Modules
Programme structure
During the first two years, you will study six modules per year across a variety of general engineering.
At the end of the second year, you'll choose which stream to study for years three and four:
 mechanical engineering
 electronics
 electromechanical engineering
 software engineering
Please note: While we make every effort to provide our prospective students and applicants with the most up to date and accurate module information for the coming academic years, you should be aware that the information provided is subject to change.
Teaching on the programme finishes in June and is followed by a thorough annual review of all modules and assessment methods. During this review period we encourage feedback from the students to support us in the development of the programme and potential changes to the module specifications. All changes are discussed and signedoff at the Programme Review Board in August, ahead of teaching which starts in September.
Year 1 and 2
There are six modules in both year one and year two, as outlined below.

Overview
The aim of the module is to present, in context, and provide skills in, the application of fundamental Mathematics and systems modelling concepts that underpin all of Engineering. To encourage the development of problem solving and modelling skills as required in other year one modules and in order that more advanced material can be tackled in modules taught in later years.
Modules
 Functions, algebra and graphs.
 Complex numbers.
 Differentiation and integration of functions of a single variable.
 Vectors, matrices and determinants.
 Matrix algebra and linear equations.
 Solution of 1st and 2nd order ordinary differential equations.
 Basic probability.
 Statistics and hypothesis testing.
 Functions of Several Variables.
Assessment Information
Unseen Written Examination (80%).
Coursework (20%).Overview
This module will introduce the fundamental programming concepts for procedural and event driven programming using Python. Python is an interpreted and dynamically typed language which will allow learners to gain insight into how software is built from the ground up. Learners will also be introduced to commonly used data structures used for storing and manipulating data, as well as external file and data input/output handling. Learners will then be introduced to tools that allow data to be visualised through plotting.
In this module learners will become familiar with industry standard programming tools and techniques, become comfortable and competent to navigate a programming environment and be able to work to industry standard coding practice.
The module will be taught using lectures, tutorials, and handson programming exercises.Modules
 IDE’s and the wider programming environment for Python.
 Programming fundamentals.
 Operators and expressions.
 Decision structures.
 Loops.
 Data, data structures and data manipulation.
 Functions.
 Manipulating Files.
 Plots and formatting.
 Debugging and unit testing.
 Version Control.
Assessment Information
Individual assessment consisting of:
Coursework 1 (45%).
Coursework 2 (45%).
Labs (10%).Overview
This module aims to introduce the fundamental principles of statics as applied in an engineering context and to develop skills in system description and modelling. This module provides an overview of fundamental mechanical principles of solids and structures which will be required not only for technical mechanical design, but also for the systematic evaluation and analysis of various engineering problems.
Modules
 Intro to vector mechanics.
 Force and moment.
 Free body diagrams.
 Equilibrium of particles and force systems.
 Equilibrium of rigid bodies.
 Pinjoint structure.
 Shear force and bending moment diagrams.
 Stress, strain, elastic constants, Hooke’s law.
 Axial load.
 Pinjointed frame lab.
 Centre of gravity and centroid.
 Engineer’s bending theory, first and second moment of area.
 Beam deflection due to bending.
 Introduction to torsion and combined loadings, and column buckling.
Assessment Information
Unseen Written Examination (60%).
Coursework (40%).Overview
This module aims to provide the students with an understanding of the fundamental concepts of electrical engineering (charge, voltage, current, power) and their application in components, topologies, and circuit analysis methods. It also provides students with an understanding of electrical machines, their fundamentals, and the applications.
Closely aligned with Year 1 Mathematics, it enables students to apply mathematical techniques in appropriate engineering contexts. Student will be encouraged to develop problemsolving and modelling skills relevant to all branches of engineering.Modules
 Introduction to Charge, Current, Voltage, Energy and Power.
 Circuit elements, energy storage elements.
 Resistive circuits, voltage and current dividers.
 Kirchhoff's laws, DC and AC circuit theorems and analysis methods.
 RLC electric circuits and filters.
 Introduction to semiconductors.
 Fundamentals of Electrical Systems.
 Electrical power, Phasors, Power factor, and Harmonics.
 Threephase systems.
 Fundamentals of electromagnetism.
 Electric field and potential.
 Electromagnets.
 Transformers.
 DC Machines.
 Stepper Motors.
 Synchronous Machines.
 Induction Machines.
Assessment Information
Unseen Written Examination (60%).
Coursework (40%).Overview
This module aims to deliver fundamental knowledge on thermodynamics and illustrates its importance to engineering systems. Thermodynamics is the science that is devoted to understanding energy in all its forms, and how energy changes form. The module’s aim is to supply the necessary analytical tools to study these energy changes when applied in engineering situations.
Starting from fundamental concepts of work, heat, and thermodynamics properties of matter, the module will cover the laws of thermodynamics and the various usages of the Carnot Cycle, heat pumps, and heat exchangers.Modules
 Multivariable Functions: the mathematical background to the course.
 Hydrostatics: the language of fluids, and the treatment of fluids at rest.
 Simple Flows: visualising flow, steadyflow, continuity, and the Bernoulli equation.
 First Law of Thermodynamics: systems, processes, reversibility, and energy.
 Second Law of Thermodynamics: heat engines, reversibility, and efficiency.
 Entropy: changes in entropy, Clausius inequality, Gibb's Equation, and potentials.
Assessment Information
Unseen Written Examination (60%).
Coursework (40%).Overview
This module aims to provide an integrated introduction to electronics engineering, taught using challenge and problembased learning infused with theory, practise, and research.
The primary goal of this module is to learn to understand and appreciate the fundamentals of electronic devices, analogue circuits, and their state of art applications in a variety of reallife engineering contexts.
This course will span the basics of design, operation and analysis of diodes, transistors, opamps, converters, and analogue systems to sensors. Fostering creativity and ideas, design and lab exercises are significant components of the course aimed at embedding the engineering relevance and societal significance of electronic systems.Modules
 Diodes: structure, working, types and applications.
 Bipolar Junction Transistors (BJT) – structure, characteristics, load line analysis and applications.
 BJT configuration as an amplifier and a switch.
 FETs (JFET, MOSFET) structure, working and characteristics.
 SCRs, Thyristors and Triacs, working and applications.
 Opamps: basic structure and configuration.
 Opamp application as filters, comparators, and oscillators.
 Circuit design and prototyping.
 Voltage regulators.
 Rectifiers and inverter circuits.
 Power electronic devices and systems.
 Sensors, transducers, and their applications.
Assessment Information
Unseen Written Examination (60%).
Group Project (20%).
Individual Project (20%). 
Overview
To present and provide skills in the application of more advanced mathematics and systems modelling concepts that underpin many areas of Engineering. To build on the fundamental material introduced in the Year 1 Engineering Mathematics and Systems module and introduce more advanced topics related to the analysis of a wide variety of engineering systems.
To consolidate the development of problem solving and modelling skills as required in other Year 2 modules and that students are equipped with the skills to tackle advanced material in modules taught in later years.
Modules
 Series and limits.
 Fourier Analysis.
 Laplace Transforms.
 Differentiation and integration of functions of two or more variables.
 Vector calculus.
 Partial differential equations.
Assessment Information
Unseen examination (80%).
Coursework (20%).Overview
Building on the module Applied Programming 1 where learners are introduced to eventdriven programming, this module aims to enhance students’ (learners’) programming skills through use of Object Oriented Programming (OOP) in Python. It will provide both a theoretical and practice led insight into the fundamentals and advanced concepts of OOP through a range of problems and scenarios/handson exercises.
The module will also familiarise learners with theoretical and practical aspects of data acquisition and data analysis to develop their skills in creating systems and processes that are responsive to live realworld data.
Finally, learners will be introduced to software development techniques and concepts, such as the use of GIT for version control and tracking changes in source code during development.
The module will be taught using lectures, tutorials and handson programming exercises.Modules
 Object Oriented Programming fundamentals.
 Object Oriented Programming advanced concepts.
 Graphical User Interface design and implementation.
 Data Acquisition.
 Data Analysis.
 Software development concepts and tools.
Assessment Information
Individual assessment consisting of:
Coursework 1 (45%).
Coursework 2 (45%).
Seminar (10%).Overview
This module aims to cover the underlying concepts and applications of dynamics and vibration and how these apply to engineering systems.
The course covers topics in dynamics mechanics including different types of motion (linear, circular, and projectile); force, momentum, and impulse; bodies in rotation; work and power; torque, angular momentum and energy; and vibration.
Modules
 Introduction to dynamic mechanics, rectilinear and curvilinear motion.
 Motion of projectile, dependent and relative motion.
 Kinetics of a particle:
 Force and acceleration, equation of motion
 Work and energy for particles, power and efficiency
 Linear and angular impulse and momentum
 Dynamics of Particles
 Importance and applications in rigid bodies
 Difference between kinematics and kinetics
 Planar Kinematics of a Rigid Body:
 Planar RigidBody Motion
 Translation
 Rotation about a Fixed Axis
 Absolute Motion Analysis
 RelativeMotion Analysis: Velocity
 Instantaneous Centre of Zero Velocity
 RelativeMotion Analysis: Acceleration
 RelativeMotion Analysis using Rotating Axes
 Planar Kinetics of a Rigid Body: Force and Acceleration
 Moment of Inertia
 Planar Kinetic Equations of Motion
 Equations of Motion: Translation
 Equations of Motion: Rotation about a Fixed Axis
 Equations of Motion: General Plane Motion
 Planar Kinetics of a Rigid Body: Work and Energy
 Kinetic Energy
 The Work of a Force
 The Work of a Couple
 Principle of Work and Energy
 Conservation of Energy
 Planar Kinetics of a Rigid Body: Impulse and Momentum
 Linear and Angular Momentum
 Principle of Impulse and Momentum
 Conservation of Momentum
 Eccentric Impact
 Vibrations
 Undamped Free Vibration
 Undamped Forced Vibration
 Viscous Damped Free Vibration
 Viscous Damped Forced Vibration
Assessment Information
Unseen Examination (60%).
Coursework (40%).Overview
The module aims to provide students with an understanding of digital systems and their applications. It puts them into context as core components of computer architectures.
The main focus is to understand digital systems and lowlevel computer architecture elements such as memories, arrays, I/O, and processes. It also shows the interconnection and role of the various layers from a device, through assembler, to programming and communication with other devices or systems.Modules
 Digital devices.
 Digital logic.
 Combinational circuits.
 Sequential circuits.
 Processor elements.
 Registers and memories.
 Memories and components.
 Digital System Arrays (Multiplexers, demultiplexers, decoders, programmable logic arrays, FPGA,ASIC).
 Assembler.
 I/O systems.
 A/D – D/A conversion.
 Processes and communications (e.g. Kernel).
 Modern processor architectures.
 Performance enhancing techniques.
 Applications.
 Low level debugging.
Assessment Information
Unseen Examination (40%).
Coursework (60%).Overview
The overall module aim is to develop the abilities to understand, model and analyse heat transfer and fluid flow and apply these to engineering systems. The module incorporates two components of thermal fluid sciences  heat transfer engineering and fluid mechanics.
The heat transfer component will cover different heat transfer modes, formulating them in order to analyse steadystate and transient behaviour of the bodies subjected to thermal gradients. Thermal resistance approach, heat capacity and the lumped mass approximation are dealt with by both analytical and numerical methods.
The fluid mechanics component includes the flow properties, Newtonian and nonNewtonian fluids, the principles of conservation of mass and momentum, laminar and turbulent flows, pipe flows, flow resistance, friction and losses in pipes, ducts and fittings for case of fluids in motion.Modules
Fluids
 Introduction to fluid dynamics.
 Mass and momentum conservation equations and their applications I simple engineering problems.
 Internal flows; Definition of Reynolds number; Laminar vs turbulent flows.
 External flows; Elements of Boundary Layer.
 Flow around aerofoils; Lift and drag.
 Navier Stokes equation; Euler flow; Stokes flow; Couette flow; Poiseuille flow.
