic drivers behind industry 4.0/smart manufacturing, including knowledge of good industrial case studies.	D1m, ET2m	D1p, ET2p
ILO #2	Understand principle mathematical tools in handling data	SM2m, EA3, EA5m	SM2p, EA3p
ILO #3	Understand basic principles, and know-how to program a simple neural network / regression based model, for learning simple automated tasks.	SM2m, EA2m, Ea3m, D3m, D4m, EP1m	SM2p, EA3p, SM2p, D3p, D4p, EP1p, EP8p
ILO #4	Learn the basic principle and mechanism of a robot manipulator, and be able to control it to do simple tasks.	SM2m, SM4m, SM5m, EA2m, EA3m, EA4m	SM2p, EA1p, EA2p, EA4p, D4p, EP1p, EP2p, EP3p, G1p
ILO #5	Understand basic principles and algorithms for machine vision		SM2p, EA2p, D4p
ILO #6	Apply machine vision for an engineering problem in pattern / object recognition
ILO #7	Develop the ability to understand complex mathematical methods in the context of real-world engineering problems		SM2p, D4p, G1p, G2p
ILO #8	Develop strong programming skills	SM5m, EA3m	SM2p, EP3p
ILO #9	Develop presentation skills to technical and non-technical audience		D6p
ILO #10	Work effectively as a group	EP11m	EP9p, G4p
*Engineering Council Accreditation of Higher Education Programmes (AHEP) ILOs for MEng and BEng Degrees

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

1: Introduction to Smart Manufacturing;

2: Introduction to Data Analysis and Artificial Intelligence;

3: Modelling to Make Sense of Data;

4: Sensors;

5: Robotic Control;

6: Machine Vision and its Applications;

7: Neural Networks, Model Fitting and Sensitivity Analysis.

LEARNING AND TEACHING

LEARNING ACTIVITIES AND TEACHING METHODS (given in hours of study time)

Scheduled Learning & Teaching Activities	24	Guided Independent Study	126	Placement / Study Abroad

DETAILS OF LEARNING ACTIVITIES AND TEACHING METHODS

Category	Hours of study time	Description
Scheduled Learning and Teaching Activities	11	Weekly lectures
Scheduled Learning and Teaching Activities	11	Weekly programming tutorials
Scheduled Learning and Teaching Activities	2	Practical Lab Sessions
Guided Independent Study	126

ASSESSMENT

FORMATIVE ASSESSMENT - for feedback and development purposes; does not count towards module grade

Form of Assessment	Size of Assessment (e.g. duration/length)	ILOs Assessed	Feedback Method
Weekly Problem Sheets	2 hours	2, 3

SUMMATIVE ASSESSMENT (% of credit)

Coursework	100	Written Exams	0	Practical Exams

DETAILS OF SUMMATIVE ASSESSMENT

Form of Assessment	% of Credit	Size of Assessment (e.g. duration/length)	ILOs Assessed	Feedback Method
Coursework - Robotics	45	4000-word report (less than 10 A4 pages)	1-4, 7-8	eBart
Coursework - Machine Vision	45	Approximately 1000 lines of Python code (maximum)	2, 3, 5-10	eBart
Coursework - Smart manufacturing	10	700-word report	1, 2	eBart

DETAILS OF RE-ASSESSMENT (where required by referral or deferral)

Original Form of Assessment	Form of Re-assessment	ILOs Re-assessed	Time Scale for Re-reassessment
Coursework	Re-submission of failed coursework (100%)	All	August Ref/Def Period

RE-ASSESSMENT NOTES

Ref/Def assessment is via resubmission of failed coursework in August.

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

Reading list for this module:

There are currently no reading list entries found for this module.

CREDIT VALUE	15	ECTS VALUE	7.5

PRE-REQUISITE MODULES	None
CO-REQUISITE MODULES	None

NQF LEVEL (FHEQ)	5	AVAILABLE AS DISTANCE LEARNING	No
ORIGIN DATE	Friday 8th January 2021	LAST REVISION DATE	Monday 28th March 2022

KEY WORDS SEARCH	None Defined

Industry 4.0 - 2021 entry