 Dimensional analysis (DA)
Heat transfer
 Heat transfer review (conduction, convection, and radiation); thermal resistance, critical radius of insulation.
 Thermal diffusivity; heat equation; special cases; Boundary conditions.
 Numerical methods; 1D HT (matrix solution); 2D HT (matrix and iterative methods).
 Lumped system analysis.
 Physical mechanism of convection; thermal boundary layer.
 Radiation (absorptivity, reflectivity, transmissivity); black bodies; Grey bodies; radiation between two or more surfaces.
Assessment Information
Closed Book Written Examination (60%).
Experimental Coursework (20%).
Numerical Coursework (20%).Overview
This module aims to develop an understanding of the main techniques for modelling, analysis and design of practical continuoustime control systems. It covers the underlying concepts and applications of control theory to engineering systems, with particular emphasis on electromechanical systems.
The case studies underpin the usage of wellestablished analytical techniques for estimating the behaviour of singleinput singleoutput systems under both steadystate and transient conditions.
Modules
 Basic concepts of control
 Sensors, controllers, actuators
 Principles of open and closedloop control, standard signals in control
 Modelling: time domain, Laplace domain
 Transfer functions
 Stability analysis
 Bode and Nyquist diagrams and stability analysis
 Performance in steadystate and transient operation
 P, I, D, PI, PID controllers and their application
 Practical Implementations (e.g noisy inputs, output signals, etc.)
 Compensators
 Cascade control
 Introduction to state space systems modelling
 Dynamic behaviour from standard tests (specs)
Assessment Information
Unseen Examination (60%).
Coursework (40%).
Year 3 and 4
In year three you study six modules, three per semester. In year four, you study two modules per semester, alongside your final year project which spans the whole academic year.

Overview
The aim of this module is to understand and appreciate appropriate manufacturing technologies as well as the role of metrology in an advanced production environment. A comprehensive knowledge of the modern manufacturing techniques is of vital importance for a number of engineering disciplines including Mechanical, Industrial, Manufacturing etc. The module will cover a range of conventional and nonconventional manufacturing. In this module participants will examine how advanced manufacturing organisations make extensive use of computers and information technologies and high precision specialist manufacturing technology to produce a heterogeneous mix of products in small or large volumes with both the efficiency of mass production and the flexibility of custom manufacturing in order to respond quickly to customer demands.
Metrology, being an integral part of manufacturing, is directly related to quality and conformity of the final product. With modern design tools and techniques, it is possible to define products and develop their virtual model, and fully validate by simulation methods. The journey from virtual design to real word cannot be fulfilled without a good understanding of the design feasibility in terms of dimensioning and tolerance definition linked with available manufacturing capabilities. This module reviews the context of metrology and manufacturing methods and their limitations for designers. The concept of uncertainty in design and product maturation are explained. Measurement technologies, their applications, related standards, and best practices are reviewed.
Modules
 Conventional and Computerised Numerically Controlled (CNC) machine tools: turning, milling, drilling etc.
 Cutting tool technology materials, geometry, surface coatings, constraint, working conditions etc.
 Nonconventional processing: Laser, EDM, Water Jet, Ultrasonic etc.
 Rapid prototyping techniques for polymers and metals (e.g. Additive Manufacturing, 3D printing etc).
 Composite component construction for high performance and volume application
 Sheet metal forming using conventional and specialist techniques such as hydroforming and superplastic forming
 Metrology, manufacturing, and variation
 Terminology and standards
 Statistical process control (SPC)
 Principles and methods of measurement
 Coordinate measurement methods
 Measurement uncertainty
 Measurement systems analysis
By the end of the module you should be able to:
 Critically review and evaluate the existing manufacturing techniques and examine the advances in manufacturing process technology relevant to an advanced manufacturing organisation.
 Develop a systematic approach to adopt new processes in order to achieve weight saving, accelerated time to market, quality improvements, cost reduction and/or reduced environmental impact.
 Evaluate and show critical understanding the relationship between measurement uncertainty and manufacturing process variation.
 Examine the role of dimensional measurement and management in the successful introduction of new products.
 Critically assess measurement approaches for suitability in a complex manufacturing environment.
Assessment Information
Unseen Examination (40%)
Group Coursework Assignment (45%)
Group Presentation (15%)Overview
Sound impacts on our daily lives in many ways, from the safety and comfort of the environments in which we live and work, to the functionality of the products that we use. The aim of this module is to understand the origins of sound, how we perceive it, and the subsequent implications for product design.
The module will cover the underlying physics of sound and sound propagation, introducing the onedimensional wave equation; along with time and frequencydomain representations of sound signals. Approaches for the measurement and analysis of sound will be introduced and discussed. Participants will learn about controlling noise, with an overview of noise legislation and its application to products and the environment.
Modules
 Introduction to sound
 Sound propagation
 Onedimensional wave equation
 Source power and intensity
 Time and frequency domain representations
 Sinusoidal signals and noise spectra
 Sound perception
 Measuring sound
 Acoustic impedance and absorption
 Reflection and diffraction
 Noise legislation
 Wave motion through ducts
 Noise control methods
By the end of the module you should be able to:
 Evaluate the core concepts of wave mechanics and how they apply to the formation and propagation of sound waves.
 Formulate expressions for sound pressure based on the onedimensional wave equation.
 Communicate the relationship between the temporal and frequency characteristics of sound and its perception.
 Capture and analyse sound pressure data to identify key frequency components and characterise probable sound sources.
 Devise strategies to improve the noise performance of a product while optimising functional performance, cost and weight.
Assessment Information
Unseen Examination (40%)
Group Coursework Assignment (45%)
Group Presentation (15%)Overview
In the first part of this module the theories and applications of heat transfer as well as mass transfer will be introduced, and you'll be equipped with the knowledge and skills required to solve problems for the design, assessment, and analysis of heat and mass transfer processes. In the second part, the module will aim to develop the abilities to understand, model and analyse advanced thermodynamics theories and systems and apply these to engineering systems. The advanced thermodynamic cycles component will include the analysis of real power heating and cooling systems using thermodynamic principles.
Modules
Heat transfer
 Fundamentals: revision of year 2 heat transfer concepts.
 Fin cooling; fin array; fin cooling with natural convection.
 Mass transfer: mass diffusion; heat & mass transfer; convective mass transfer; drying.
 Heat & mass transfer in porous media; filtration.
Thermodynamics
 Gases: ideal gas; gas mixture; real gas behaviour, kinetic theory.
 Humidity: specific and relative humidity; saturation pressure; dew point.
 Real air cycles: polytropic eq. of state; Otto cycle; Diesel cycle.
 Refrigeration: Ph and TS diagram; reversed Carnot cycle; cryogenics.
 Heat pumps: applications; coefficient of performance.
 Solid state heat pumps: thermoelectric materials/cooling.
By the end of the module you should be able to:
 Recognise the fin equation and identify its general solutions, and apply the boundary conditions to the fin equation and obtain a temperature profile.
 Develop transport models based on the differential equations of heat and mass transfer and their simplified forms, and identify suitable boundary conditions.
 Solve problems involving convective heat and mass transfer.
 Differentiate between the properties of pure and ideal mixed gases, and use thermodynamics tables to measure those properties.
 Represent a variety of real thermodynamic cycles on PV and TS diagrams and discuss the differences between real and ideal cycles.
Assessment Information
Unseen Examination (40%)
Group Coursework Assignment (45%)
Group Presentation (15%)Overview
This module starts with introduction and derivation of fundamental conservation laws for fluids (mass, momentum, and energy), and demonstrate the application of these equations for solving simple flow problems. This will be expanded further by focusing on classical theory of fluid dynamics by covering viscous flows with emphasis on boundary layers, potential flows, turbomachinery fluid dynamics, and compressible flows.
Modules
 Refresher on year 2 fluids: flow properties; fluid as continuum, Langragian and Eulerian description, velocity and stress field, fluid statics/kinematics.
 Reynolds transport theorem, integral and differential forms of governing equations: mass, momentum and energy conservation equations, NavierStokes equations, Euler’s equation, Bernoulli’s Equation.
 Boundary layer equations, boundary layer thickness, boundary layer on a flat plate, similarity solutions, integral form of boundary layer equations, flow separation, inviscid stability theory, boundary layer stability, transition to turbulence.
 Stream and velocity potential function, circulation, irrotational vortex, basic plane potential flows: uniform stream, source and sink, vortex flow, doublet, superposition of basic plane potential flows.
 Flow past a circular cylinder, Magnus effect, KuttaJoukowski lift theorem, concept of lift and drag.
 Turbomachinery; introduction, elementary pump theory, centrifugal/axialflow pumps, turbines, specific speed in pumps and turbines, estimation of the critical speeds.
 Principles of compressible flow; compressible flow through nozzles, diffusers and wind tunnels.
 Quasione dimensional flows, compressible viscous flows, compressible boundary layers.
 Speed of sound and Mach number, basic equations for one dimensional flows, isentropic relations, condi nozzle, normalshock wave.
 RankineHugoniot relations, Fanno and Rayleigh curve, Mach waves, oblique shock wave, PrandtlMeyer expansion waves.
By the end of the module students should be able to: Demonstrate their knowledge and understanding of conservation laws, and solve simple flow problems by making appropriate assumptions as well as using sensible boundary conditions.
 Describe and solve elementary potential flow problems.
 Show critical understanding and apply theories for predicting the behaviour of compressible flows in ducts and nozzle.
 Analyse external compressible flow including expansion and compression turns.
Assessment Information
Unseen Examination (40%)
Group Coursework Assignment (45%)
Group Presentation (15%)Overview
Digital Signal Processing can analyse, modify and enhance various signals; audio, video and communication signals. It supports and enhances interfaces between humans, between machines and between humans and machines. This module provides a detailed knowledge base for the theoretical and practical techniques used in discretetime systems. It aims to develop your skills in designing digital filters and using Fourier transform techniques.
Several digital image processing techniques will be introduced and then used in simulations and practical laboratory sessions.
Modules
Linear time Invariant Systems
 Continuous and Discrete time signals
 Introduction to linear time invariant systems
 Properties of Linear TimeInvariant (LTI) systems
 Shift invariance, stability and causality
 Impulse response and difference equations
Discrete Fourier transform
 Transform definitions and its properties
 Fourier Transform of LTI system
 Inverse Fourier transform
ZTransform
 Transform definition and its properties
 Regions of convergence
 Inverse Z transform
 Relation of Discrete Fourier Transform with Ztransform
Sampling and reconstruction
 Linear and cyclic convolution
 Sampling and reconstruction of continuoustime signals
 Aliasing and resampling digital signals
Digital Filters
 Properties of digital filters
 Digital filter design techniques
 Window designing techniques for finite impulse response filters
 Bilinear transform method for designing infinite impulse response filters
 Structural properties of FIR and IIR filters
Fast Fourier Transform
 Decimation in time using Fast Fourier Transform
 Decimation in frequency using Fast Fourier Transform
 Introduction to image processing techniques
By the end of this module you should be able to:
 Use mathematical techniques to analyse the implications of the sampling theorem and the consequences of aliasing and quantisation distortion.
 Evaluate critically the theory underpinning continuous and discretetime systems.
 Use the Fourier Transform, the Fast Fourier Transform and the ZTransform to analyse various types of signals.
 Design finite impulse response (FIR) and infinite impulse response (IIR) digital filters and apply them to practical signal processing problems.
 Apply basic digital image processing algorithms.
Assessment Information
Assignment (45%)
Assignment demonstration (15%)
Examination (40%)Overview
Most disciplines of the engineering profession require a sound understanding of the techniques used in the modelling and control of dynamic, multidomain physical, and other, systems. The aims of this module are: to introduce techniques and computer tools for modelling, predicting and analysing the behaviour of dynamic systems; and to introduce concepts, principles and techniques employed in classical methods of single loop feedback control design.
Modules
 Systems modelling and control in state space
 Nonlinear systems, equilibrium points and linearization
 Linear time invariant (LTI) systems
 Transfer Matrix, Controllability, Observability, and Reachability
 MultipleInput MultipleOutput (MIMO) Systems
 Root Locus analysis and controller design
 Digital control
 Ztransform
 Digital PID
 Digital controller design
 Practical Applications and Implementation
 Simscape
 Hardware in the Loop
 Design Cycle (Design and virtual testing)
By the end of the module you should be able to:
 Apply procedures for developing mathematical models of complex physical systems and use appropriate analytical and numerical methods for predicting their behaviour.
 Evaluate and apply key concepts and techniques to analyse the behaviour of complex physical systems, and design feedback control systems to meet given requirements.
 Use computational tools in the modelling, simulation and analysis of engineering systems; and communicate results and outcomes to specialists and nonspecialists.
 Apply appropriate theoretical and practical methods to the analysis and solution of engineering problems.
Assessment Information
Unseen Examination (40%)
Group Report (45%)
Group Presentation (15%)Overview
This module reviews concepts of statics and strength of materials used to determine the stress, strain and deflection of structures, and introduces fundamental approaches to failure prevention for static and repeated loading. The module continues by introducing mathematical and numerical methods to simulate structural problems by modern engineering tools and packages. It will further enhance both theoretical and practical appreciation of CAD and matrix analysis of structures, whilst introducing the supporting role of Finite Element Method (FEM).
Modules
Stress Analysis
 Introduction to mechanical properties of engineering materials and their stressstrain behaviour
 Load/force analysis; refresher on the first year module
 Analysis and Design of Shafts for Torsion
 Analysis and Design of Beams for Bending
 Multiple loadings and Complex Stresses
 Principal Stresses / Stress Transformation
 Design based on Failure criteria
 Monotonic failure; failure mechanisms associated with rotating machines
 Fatigue failure analysis
 SN diagrams
 The effect of stress concentration and surface finish
FEM
 Review of Linear Algebra, Matrix calculations
 Fundamental Relationships of Structural Analysis
 The Finite Element Method
 Basic Concepts and definitions
 Fundamental equations of FEM
 Shape functions and the interpolation concept
 1D FE Analysis:
 Bar element
 3Node Bar Element
 Selection of boundary/load conditions
 Matrix Condensations
 Assembling the global stiffness matrix
 2D FE Analysis:
 Formation of the Global Analysis Equations for Plane Trusses
 Local vs. Global coordinates and coordinate Transformation
 Member Stiffness in Local/Global Coordinates
 Assembly of Structure Stiffness
 2D (Plane) elements
 Plane Stress/Strain considerations
 CST Element
 4node Quadrilateral Element
 FE formulations of Beam element
 Plane Frames
 Implementation of FE formulations in programming languages (e.g. MATLAB)
By the end of the module you should be able to:
 Identify loads and stresses associated with mechanical parts and structures.
 Implement stress analysis approach to design based on failure criteria.
 Undertake critical comparative analyses of structures using classical methods and matrix/numerical calculation methods.
 Employ the Finite Element Method in modelling solids/structures, selection of boundary conditions and loading conditions and also to make simplifications, assumptions and idealisations during FEM simulations.
 Provide simulationbased solutions for a range of applied solid mechanics problems, practical modelling, verification of models and analysis, postprocessing and checking of results.
Assessment Information
Unseen Examination (40%)
Group Coursework Assignment (45%)
Group Presentation (15%)Overview
The purpose of this module is to demonstrate dynamical performance of rotors and also to solve problems such as synchronous and nonsynchronous whirl, sensitivity to unbalance, threshold of instability, torsional behaviour of branched systems, the analysis of steady and cyclic stress distributions caused by unbalance and other vibration phenomena.
Modules
 Fundamentals of Machine Vibration and Classical Solutions
 Torsional Vibration
 Torsional Vibration Indicators, Objectives of Torsional Vibration Analysis
 Kinetic Energy Expression, Potential Energy
 Torsional Vibration Measurement
 Carrier Signal Transducers
 Frequencymodulated Systems, Amplitudemodulated Systems
 Frequency Analysis and the Sideband System
 Introduction to Rotordynamics Analysis
 Objectives of Rotordynamics Analysis
 The Spring–Mass Model
 Synchronous and Nonsynchronous Whirl
 Analysis of the Jeffcott Rotor
 Critical Speed Deﬁnitions
 Effect of Flexible (Soft) Supports
 Rotordynamic Effects of the Force Coefﬁcients
 Rotordynamic Instability
 Gyroscopic Effects
 Computer Simulations of Rotordynamics
 Different Types of Models
 Bearing and Seal Matrices
 Torsional and Axial Models
 Eigenanalysis
 Linear Forced Response (LFR)
 Bearings and Their Effect on Rotordynamics
 Fluid Film Bearings, Fixedgeometry Sleeve Bearings, Variablegeometry Tilting Pad Bearings
 Load Between Pivots Versus Load on Pivot
 Inﬂuence of Preload on the Dynamic Coefﬁcients in Tilt Pad Bearings
 Inﬂuence of the Bearing Length or Pad Length
 Squeeze Film Dampers/Applications
 Insights into the Rotor–Bearing Dynamic Interaction with Soft/Stiff Bearing Supports
 Inﬂuence on Natural Frequencies with Soft/Stiff Bearing Supports
 Effects of Mass Distribution on the Critical Speeds with Soft/Stiff Bearing Supports
 Inﬂuence of Overhung Mass/ Gyroscopic Moments on Natural Frequencies with Soft/Stiff Supports
 Fluid Seals and Their Effect on Rotordynamics
By the end of the module you should be able to:
 Mathematically model a variety of rotating machines, including reciprocating engines, compressors, gas and steam turbines, pumps and fans.
 Predict critical speeds and determine design modifications to change them.
 Apply different techniques used in industry for the analysis of rotordynamic problems and solutions.
 Calculate balance correction masses and locations from measured vibration data.
 Solve exploitation problems related to consumer discomfort and machine life.
Assessment Information
Unseen Examination (40%)
Group Coursework Assignment (45%)
Group Presentation (15%)Overview
The aim of project work is to undertake a piece of independent study that will draw on the knowledge and skills acquired during the programme. The project will deepen comprehension of principles and methods by applying them to a problem in the work place. You'll develop enhanced knowledge and understanding of the engineeringrelated aspects of their project. Typically, you'll develop skills in qualitative and quantitative analysis, risk assessment, problem solving using appropriate methodologies, research and information gathering as well as planning and designing an experiment. Generic skills developed during projects will include using appropriate engineering analysis software and IT tools, adhering to research ethics processes and health & safety requirement, oral/written communication, project and time management, computing and IT, selfdiscipline and selfmotivation.
Project
Your project shall focus on a problem relevant to Dyson that may relate to the Dyson's products, its engineering processes or the management of the business from a technical perspective.
As the project can cover any one of a broad range of topics, you'll be responsible for the initiation, planning and management of the task. This means that the knowledge and skills you acquire during this module will differ quite significantly from those acquired elsewhere on the course.
Unlike other classroombased modules, tuition during the WorkBased Project is facilitated partly via group seminars, online exercises and report style guides but primarily via tailored advice and guidance from your supervisors at key points in the project’s lifecycle. That tuition will cover the following topics and techniques:
 Approaches to identifying and describing a problem in or improvement to the workplace that, if remedied to a professional standard, will deliver meaningful outcomes for the company.
 Techniques for planning an approach to solving the selected problem or delivering the anticipated improvement within the constraints imposed by the time and resources available for the project.
 Methods for assessing any risks that may hinder or otherwise diminish the effectiveness of the work done to achieve/deliver the specified outcome of the project.
 Methods for risk assessment and risk control in the context of occupational health and safety.
 Techniques for conducting a review of relevant literature in order to identify and apply theories, methods or concepts that may guide the planning and execution of the project.
 Requirements for engineering activities to promote sustainable development, knowledge of relevant legal issues, codes of practice and industry standards.
 Approaches to managing and executing the project in accordance with the plan specified previously, monitoring progress and responding appropriately to any change in resource or circumstance that might affect its outcome or the effectiveness of the eventual solution.
 Methods of reflecting on and evaluating the outcome of the project with respect to its aims in order to estimate the impact of the improvement brought to the workplace by the proposed solution or improvement.
 Estimating the contribution of the project to a more sustainable products, processes and practice.
 Techniques for disseminating the outcome of the project to both technical and nontechnical audiences, including the awareness of intellectual property issues.
Learning Outcomes for the final year project are:
 Generate a robust project proposal that clearly defines a research question and seeks to solve an existing problem or make some kind of improvement for the company.
 Critically analyse existing literature that relates to the project.
 Select and execute an appropriate methodology to answer the research question, ensuring the compliance with research ethics processes and health & safety requirements.
 Critically communicate the work effectively using a range of media (report, eportfolio and presentation).
 Consider and communicate the postproject reflection and the impact on both the company and the individual.
Assessment Information
Separate submissions consisting of:
 Proposal (10%)
 Progress Review (15%)
 Presentation (15%)
 Final report (60%)
Overview
The aim of this module is to introduce advanced numerical methods which can be used to solve the governing equations of fluid flow and turbulence. This numerical approach is often referred to as Computational Fluid Dynamics (CFD). In this module, you'll learn to utilise conservation laws to derive the governing equations of fluid dynamics and then to apply the finite volume method to transform these governing equations into a set of linear algebraic equations which can then be solved computationally. You'll also be provided with a general understating of turbulence and the nature and structure of turbulent flows as well as turbulence modelling and its application in CFD. These skills will be applied to solve a number of complex but industrially relevant flow problems using Matlab and Ansys.
Modules
 Review of basic fluid mechanics and governing equations (conservation laws).
 Finite difference method (FDM): Taylor series revision, upwind and central differences, stability and accuracy.
 Finite volume method (FVM): methodology, approximation of diffusion and convectiondiffusion problems.
 Pressurevelocity coupling: the staggered mesh, SIMPLE and related methods.
 Solution of discretised equations: the TDMA, pointiterative methods (Jacobi, GaussSeidel, etc.), multigrid methods.
 Unsteady problems: implicit/explicit schemes and associated stability/accuracy issues.
 General CFD code strategies: grid generation (complex geometries: bodyfitted grids, curvilinear grids, blockstructured grids, unstructured grids), BCs, solver, postprocessing, uncertainties in CFD modelling.
 Modelling turbulent flow: RANS, LES, DN.
 Case studies for Applied CFD & Turbulence.
By the end of the module you should be able to:
 Derive the primary governing equations of fluid dynamics for 2D/3D analyses.
 Utilise the fundaments of finite volume method to discretise the governing equations of fluid flow into a set of linear algebraic equations which can then be solved computationally.
 Identify appropriate physical models, CFD parameters and boundary conditions required to numerically solve complex transport problems.
 Use of different approaches to solving different turbulent flow problems, and introduction to different modelling approaches, and an appreciation of their assumptions and limitations.
 Solve complex transport problems using Matlab and Ansys, and postprocess the numerical results into visual interpretation, in order to obtain meaningful engineering insights.
Assessment Information
Unseen Examination (40%)
Group Coursework Assignment (45%)
Group Presentation (15%)Overview
This module briefly reviews concepts of stress analysis used to determine the stress, strain and deflection of mechanical parts, and also fundamental approaches to failure prevention under static and repeated loading. The module mostly focuses on the study of kinematics and design of machinery and related mechanical components, with the aim to introduce fundamental principles of interaction between load and deflection in machinery design, and to develop practical design methodology with emphasis on applications (sizing of parts and selection of materials) and synthesis of mechanical components such as shaft, joints, belts, bearings, and gears.
Modules
 Review on stress analysis & Failure criteria: refresher on material strength and stiffness; discussion of major loadings associated with the rotating components; failure mechanisms including creep and fatigue.
 Introduction to mechanical engineering design: fundamentals of the design process; standards and codes; factor of safety; reliability.
 Shafts and shaft components: shaft materials; shaft design for stress; deflection considerations; critical speeds for shafts.
 Joints: screws, fasteners; design for adhesive bonding; special case of design optimisation by component strain matching.
 Rollingcontact bearings: bearing types; bearing reliability versus life; relating load, life, and reliability; combined radial and thrust loading; selection of ball and cylindrical roller bearings; design assessment for selected rollingcontact bearings; hydrodynamic lubrication: derivation of Reynold’s equation in one dimension; solutions for wide plane thrust bearings and journal bearings; friction and temperature rise associated with hydrodynamic bearings
 Traction drives and belts.
 Gears: types of gears: spur, helical, bevel, worm; conjugate action; involute properties; contact ratio; interference; force analysis in gears.
By the end of the module you should be able to:
 Develop appropriate analyses to describe and predict the behaviour of standard machine components under loading.
 Reduce the behaviour of a complex mechanical machine into appropriate sub systems/elements and then analyse the behaviour of their elements.
 Apply stress analysis theory, fatigue theory and appropriate criteria of failure to the design of simple machine elements.
 Apply codes and standards to machine component design.
 Approach a design problem successfully, taking decisions when there is not a unique answer, and communicate the results of a design assignment.
Assessment Information
Unseen Examination (40%)
Group Coursework Assignment (45%)
Group Presentation (15%) 
Overview
Renewable energies such as wind power, solar power, geothermal energy, hydropower or bioenergy have the potential to deliver sustainable energy on windy and sunny days or as baseload grid energy, respectively. Energy storage is needed to enable transition towards energy systems with low environmental impact.
This course is designed for introducing different renewable technologies and a deeper understanding of the underlying concepts and processes of energy storage. The module will provide you with a firm grounding in the thermodynamic principles of electrochemical, electrical and mechanical energy conversion with a deeper focus on fuel cells and energy storage methods, e.g., batteries, supercapacitors, by targeting technological aspects as well as simulation strategies.
Modules
Introduction to Energy Storage
 General background on alternative energy sources and sustainability
 Resource scale and availability
 Available technologies, implications and challenges
Batteries
 Principle of operation
 Battery components (electrode, cell, modules and packs)
 Governing physics (coupled electrochemical and thermal)
 Battery Thermal Management
Fuel Cells and Hydrogen Storage
 Types of fuel cells
 Physics of PEM fuel cells and its modelling
 Hydrogen storage systems
Supercapacitors
 Aqueous and organic based supercapacitors
 Pseudo and asymmetric supercapacitors
System Integration
 Applications
 Product development
Hybrid Systems
Mechanical storage (Wider Electrical System), Hydroelectric, etc.
By the end of this module you should be able to:
 Distinguish the different approaches of renewable energies and energy storage technologies.
 Analyse the underlying physical, physiochemical and technological concepts of energy conversion and energy storage linked with different technologies.
 Differentiate the components of advanced battery and fuel cell systems and the fundamental principles governing their operation.
 Evaluate and to specialists and nonspecialists the requirements of energy storage cell applications.
 Discuss and critically examine mechanical and thermal energy storage methods, their applications and limitations.
 Evaluate and discuss on the components, operation and limitations of advanced energy storage systems such as batteries and supercapacitors.
Assessment Information
Unseen Exam (40%)
Individual Report (45%)
Individual Presentation (15%)Overview
The module will present the fundamentals of embedded systems including the microcontrollers’ architecture, programming languages, combinational logic and practical examples to show the tradeoffs between power, performance and cost.
A stateoftheart microcontroller development suite will be used to analyse various aspects of embedded systems’ hardware as well as the conversion between analogue and digital signals given the application of sensors/actuators in an industrial context.
Modules
 The history and architecture of embedded systems
 Programming languages and development tools (C/C++)
 Compilation, assembly and linking in the translation process
 General purpose input/output and writing set of operations for them
 Asynchronous and synchronous serial communication
 Data formatting, timing diagrams, and signalling levels
 Perform voltage to binary and binary to voltage numerical conversions
 Embedded designing and programming for monitoring physical properties
 Embedded designing and programming for effecting physical control
 Interrupts, waveform generation and time measurement
 Applications of pulse width modulation
 I/O buses and master/slave devices
 Wireless ports (Wireless updates, bootloaders, functionality of products)
 Eventdriven and realtime solutions
 Low Power Modes, Power Budgeting
 Safety requirements
By the end of this module you should be able to:
 Evaluate the fundamental building blocks and architecture of microprocessor and relate that to the ‘embedded systems’ controller and interrelationships.
 Analyse, design, develop, debug, and document embedded systems using a range of languages, environments, development tools and hardware.
 Synthesise significant considerations and issues relating to embedded systems (such as power consumption, cost, reliability and safety performance etc).
 Design an embedded system to meet specifications, conditions and requirements.
Assessment Information
Unseen Examination (40%)
Group Report (45%)
Group Presentation (15%)Overview
The module aims to provide you with the ability to analyse and design analogue electronic circuits. You will be able to use Electronic Design Automation tools, for different simulation analyses. It will encompass typical functions of analogue circuits: voltage and current references, operational amplifiers (internal topology and their utilisation in different closedloop circuits), filters, signal conditioning, comparators, oscillators and signal generators.
You will be encouraged to explore and compare the performance of different circuits with the same functionality.
Modules
 Analogue circuit modelling and simulation.
 Behaviour of discrete components.
 Class AB and B power amplifiers.
 Voltage and current references.
 Operational amplifiers (including internal topology).
 Analogue multipliers and their applications.
 Operational transconductance amplifiers and applications.
 Design of analogue filters.
 Signal selection, processing and conversion (including multiplexing, ADCs and DACs).
 Comparators, hysteresis.
 Oscillators and voltagecontrolled oscillators.
 Waveform generators.
 Sensitivity and Tolerance.
 Worst case design analysis.
By the end of the module you should be able to:
 Recognise, compare and apply different circuit topologies to implement a variety of analogue functions.
 Consider and distinguish practical issues associated with the selection of components.
 Use models of components to analyse the nominal or ideal behaviour of circuits.
 Perform sensitivity and worstcase analyses by use of software simulation tools.
 Design analogue electronic circuits and optimise their performance against a variety of criteria.
Assessment Information
Unseen Exam (40%).
Individual Report (45%).
Demonstration (15%).Overview
Modern electronic equipment, domestic and industrial alike, requires conditioning of the electric supply delivered to it in order to enable adequate, efficient and flexible operation. The electronics is used for processing power rather than information.
This module aims to introduce the concept of power electronic devices and their usage for power processing, conversion and control purposes. It will present the range of applications of power electronics, from power supplies for laptops to motor drives in appliances, robotics and electric vehicles.
Modules
 Detailed characteristics of power devices – diodes, IGBTs, MOSFETs, thyristors
 Limitations in utilisation – voltages, currents, switching frequencies
 Power converters: ACDC converters, DCDC converters, isolated converters, bridges and 3phase inverters, resonant converters
 Nonideal cases, commutation and overlap, dead time in inverters
 Grounding and user safety issues regarding electric shock and excessive temperatures.
 Pulsewidth modulation in converters
 Design and simulation of converters
 Applications (e.g. laptop charger design, solar power, wind power, hybrid & electric vehicles)
 Charge and discharge of Power Electronic Converters (Energy Storage Systems)
 Safety
By the end of this module you should be able to:
 Evaluate the static and dynamic characteristics of Power Electronic Converters (PECs), components and their operation limits.
 Examine the operation and types of PECs;
 Design and analyse PECs, and communicate justification of decisions, outcomes and results.
 Analyse the power quality of PECs and implement appropriate filters in order to improve the power quality of PECs’ input and/or output.
 Compare and model PECs for different applications and examine employment of new devices in them.
Assessment Information
40% Unseen Exam (2 hours)
45% Individual Report (3000 words)
15% Individual Presentation (10 minutes)Overview
Digital Signal Processing can analyse, modify and enhance various signals; audio, video and communication signals. It supports and enhances interfaces between humans, between machines and between humans and machines. This module provides a detailed knowledge base for the theoretical and practical techniques used in discretetime systems. It aims to develop your skills in designing digital filters and using Fourier transform techniques.
Several digital image processing techniques will be introduced and then used in simulations and practical laboratory sessions.
Modules
Linear time Invariant Systems
 Continuous and Discrete time signals
 Introduction to linear time invariant systems
 Properties of Linear TimeInvariant (LTI) systems
 Shift invariance, stability and causality
 Impulse response and difference equations
Discrete Fourier transform
 Transform definitions and its properties
 Fourier Transform of LTI system
 Inverse Fourier transform
ZTransform
 Transform definition and its properties
 Regions of convergence
 Inverse Z transform
 Relation of Discrete Fourier Transform with Ztransform
Sampling and reconstruction
 Linear and cyclic convolution
 Sampling and reconstruction of continuoustime signals
 Aliasing and resampling digital signals
Digital Filters
 Properties of digital filters
 Digital filter design techniques
 Window designing techniques for finite impulse response filters
 Bilinear transform method for designing infinite impulse response filters
 Structural properties of FIR and IIR filters
Fast Fourier Transform
 Decimation in time using Fast Fourier Transform
 Decimation in frequency using Fast Fourier Transform
 Introduction to image processing techniques
By the end of this module you should be able to:
 Use mathematical techniques to analyse the implications of the sampling theorem and the consequences of aliasing and quantisation distortion.
 Evaluate critically the theory underpinning continuous and discretetime systems.
 Use the Fourier Transform, the Fast Fourier Transform and the ZTransform to analyse various types of signals.
 Design finite impulse response (FIR) and infinite impulse response (IIR) digital filters and apply them to practical signal processing problems.
 Apply basic digital image processing algorithms.
Assessment Information
Assignment (45%)
Assignment demonstration (15%)
Examination (40%)Overview
Most disciplines of the engineering profession require a sound understanding of the techniques used in the modelling and control of dynamic, multidomain physical, and other, systems. The aims of this module are: to introduce techniques and computer tools for modelling, predicting and analysing the behaviour of dynamic systems; and to introduce concepts, principles and techniques employed in classical methods of single loop feedback control design.
Modules
 Systems modelling and control in state space
 Nonlinear systems, equilibrium points and linearization
 Linear time invariant (LTI) systems
 Transfer Matrix, Controllability, Observability, and Reachability
 MultipleInput MultipleOutput (MIMO) Systems
 Root Locus analysis and controller design
 Digital control
 Ztransform
 Digital PID
 Digital controller design
 Practical Applications and Implementation
 Simscape
 Hardware in the Loop
 Design Cycle (Design and virtual testing)
By the end of the module you should be able to:
 Apply procedures for developing mathematical models of complex physical systems and use appropriate analytical and numerical methods for predicting their behaviour.
 Evaluate and apply key concepts and techniques to analyse the behaviour of complex physical systems, and design feedback control systems to meet given requirements.
 Use computational tools in the modelling, simulation and analysis of engineering systems; and communicate results and outcomes to specialists and nonspecialists.
 Apply appropriate theoretical and practical methods to the analysis and solution of engineering problems.
Assessment Information
Unseen Examination (40%)
Group Report (45%)
Group Presentation (15%)Overview
This module aims to show how power electronics, modern electric motors and control theory underpin modern electric drives. Characteristics of standard and bespoke AC motors will be analysed in context of different control approaches, focusing on vector control and directtorque control. Applications will include appliances, robotics and electric vehicles.
Modules
 Motors revision
 Applications (e.g. automotive, home appliances, robotics)
 Modelling and analysis of DC, induction, PM and reluctance motors
 Modelling AC motors in orthogonal dq reference frames
 Heating and Thermal effects in electric drives, Losses and where losses occur
 Performance tests
 Steadystate characteristics of motors under controlled DC or AC supply
 Principles of singleloop and cascaded control systems for drives
 Scalar control, vector control, direct torque control
 Performance issues regarding sensors' accuracy and/or parameter sensitivity (Position sensing)
 Types of generic and bespoke power electronic converters
 Currentregulated pulsewidth modulation for lowpower drives
 Limitations of power electronics in highpower drives
 Typical frequency converter – modes of operation, interfaces, parameter adjustment
 Electric drives design/specification
By the end of this module you should be able to:
 Show an advanced understanding on how variable supply is used to control the operation of modern electric machines.
 Critically analyse operational and control aspects of various electric machines; and communicate outcomes and results to both specialist and nonspecialist audiences.
 Design electric drives to meet specifications and make judgements to address power requirements of all components.
 Critically examine mechanical and thermal aspects and limits of highperformance electric drives.
 Perform simulation analysis of electric drives.
Assessment Information
Unseen Examination (40%)
Group Report (45%)
Group Presentation (15%)Overview
The module aims to present the principles and techniques of electronics design for manufacture and assembly into a final product. The module will provide you with the theoretical and practical aspects of electronics design from prototyping to mass production encompassing product requirements, design constraints, manufacturing, assembly and testing methods.
The module will introduce you to the fundamentals of integrated circuits, device packaging, schematics design and layout design of printed circuits boards.
Modules
 Electronic components, integrated circuits and packaging
 IC integration: hybrid, monolithic, chip on board.
 IC packaging, surface mount and through hole technologies, footprints.
 Resistors, capacitors, diodes, transistors, connectors (types and packaging).
 Printed circuit boards (PCBs)
 Single sided, double sided, multilayer, flexible printed boards.
 Substrate and metallization materials, finishing, layers definition, copper weight.
 General design of printed circuit boards
 Schematic design and components footprints and symbols.
 Tracks, pads, vias, polygons, routing, solder lands, thermal relief, component placement, necking.
 Electromagnetic interference, high frequency design considerations, cooling methods.
 Design for manufacture
 Standardization, design rules, tolerances, resolution, board size and shape, cost.
 Design for testability
 Test points, accessibility to components (soldering, testing probes), connectors.
 Circuit manufacturing and mass production
 Manufacturing techniques and basic processes, submitting the design files, specifications, panels, stencils, tooling strips.
 Circuit assembly and testing
 PCB population, soldering methods, wire bonding techniques, incircuit testing.
By the end of this module you should be able to:
 Analyse and evaluate practical issues associated with the design, manufacture and assembly of electronic circuits for mass production.
 Apply practical design considerations related to manufacturability, testing and assembly of printed circuit boards according to final product specifications.
 Correlate circuit schematics and layouts, both in direct and reverse engineering contexts.
 Design circuit schematics and lay out printed circuits boards based on component datasheets, product specifications, design constraints, manufacturing limitations and testing requirements.
 Demonstrate practical skills in the use of Computer Aided Design Software for the design of complex printed circuit boards.
 Design, assemble and test a prototype printed circuit board for an electronic circuit application.
Assessment Information
Unseen Exam (40%)
Individual Report (45%)
Individual Presentation (15%)Overview
The aim of project work is to undertake a piece of independent study that will draw on the knowledge and skills acquired during the programme. The project will deepen comprehension of principles and methods by applying them to a problem in the work place. You'll develop enhanced knowledge and understanding of the engineeringrelated aspects of their project. Typically, you'll develop skills in qualitative and quantitative analysis, risk assessment, problem solving using appropriate methodologies, research and information gathering as well as planning and designing an experiment. Generic skills developed during projects will include using appropriate engineering analysis software and IT tools, adhering to research ethics processes and health & safety requirement, oral/written communication, project and time management, computing and IT, selfdiscipline and selfmotivation.
Project
Your project shall focus on a problem relevant to Dyson that may relate to the Dyson's products, its engineering processes or the management of the business from a technical perspective.
As the project can cover any one of a broad range of topics, you'll be responsible for the initiation, planning and management of the task. This means that the knowledge and skills you acquire during this module will differ quite significantly from those acquired elsewhere on the course.
Unlike other classroombased modules, tuition during the WorkBased Project is facilitated partly via group seminars, online exercises and report style guides but primarily via tailored advice and guidance from your supervisors at key points in the project’s lifecycle. That tuition will cover the following topics and techniques:
 Approaches to identifying and describing a problem in or improvement to the workplace that, if remedied to a professional standard, will deliver meaningful outcomes for the company.
 Techniques for planning an approach to solving the selected problem or delivering the anticipated improvement within the constraints imposed by the time and resources available for the project.
 Methods for assessing any risks that may hinder or otherwise diminish the effectiveness of the work done to achieve/deliver the specified outcome of the project.
 Methods for risk assessment and risk control in the context of occupational health and safety.
 Techniques for conducting a review of relevant literature in order to identify and apply theories, methods or concepts that may guide the planning and execution of the project.
 Requirements for engineering activities to promote sustainable development, knowledge of relevant legal issues, codes of practice and industry standards.
 Approaches to managing and executing the project in accordance with the plan specified previously, monitoring progress and responding appropriately to any change in resource or circumstance that might affect its outcome or the effectiveness of the eventual solution.
 Methods of reflecting on and evaluating the outcome of the project with respect to its aims in order to estimate the impact of the improvement brought to the workplace by the proposed solution or improvement.
 Estimating the contribution of the project to a more sustainable products, processes and practice.
 Techniques for disseminating the outcome of the project to both technical and nontechnical audiences, including the awareness of intellectual property issues.
Learning Outcomes for the final year project are:
 Generate a robust project proposal that clearly defines a research question and seeks to solve an existing problem or make some kind of improvement for the company.
 Critically analyse existing literature that relates to the project.
 Select and execute an appropriate methodology to answer the research question, ensuring the compliance with research ethics processes and health & safety requirements.
 Critically communicate the work effectively using a range of media (report, eportfolio and presentation).
 Consider and communicate the postproject reflection and the impact on both the company and the individual.
Assessment Information
Separate submissions consisting of:
 Proposal (10%)
 Progress Review (15%)
 Presentation (15%)
 Final report (60%)
Overview
This module introduces the concept, implementation and applications of digitally enabled objects that can transfer data over a network without requiring humantohuman or humantocomputer interaction.
The potential of Internet of things (IoT) in an industrial context for automating specific tasks such as industrial machine control, selfdiagnostics in machines and predictive maintenance will be introduced. Different IoT systems architecture and programming techniques will be taught to acquire and process data using hardware kits such as Raspberry Pi, microcontrollers, energy monitors and PLCs.
Modules
 Basic function and architecture of a sensor
 Knowledge of different hardware devices
 Basic programming technique
 Industry related protocols
 Network systems (Protocols)
 Gathering and sharing data between different devices
 Connecting Sensors to the Cloud
 Collection and storage of IoT sensor data
 Data Aggregation
 Processing IoT Data
 Privacy and security
 Analysis and visualization of data
 How things work together: Cloud and IoT
 Embedded operating systems
 Linux (and Windows) based IoT
 Cloudbased data collection
 OnGoing IoT Operations
 Controlling/Operating devices/systems
 Hardware devices (regulations, power management, etc.)
By the end of this module you should be able to:
 Differentiate the main IoT system components, retrieve and process data from different devices using programming techniques.
 Appraise where the IoT concept fits within the industry (Industry 4.0) and future trends
 Analyse the various network protocols used in IoT and know the key wireless technologies used in IoT systems.
 Analyse and compare the link between IoT, big data, cloud computing and data analytics
 Design a simple IoT system composed of sensors, data processing units, wireless networks and display/actuators.
Assessment Information
Unseen Examination (40%)
Group Report (45%)
Group Presentation (15%)Overview
The module provides a deeper understanding of the principles of operation of mobile robots and future robotic applications outside the factory. It focuses on the methodology used for modelling, planning, control and localisation of mobile robots in both structured and unstructured environments.
The focus is on wheeled robots, which are the most common, however the techniques introduced are general enough to be applied to any mobile robot. A part of the course is devoted to recent techniques in robotic perception and onboard intelligence that are deemed to play a relevant role in the coming years.
Modules
 Applications, Problems, Architectures
 Conﬁguration space
 Mechanics, Kinematics
 Path/trajectory planningtracking
 Regulation
 Retraction and cell decomposition
 Probabilistic planning
 Artiﬁcial potential ﬁelds
 Sensors for mobile robots
 Odometric localization
 Bayes theorem
 Kalman Filters
 Landmarkbased and SLAM
 Practical Robotics, consistency and correlation
By the end of this module you should be able to:
 Analyse and apply basic techniques of mobile robotics and thus show a deep understanding of the main challenges in the subject.
 Distinguish different locomotion methods and discuss their suitability for different environments (sometimes unpredictable).
 Build kinematic models of common mobile robot types and apply basic nonlinear control techniques to control them.
 Evaluate and select sensors for a given mobile robot application and apply sensor fusion for robust perception of unstructured environments.
 Design, select and implement appropriate techniques for Localisation, Motion Planning & Navigation.
Assessment Information
Unseen Examination (40%)
Group Report (45%)
Group Presentation (15%) 
Overview
The module aims to present software development principles and good practices.
The module covers the main phases of software development life cycle including requirements analysis, design, development, testing and maintenance. A brief introduction to tools and techniques for managing changes in software, code and documentation will also be discussed in the module.
The module will also cover the important factors relating to software quality including functionality, reliability, usability, portability and maintainability.
Modules
 Importance of Software Engineering
 Software development methadologies
 Stages of software development life cycle
 Gathering and analyzing requirements
 Software Design using UML
 Designing the Software using UML
 Use Case diagram
 Activity diagram
 Sequence diagram
 State diagram
 Deployment diagram
 Gang of Four design patterns
 Objectoriented software design
 Testdriven development
 Software testing
 Blackbox testing
 Whitebox testing
 Overview of software quality assurance
 Program verification technologies and methods
 Inspections and code reviews
 Software configuration control
 Implementing software changes
 Software documentation
By the end of this module you should be able to:
 Differentiate a range of software process models used to describe software development lifecycle
 Design and justify complex software systems using symbolic representations and illustrations
 Analyse scenarios where typical design patterns can be applied, and critically evaluate these patterns
 Use software testing during different stages of software development, design and implement software testing solutions
 Select and evaluate appropriate tools for configuration management, version control, and quality control etc under enterprise environments.
Assessment Information
Assignment (45%)
Assignment demonstration/presentation (15%)
Examination (40%)Overview
The module will present the fundamentals of embedded systems including the microcontrollers’ architecture, programming languages, combinational logic and practical examples to show the tradeoffs between power, performance and cost.
A stateoftheart microcontroller development suite will be used to analyse various aspects of embedded systems’ hardware as well as the conversion between analogue and digital signals given the application of sensors/actuators in an industrial context.
Modules
 The history and architecture of embedded systems
 Programming languages and development tools (C/C++)
 Compilation, assembly and linking in the translation process
 General purpose input/output and writing set of operations for them
 Asynchronous and synchronous serial communication
 Data formatting, timing diagrams, and signalling levels
 Perform voltage to binary and binary to voltage numerical conversions
 Embedded designing and programming for monitoring physical properties
 Embedded designing and programming for effecting physical control
 Interrupts, waveform generation and time measurement
 Applications of pulse width modulation
 I/O buses and master/slave devices
 Wireless ports (Wireless updates, bootloaders, functionality of products)
 Eventdriven and realtime solutions
 Low Power Modes, Power Budgeting
 Safety requirements
By the end of this module you should be able to:
 Evaluate the fundamental building blocks and architecture of microprocessor and relate that to the ‘embedded systems’ controller and interrelationships.
 Analyse, design, develop, debug, and document embedded systems using a range of languages, environments, development tools and hardware.
 Synthesise significant considerations and issues relating to embedded systems (such as power consumption, cost, reliability and safety performance etc).
 Design an embedded system to meet specifications, conditions and requirements.
Assessment Information
Unseen Examination (40%)
Group Report (45%)
Group Presentation (15%)Overview
The module aims to provide you with the ability to analyse and design analogue electronic circuits. You will be able to use Electronic Design Automation tools, for different simulation analyses. It will encompass typical functions of analogue circuits: voltage and current references, operational amplifiers (internal topology and their utilisation in different closedloop circuits), filters, signal conditioning, comparators, oscillators and signal generators.
You will be encouraged to explore and compare the performance of different circuits with the same functionality.
Modules
 Analogue circuit modelling and simulation.
 Behaviour of discrete components.
 Class AB and B power amplifiers.
 Voltage and current references.
 Operational amplifiers (including internal topology).
 Analogue multipliers and their applications.
 Operational transconductance amplifiers and applications.
 Design of analogue filters.
 Signal selection, processing and conversion (including multiplexing, ADCs and DACs).
 Comparators, hysteresis.
 Oscillators and voltagecontrolled oscillators.
 Waveform generators.
 Sensitivity and Tolerance.
 Worst case design analysis.
By the end of the module you should be able to:
 Recognise, compare and apply different circuit topologies to implement a variety of analogue functions.
 Consider and distinguish practical issues associated with the selection of components.
 Use models of components to analyse the nominal or ideal behaviour of circuits.
 Perform sensitivity and worstcase analyses by use of software simulation tools.
 Design analogue electronic circuits and optimise their performance against a variety of criteria.
Assessment Information
Unseen Exam (40%).
Individual Report (45%).
Demonstration (15%).Overview
This module starts with introduction and derivation of fundamental conservation laws for fluids (mass, momentum, and energy), and demonstrate the application of these equations for solving simple flow problems. This will be expanded further by focusing on classical theory of fluid dynamics by covering viscous flows with emphasis on boundary layers, potential flows, turbomachinery fluid dynamics, and compressible flows.
Modules
 Refresher on year 2 fluids: flow properties; fluid as continuum, Langragian and Eulerian description, velocity and stress field, fluid statics/kinematics;
 Reynolds transport theorem, integral and differential forms of governing equations: mass, momentum and energy conservation equations, NavierStokes equations, Euler’s equation, Bernoulli’s Equation.
 Boundary layer equations, boundary layer thickness, boundary layer on a flat plate, similarity solutions, integral form of boundary layer equations, flow separation, inviscid stability theory, boundary layer stability, transition to turbulence.
 Stream and velocity potential function, circulation, irrotational vortex, basic plane potential flows: uniform stream, source and sink, vortex flow, doublet, superposition of basic plane potential flows.
 Flow past a circular cylinder, Magnus effect, KuttaJoukowski lift theorem, concept of lift and drag.
 Turbomachinery; introduction, elementary pump theory, centrifugal/axialflow pumps, turbines, specific speed in pumps and turbines, estimation of the critical speeds
 Principles of compressible flow; compressible flow through nozzles, diffusers and wind tunnels.
 Quasione dimensional flows, compressible viscous flows, compressible boundary layers.
 Speed of sound and Mach number, basic equations for one dimensional flows, isentropic relations, condi nozzle, normalshock wave.
 RankineHugoniot relations, Fanno and Rayleigh curve, Mach waves, oblique shock wave, PrandtlMeyer expansion waves.
By the end of the module students should be able to: Demonstrate their knowledge and understanding of conservation laws, and solve simple flow problems by making appropriate assumptions as well as using sensible boundary conditions.
 Describe and solve elementary potential flow problems.
 Show critical understanding and apply theories for predicting the behaviour of compressible flows in ducts and nozzle.
 Analyse external compressible flow including expansion and compression turns.
Assessment Information
Unseen Examination (40%).
Group Coursework Assignment (45%).
Group Presentation (15%).Overview
Digital Signal Processing can analyse, modify and enhance various signals; audio, video and communication signals. It supports and enhances interfaces between humans, between machines and between humans and machines. This module provides a detailed knowledge base for the theoretical and practical techniques used in discretetime systems. It aims to develop your skills in designing digital filters and using Fourier transform techniques.
Several digital image processing techniques will be introduced and then used in simulations and practical laboratory sessions.
Modules
Linear time Invariant Systems
 Continuous and Discrete time signals
 Introduction to linear time invariant systems
 Properties of Linear TimeInvariant (LTI) systems
 Shift invariance, stability and causality
 Impulse response and difference equations
Discrete Fourier transform
 Transform definitions and its properties
 Fourier Transform of LTI system
 Inverse Fourier transform
ZTransform
 Transform definition and its properties
 Regions of convergence
 Inverse Z transform
 Relation of Discrete Fourier Transform with Ztransform
Sampling and reconstruction
 Linear and cyclic convolution
 Sampling and reconstruction of continuoustime signals
 Aliasing and resampling digital signals
Digital Filters
 Properties of digital filters
 Digital filter design techniques
 Window designing techniques for finite impulse response filters
 Bilinear transform method for designing infinite impulse response filters
 Structural properties of FIR and IIR filters
Fast Fourier Transform
 Decimation in time using Fast Fourier Transform
 Decimation in frequency using Fast Fourier Transform
 Introduction to image processing techniques
By the end of this module you should be able to:
 Use mathematical techniques to analyse the implications of the sampling theorem and the consequences of aliasing and quantisation distortion.
 Evaluate critically the theory underpinning continuous and discretetime systems.
 Use the Fourier Transform, the Fast Fourier Transform and the ZTransform to analyse various types of signals.
 Design finite impulse response (FIR) and infinite impulse response (IIR) digital filters and apply them to practical signal processing problems.
 Apply basic digital image processing algorithms.
Assessment Information
Assignment (45%)
Assignment demonstration (15%)
Examination (40%)Overview
Most disciplines of the engineering profession require a sound understanding of the techniques used in the modelling and control of dynamic, multidomain physical, and other, systems. The aims of this module are: to introduce techniques and computer tools for modelling, predicting and analysing the behaviour of dynamic systems; and to introduce concepts, principles and techniques employed in classical methods of single loop feedback control design.
Modules
 Systems modelling and control in state space
 Nonlinear systems, equilibrium points and linearization
 Linear time invariant (LTI) systems
 Transfer Matrix, Controllability, Observability, and Reachability
 MultipleInput MultipleOutput (MIMO) Systems
 Root Locus analysis and controller design
 Digital control
 Ztransform
 Digital PID
 Digital controller design
 Practical Applications and Implementation
 Simscape
 Hardware in the Loop
 Design Cycle (Design and virtual testing)
By the end of the module you should be able to:
 Apply procedures for developing mathematical models of complex physical systems and use appropriate analytical and numerical methods for predicting their behaviour.
 Evaluate and apply key concepts and techniques to analyse the behaviour of complex physical systems, and design feedback control systems to meet given requirements.
 Use computational tools in the modelling, simulation and analysis of engineering systems; and communicate results and outcomes to specialists and nonspecialists.
 Apply appropriate theoretical and practical methods to the analysis and solution of engineering problems.
Assessment Information
Unseen Examination (40%)
Group Report (45%)
Group Presentation (15%)Overview
This module reviews concepts of statics and strength of materials used to determine the stress, strain and deflection of structures, and introduces fundamental approaches to failure prevention for static and repeated loading. The module continues by introducing mathematical and numerical methods to simulate structural problems by modern engineering tools and packages. It will further enhance both theoretical and practical appreciation of CAD and matrix analysis of structures, whilst introducing the supporting role of Finite Element Method (FEM).
Modules
Stress Analysis
 Introduction to mechanical properties of engineering materials and their stressstrain behaviour
 Load/force analysis; refresher on the first year module;
 Analysis and Design of Shafts for Torsion
 Analysis and Design of Beams for Bending
 Multiple loadings and Complex Stresses
 Principal Stresses / Stress Transformation
 Design based on Failure criteria;
 monotonic failure; failure mechanisms associated with rotating machines
 Fatigue failure analysis
 SN diagrams
 The effect of stress concentration and surface finish
FEM
 Review of Linear Algebra, Matrix calculations
 Fundamental Relationships of Structural Analysis
 The Finite Element Method
 Basic Concepts and definitions
 Fundamental equations of FEM
 Shape functions and the interpolation concept
 1D FE Analysis
 Bar element
 3Node Bar Element
 Selection of boundary/load conditions
 Matrix Condensations
 Assembling the global stiffness matrix
 2D FE Analysis
 Formation of the Global Analysis Equations for Plane Trusses
 Local vs. Global coordinates and coordinate Transformation
 Member Stiffness in Local/Global Coordinates
 Assembly of Structure Stiffness
 2D (Plane) elements
 Plane Stress/Strain considerations
 CST Element
 4node Quadrilateral Element
 FE formulations of Beam element
 Plane Frames
 Implementation of FE formulations in programming languages (e.g. MATLAB)
By the end of the module you should be able to:
 Identify loads and stresses associated with mechanical parts and structures.
 Implement stress analysis approach to design based on failure criteria.
 Undertake critical comparative analyses of structures using classical methods and matrix/numerical calculation methods.
 Employ the Finite Element Method in modelling solids/structures, selection of boundary conditions and loading conditions and also to make simplifications, assumptions and idealisations during FEM simulations.
 Provide simulationbased solutions for a range of applied solid mechanics problems, practical modelling, verification of models and analysis, postprocessing and checking of results.
Assessment Information
Unseen Examination (40%)
Group Coursework Assignment (45%)
Group Presentation (15%)Overview
The purpose of this module is to demonstrate dynamical performance of rotors and also to solve problems such as synchronous and nonsynchronous whirl, sensitivity to unbalance, threshold of instability, torsional behaviour of branched systems, the analysis of steady and cyclic stress distributions caused by unbalance and other vibration phenomena.
Modules
 Fundamentals of Machine Vibration and Classical Solutions
 Torsional Vibration
 Torsional Vibration Indicators, Objectives of Torsional Vibration Analysis
 Kinetic Energy Expression, Potential Energy
 Torsional Vibration Measurement
 Carrier Signal Transducers
 Frequencymodulated Systems, Amplitudemodulated Systems
 Frequency Analysis and the Sideband System
 Introduction to Rotordynamics Analysis
 Objectives of Rotordynamics Analysis
 The Spring–Mass Model
 Synchronous and Nonsynchronous Whirl
 Analysis of the Jeffcott Rotor
 Critical Speed Deﬁnitions
 Effect of Flexible (Soft) Supports
 Rotordynamic Effects of the Force Coefﬁcients
 Rotordynamic Instability
 Gyroscopic Effects
 Computer Simulations of Rotordynamics
 Different Types of Models
 Bearing and Seal Matrices
 Torsional and Axial Models
 Eigenanalysis
 Linear Forced Response (LFR)
 Bearings and Their Effect on Rotordynamics
 Fluid Film Bearings, Fixedgeometry Sleeve Bearings, Variablegeometry Tilting Pad Bearings
 Load Between Pivots Versus Load on Pivot
 Inﬂuence of Preload on the Dynamic Coefﬁcients in Tilt Pad Bearings
 Inﬂuence of the Bearing Length or Pad Length
 Squeeze Film Dampers/Applications
 Insights into the Rotor–Bearing Dynamic Interaction with Soft/Stiff Bearing Supports
 Inﬂuence on Natural Frequencies with Soft/Stiff Bearing Supports
 Effects of Mass Distribution on the Critical Speeds with Soft/Stiff Bearing Supports
 Inﬂuence of Overhung Mass/ Gyroscopic Moments on Natural Frequencies with Soft/Stiff Supports
 Fluid Seals and Their Effect on Rotordynamics
By the end of the module you should be able to:
 Mathematically model a variety of rotating machines, including reciprocating engines, compressors, gas and steam turbines, pumps and fans.
 Predict critical speeds and determine design modifications to change them.
 Apply different techniques used in industry for the analysis of rotordynamic problems and solutions.
 Calculate balance correction masses and locations from measured vibration data.
 Solve exploitation problems related to consumer discomfort and machine life.
Assessment Information
Unseen Examination (40%)
Group Coursework Assignment (45%)
Group Presentation (15%)Overview
The aim of project work is to undertake a piece of independent study that will draw on the knowledge and skills acquired during the programme. The project will deepen comprehension of principles and methods by applying them to a problem in the work place. You'll develop enhanced knowledge and understanding of the engineeringrelated aspects of their project. Typically, you'll develop skills in qualitative and quantitative analysis, risk assessment, problem solving using appropriate methodologies, research and information gathering as well as planning and designing an experiment. Generic skills developed during projects will include using appropriate engineering analysis software and IT tools, adhering to research ethics processes and health & safety requirement, oral/written communication, project and time management, computing and IT, selfdiscipline and selfmotivation.
Project
Your project shall focus on a problem relevant to Dyson that may relate to the Dyson's products, its engineering processes or the management of the business from a technical perspective.
As the project can cover any one of a broad range of topics, you'll be responsible for the initiation, planning and management of the task. This means that the knowledge and skills you acquire during this module will differ quite significantly from those acquired elsewhere on the course.
Unlike other classroombased modules, tuition during the WorkBased Project is facilitated partly via group seminars, online exercises and report style guides but primarily via tailored advice and guidance from your supervisors at key points in the project’s lifecycle. That tuition will cover the following topics and techniques:
 Approaches to identifying and describing a problem in or improvement to the workplace that, if remedied to a professional standard, will deliver meaningful outcomes for the company.
 Techniques for planning an approach to solving the selected problem or delivering the anticipated improvement within the constraints imposed by the time and resources available for the project.
 Methods for assessing any risks that may hinder or otherwise diminish the effectiveness of the work done to achieve/deliver the specified outcome of the project.
 Methods for risk assessment and risk control in the context of occupational health and safety.
 Techniques for conducting a review of relevant literature in order to identify and apply theories, methods or concepts that may guide the planning and execution of the project.
 Requirements for engineering activities to promote sustainable development, knowledge of relevant legal issues, codes of practice and industry standards.
 Approaches to managing and executing the project in accordance with the plan specified previously, monitoring progress and responding appropriately to any change in resource or circumstance that might affect its outcome or the effectiveness of the eventual solution.
 Methods of reflecting on and evaluating the outcome of the project with respect to its aims in order to estimate the impact of the improvement brought to the workplace by the proposed solution or improvement.
 Estimating the contribution of the project to a more sustainable products, processes and practice.
 Techniques for disseminating the outcome of the project to both technical and nontechnical audiences, including the awareness of intellectual property issues.
Learning Outcomes for the final year project are:
 Generate a robust project proposal that clearly defines a research question and seeks to solve an existing problem or make some kind of improvement for the company.
 Critically analyse existing literature that relates to the project.
 Select and execute an appropriate methodology to answer the research question, ensuring the compliance with research ethics processes and health & safety requirements.
 Critically communicate the work effectively using a range of media (report, eportfolio and presentation).
 Consider and communicate the postproject reflection and the impact on both the company and the individual.
Assessment Information
Separate submissions consisting of:
 Proposal (10%)
 Progress Review (15%)
 Presentation (15%)
 Final report (60%)
Overview
This module introduces the concept, implementation and applications of digitally enabled objects that can transfer data over a network without requiring humantohuman or humantocomputer interaction.
The potential of Internet of things (IoT) in an industrial context for automating specific tasks such as industrial machine control, selfdiagnostics in machines and predictive maintenance will be introduced. Different IoT systems architecture and programming techniques will be taught to acquire and process data using hardware kits such as Raspberry Pi, microcontrollers, energy monitors and PLCs.
Modules
 Basic function and architecture of a sensor
 Knowledge of different hardware devices
 Basic programming technique
 Industry related protocols
 Network systems (Protocols)
 Gathering and sharing data between different devices
 Connecting Sensors to the Cloud
 Collection and storage of IoT sensor data
 Data Aggregation
 Processing IoT Data
 Privacy and security
 Analysis and visualization of data
 How things work together: Cloud and IoT
 Embedded operating systems
 Linux (and Windows) based IoT
 Cloudbased data collection
 OnGoing IoT Operations
 Controlling/Operating devices/systems
 Hardware devices (regulations, power management, etc.)
By the end of this module you should be able to:
 Differentiate the main IoT system components, retrieve and process data from different devices using programming techniques.
 Appraise where the IoT concept fits within the industry (Industry 4.0) and future trends
 Analyse the various network protocols used in IoT and know the key wireless technologies used in IoT systems.
 Analyse and compare the link between IoT, big data, cloud computing and data analytics
 Design a simple IoT system composed of sensors, data processing units, wireless networks and display/actuators.
Assessment Information
Unseen Examination (40%)
Group Report (45%)
Group Presentation (15%)Overview
The module provides a deeper understanding of the principles of operation of mobile robots and future robotic applications outside the factory. It focuses on the methodology used for modelling, planning, control and localisation of mobile robots in both structured and unstructured environments.
The focus is on wheeled robots, which are the most common, however the techniques introduced are general enough to be applied to any mobile robot. A part of the course is devoted to recent techniques in robotic perception and onboard intelligence that are deemed to play a relevant role in the coming years.
Modules
 Applications, Problems, Architectures
 Conﬁguration space
 Mechanics, Kinematics
 Path/trajectory planningtracking
 Regulation
 Retraction and cell decomposition
 Probabilistic planning
 Artiﬁcial potential ﬁelds
 Sensors for mobile robots
 Odometric localization
 Bayes theorem
 Kalman Filters
 Landmarkbased and SLAM
 Practical Robotics, consistency and correlation
By the end of this module you should be able to:
 Analyse and apply basic techniques of mobile robotics and thus show a deep understanding of the main challenges in the subject.
 Distinguish different locomotion methods and discuss their suitability for different environments (sometimes unpredictable).
 Build kinematic models of common mobile robot types and apply basic nonlinear control techniques to control them.
 Evaluate and select sensors for a given mobile robot application and apply sensor fusion for robust perception of unstructured environments.
 Design, select and implement appropriate techniques for Localisation, Motion Planning & Navigation.
Assessment Information
Unseen Examination (40%)
Group Report (45%)
Group Presentation (15%) 
Overview
The module aims to present software development principles and good practices.
The module covers the main phases of software development life cycle including requirements analysis, design, development, testing and maintenance. A brief introduction to tools and techniques for managing changes in software, code and documentation will also be discussed in the module.
The module will also cover the important factors relating to software quality including functionality, reliability, usability, portability and maintainability.
Modules
 Importance of Software Engineering
 Software development methadologies
 Stages of software development life cycle
 Gathering and analyzing requirements
 Software Design using UML
 Designing the Software using UML
 Use Case diagram
 Activity diagram
 Sequence diagram
 State diagram
 Deployment diagram
 Gang of Four design patterns
 Objectoriented software design
 Testdriven development
 Software testing
 Blackbox testing
 Whitebox testing
 Overview of software quality assurance
 Program verification technologies and methods
 Inspections and code reviews
 Software configuration control
 Implementing software changes
 Software documentation
By the end of this module you should be able to:
 Differentiate a range of software process models used to describe software development lifecycle
 Design and justify complex software systems using symbolic representations and illustrations
 Analyse scenarios where typical design patterns can be applied, and critically evaluate these patterns
 Use software testing during different stages of software development, design and implement software testing solutions
 Select and evaluate appropriate tools for configuration management, version control, and quality control etc under enterprise environments.
Assessment Information
Assignment (45%)
Assignment demonstration/presentation (15%)
Examination (40%)Overview
The module will present the fundamentals of embedded systems including the microcontrollers’ architecture, programming languages, combinational logic and practical examples to show the tradeoffs between power, performance and cost.
A stateoftheart microcontroller development suite will be used to analyse various aspects of embedded systems’ hardware as well as the conversion between analogue and digital signals given the application of sensors/actuators in an industrial context.
Modules
 The history and architecture of embedded systems
 Programming languages and development tools (C/C++)
 Compilation, assembly and linking in the translation process
 General purpose input/output and writing set of operations for them
 Asynchronous and synchronous serial communication
 Data formatting, timing diagrams, and signalling levels
 Perform voltage to binary and binary to voltage numerical conversions
 Embedded designing and programming for monitoring physical properties
 Embedded designing and programming for effecting physical control
 Interrupts, waveform generation and time measurement
 Applications of pulse width modulation
 I/O buses and master/slave devices
 Wireless ports (Wireless updates, bootloaders, functionality of products)
 Eventdriven and realtime solutions
 Low Power Modes, Power Budgeting
 Safety requirements
By the end of this module you should be able to:
 Evaluate the fundamental building blocks and architecture of microprocessor and relate that to the ‘embedded systems’ controller and interrelationships.
 Analyse, design, develop, debug, and document embedded systems using a range of languages, environments, development tools and hardware.
 Synthesise significant considerations and issues relating to embedded systems (such as power consumption, cost, reliability and safety performance etc).
 Design an embedded system to meet specifications, conditions and requirements.
Assessment Information
Unseen Examination (40%)
Group Report (45%)
Group Presentation (15%)Overview
This module aims to equip students with the knowledge of computer architecture and networked computer systems required to build a small to mediumnetworked computer and the corresponding switching routing principles. This includes topics such as IP addressing techniques (IPv4 and IPv6); commandline interface (CLI) configuration of Ethernet switches, routers, Virtual Local Area Networks (VLANs); network security and firewalls. Software based realworld scenarios are used to enhance the theoretical knowledge of network devices and configure both Ethernet switching and IP configuration. Automotive communication network protocols such as Flex Ray, CAN and LIN will also be covered in this module.
Skills acquired in this module will enable students to identify, plan, build and maintain computer systems networks, as well as troubleshoot common hardware and software problems in an industrial environment.
Modules
 Computer architecture and internetworking
Computer architecture; control units including hardwired and microprogrammed control units; performance of microprocessors; RISC/CISC architectures and the Central Processing Unit (CPU). Storage devices, memory hierarchy, data storage and elementary error detection and correction. Brief number system reminder and binary/decimal conversion for networking. Basics of internetworking, background of data communication (wired, wireless). Network topologies (Star, Mesh, Hybrid) and core/access tiers. Cabling technology, troubleshoot interface and cable issues; Network Interface Card.  The OSI Reference Model, TCP/IP reference model
Errordetection and correction techniques; Principles of Reliable Data Transfer. Network Devices: Hub, Switch, Router, Firewalls, Access points, Wireless controllers and their role in connection with the TCP/IP model.  Ethernet technology
Multiple Access Links and Protocols (static and dynamic channel allocation). MAC addressing, Frame format Broadcast & collusion domain. Describe and verify switching concepts (MAC learning, Frame switching, frame flooding, MAC address table); Further protocol discussions such as STP algorithm.  IP addressing and routing
Network Protocols, IPv4 address types (Unicast, Multicast, and Broadcast); IPv6 basics. Private and Public networks. Subnet Mask, troubleshoot IPv4 addressing and subnetting. Introducing the most common services such as HTTP, DNS and Email and VOIP and corresponding layers.  Advanced features
Automotive Networks characteristics and its communication requirements. The combined wired/wireless network infrastructure modes. Steps for designing and configuring a combined network. Security aspects and configurations in a simple personal or a networkbased enterprise architecture.
By the end of the module you should be able to:
 Describe the purpose and functions of various computer components and processor architectures.
 Compare various layers of Open System Interconnection (OSI) and TCP/IP model and contrast their associated protocols and addressing schemes.
 Design network diagrams and implement appropriate addressing schemes at a subnetwork level.
 Use appropriate instructions to configure network devices and apply algorithmic approach to troubleshoot network connectivity.
Assessment Information
Assignment (45%).
Assignment demonstration/presentation (15%).
Examination (40%).Overview
This module will aim to introduce you to the concepts, terminologies and algorithms for big data analytics. Starting with methods for collecting data, you'll then learn tools and techniques for cleaning data and dealing with inconsistent, missing and redundant data. Methods for analysing structured and unstructured data are then presented.
Modules
 Fundamentals of big data
 Statistical background
 Collecting and categorising data
 Cleaning and transforming data
 Analysing data and data mining
 Making use of big data
 Technologies for big data
By the end of this module you should be able to:
 Demonstrate an understanding of the complexity of big data analysis and the challenges presented by the management of big data
 Assess data in terms of its type and structure, including its volume, variety, veracity and velocity
 Demonstrate knowledge and understanding of the key concepts of database theory
 Demonstrate an advanced knowledge and understanding of data analytics tools and techniques
 Design different types of tools for data collection, data cleaning, data analysis and data visualisation
Assessment Information
Assignment (45%)
Assignment demonstration/presentation (15%)
Examination (40%)Overview
Digital Signal Processing can analyse, modify and enhance various signals; audio, video and communication signals. It supports and enhances interfaces between humans, between machines and between humans and machines. This module provides a detailed knowledge base for the theoretical and practical techniques used in discretetime systems. It aims to develop your skills in designing digital filters and using Fourier transform techniques.
Several digital image processing techniques will be introduced and then used in simulations and practical laboratory sessions.
Modules
Linear time Invariant Systems
 Continuous and Discrete time signals
 Introduction to linear time invariant systems
 Properties of Linear TimeInvariant (LTI) systems
 Shift invariance, stability and causality
 Impulse response and difference equations
Discrete Fourier transform
 Transform definitions and its properties
 Fourier Transform of LTI system
 Inverse Fourier transform
ZTransform
 Transform definition and its properties
 Regions of convergence
 Inverse Z transform
 Relation of Discrete Fourier Transform with Ztransform
Sampling and reconstruction
 Linear and cyclic convolution
 Sampling and reconstruction of continuoustime signals
 Aliasing and resampling digital signals
Digital Filters
 Properties of digital filters
 Digital filter design techniques
 Window designing techniques for finite impulse response filters
 Bilinear transform method for designing infinite impulse response filters
 Structural properties of FIR and IIR filters
Fast Fourier Transform
 Decimation in time using Fast Fourier Transform
 Decimation in frequency using Fast Fourier Transform
 Introduction to image processing techniques
By the end of this module you should be able to:
 Use mathematical techniques to analyse the implications of the sampling theorem and the consequences of aliasing and quantisation distortion.
 Evaluate critically the theory underpinning continuous and discretetime systems.
 Use the Fourier Transform, the Fast Fourier Transform and the ZTransform to analyse various types of signals.
 Design finite impulse response (FIR) and infinite impulse response (IIR) digital filters and apply them to practical signal processing problems.
 Apply basic digital image processing algorithms.
Assessment Information
Assignment (45%)
Assignment demonstration (15%)
Examination (40%)Overview
Most disciplines of the engineering profession require a sound understanding of the techniques used in the modelling and control of dynamic, multidomain physical, and other, systems. The aims of this module are: to introduce techniques and computer tools for modelling, predicting and analysing the behaviour of dynamic systems; and to introduce concepts, principles and techniques employed in classical methods of single loop feedback control design.
Modules
 Systems modelling and control in state space
 Nonlinear systems, equilibrium points and linearization
 Linear time invariant (LTI) systems
 Transfer Matrix, Controllability, Observability, and Reachability
 MultipleInput MultipleOutput (MIMO) Systems
 Root Locus analysis and controller design
 Digital control
 Ztransform
 Digital PID
 Digital controller design
 Practical Applications and Implementation
 Simscape
 Hardware in the Loop
 Design Cycle (Design and virtual testing)
By the end of the module you should be able to:
 Apply procedures for developing mathematical models of complex physical systems and use appropriate analytical and numerical methods for predicting their behaviour.
 Evaluate and apply key concepts and techniques to analyse the behaviour of complex physical systems, and design feedback control systems to meet given requirements.
 Use computational tools in the modelling, simulation and analysis of engineering systems; and communicate results and outcomes to specialists and nonspecialists.
 Apply appropriate theoretical and practical methods to the analysis and solution of engineering problems.
Assessment Information
Unseen Examination (40%)
Group Report (45%)
Group Presentation (15%)Overview
This module focuses on how to extract information from datasets by algorithms that automatically build models from historical data and predict future behaviours of systems. Data analysis using supervised learning is particularly powerful where there is no mathematical model available and classical statistics offer limited insights (e.g., market analysis, PID parameter tuning).
You'll learn the fundamental concepts of the supervised machine learning and will apply these concepts to analyse data by using the most advanced software tools and programming languages.
Also, an introduction to unsupervised learning will be included in this module. By contrast with supervised learning, data diagnostics with unsupervised learning reﬂect the statistical structure of the overall collection of data, without any support from historical data.
Modules
 Regression of labelled data
 Least square error estimation
 Logistic Regression
 K Nearest Neighbours Regression
 Regression Trees
 Support Vector Machines
 Artificial Neural Networks
 Classification of labelled data
 Classification trees
 Support Vector Machines
 Linear and Quadratic Discriminant Analysis
 Clustering of unlabelled data
 Hierarchical Clustering
 Graph based clustering
By the end of this module you should be able to:
 Compare whether supervised learning is the only/best choice for analysing data, compared to classical statistical analysis.
 Apply supervised learning algorithms by suitable programming languages and software suites.
 Describe limits and assumptions inherent to supervised learning from data.
 Demonstrate knowledge and apply fundamental unsupervised learning techniques.
 Use limits and assumptions inherent to unsupervised learning from data.
Assessment Information
Assignment (45%)
Assignment demonstration/presentation (15%)
Examination (40%)Overview
Digital image processing has a broad range of applications such as remote sensing, image and data storage for transmission and industrial automation.
This module aims to provide the fundamentals of digital signal processing and develop your knowledge from basic signal processing techniques to advanced image processing. It covers the principles of image formation, sampling and quantization, which will allow investigation of imageprocessing techniques. You'll acquire knowledge related to image intensity transformations and spatial filtering and apply it for image enhancement in both spatial and frequency domains. Dealing with different types of noise models and achieving image restoration is also covered.
The module will familiarize you with morphological image processing, colour image processing and image segmentation to help you apply these techniques in real world problems.
Modules
 Digital image fundamentals: elements of visual perception; image perception; image sensing and acquisition; image sampling and quantization; arithmetic, set and logical operations; singlepixel operations.
 Intensity transformation and spatial filtering: intensity transformation functions; contrast stretching; histogram processing; smoothing spatial filters; sharpening spatial filters.
 Filtering in the frequency domain: discrete Fourier transform; image smoothing using frequency domain filters.
 Image restoration: noise models; restoration in the presence of noise only.
 Colour image processing: colour fundamentals; colour models; pseudocolour image processing; colour transformations; smoothing and sharpening; using colour in image segmentation.
 Morphological image processing: erosion and dilation; opening and closing; basic morphological algorithms; morphological reconstruction.
 Image segmentation: point, line and edge detection; thresholding; region segmentation; segmentation using morphological watersheds.
 Image compression and coding: image compression models; Huffman coding; LZW coding.
 Automotive case studies: e.g. image recognition for object detection in vehicle motion path, 3D vision systems.
The learning outcomes for this module are:
 Demonstrate an understanding about image formation and the role that human visual system plays in perception of grey and colour image data.
 Analyse and implement imageprocessing algorithms on computers.
 Apply principles and techniques of digital image processing for image enhancement and image restoration.
 Design and create practical solutions to a range of common image processing problems and to critically assess the results of their solution.
Assessment Information
Assignment (45%).
Assignment demonstration/presentation (15%).
Examination (40%).Overview
The aim of project work is to undertake a piece of independent study that will draw on the knowledge and skills acquired during the programme. The project will deepen comprehension of principles and methods by applying them to a problem in the work place. You'll develop enhanced knowledge and understanding of the engineeringrelated aspects of their project. Typically, you'll develop skills in qualitative and quantitative analysis, risk assessment, problem solving using appropriate methodologies, research and information gathering as well as planning and designing an experiment. Generic skills developed during projects will include using appropriate engineering analysis software and IT tools, adhering to research ethics processes and health & safety requirement, oral/written communication, project and time management, computing and IT, selfdiscipline and selfmotivation.
Project
Your project shall focus on a problem relevant to Dyson that may relate to the Dyson's products, its engineering processes or the management of the business from a technical perspective.
As the project can cover any one of a broad range of topics, you'll be responsible for the initiation, planning and management of the task. This means that the knowledge and skills you acquire during this module will differ quite significantly from those acquired elsewhere on the course.
Unlike other classroombased modules, tuition during the WorkBased Project is facilitated partly via group seminars, online exercises and report style guides but primarily via tailored advice and guidance from your supervisors at key points in the project’s lifecycle. That tuition will cover the following topics and techniques:
 Approaches to identifying and describing a problem in or improvement to the workplace that, if remedied to a professional standard, will deliver meaningful outcomes for the company.
 Techniques for planning an approach to solving the selected problem or delivering the anticipated improvement within the constraints imposed by the time and resources available for the project.
 Methods for assessing any risks that may hinder or otherwise diminish the effectiveness of the work done to achieve/deliver the specified outcome of the project.
 Methods for risk assessment and risk control in the context of occupational health and safety.
 Techniques for conducting a review of relevant literature in order to identify and apply theories, methods or concepts that may guide the planning and execution of the project.
 Requirements for engineering activities to promote sustainable development, knowledge of relevant legal issues, codes of practice and industry standards.
 Approaches to managing and executing the project in accordance with the plan specified previously, monitoring progress and responding appropriately to any change in resource or circumstance that might affect its outcome or the effectiveness of the eventual solution.
 Methods of reflecting on and evaluating the outcome of the project with respect to its aims in order to estimate the impact of the improvement brought to the workplace by the proposed solution or improvement.
 Estimating the contribution of the project to a more sustainable products, processes and practice.
 Techniques for disseminating the outcome of the project to both technical and nontechnical audiences, including the awareness of intellectual property issues.
Learning Outcomes for the final year project are:
 Generate a robust project proposal that clearly defines a research question and seeks to solve an existing problem or make some kind of improvement for the company.
 Critically analyse existing literature that relates to the project.
 Select and execute an appropriate methodology to answer the research question, ensuring the compliance with research ethics processes and health & safety requirements.
 Critically communicate the work effectively using a range of media (report, eportfolio and presentation).
 Consider and communicate the postproject reflection and the impact on both the company and the individual.
Assessment Information
Separate submissions consisting of:
 Proposal (10%)
 Progress Review (15%)
 Presentation (15%)
 Final report (60%)
Overview
This module introduces the concept, implementation and applications of digitally enabled objects that can transfer data over a network without requiring humantohuman or humantocomputer interaction.
The potential of Internet of things (IoT) in an industrial context for automating specific tasks such as industrial machine control, selfdiagnostics in machines and predictive maintenance will be introduced. Different IoT systems architecture and programming techniques will be taught to acquire and process data using hardware kits such as Raspberry Pi, microcontrollers, energy monitors and PLCs.
Modules
 Basic function and architecture of a sensor
 Knowledge of different hardware devices
 Basic programming technique
 Industry related protocols
 Network systems (Protocols)
 Gathering and sharing data between different devices
 Connecting Sensors to the Cloud
 Collection and storage of IoT sensor data
 Data Aggregation
 Processing IoT Data
 Privacy and security
 Analysis and visualization of data
 How things work together: Cloud and IoT
 Embedded operating systems
 Linux (and Windows) based IoT
 Cloudbased data collection
 OnGoing IoT Operations
 Controlling/Operating devices/systems
 Hardware devices (regulations, power management, etc.)
By the end of this module you should be able to:
 Differentiate the main IoT system components, retrieve and process data from different devices using programming techniques.
 Appraise where the IoT concept fits within the industry (Industry 4.0) and future trends
 Analyse the various network protocols used in IoT and know the key wireless technologies used in IoT systems.
 Analyse and compare the link between IoT, big data, cloud computing and data analytics
 Design a simple IoT system composed of sensors, data processing units, wireless networks and display/actuators.
Assessment Information
Unseen Examination (40%)
Group Report (45%)
Group Presentation (15%)Overview
The module will provide you with an understanding of the key issues and techniques involved with securing data and computerbased communication. This will include an introduction to the fundamental theory, concepts and applications of cryptography.
It will also ensure you understand how to systematically address threats, vulnerabilities and the negative consequences that occur should a threat exploit an organisation’s vulnerability in cyber engagement.
Modules
 Information security – threats, risks, forms of attack, risk management, human factors, security testing
 Techniques for securing access to data and prevention against accidental loss
 Authentication, authorisation, nonrepudiation, confidentiality and integrity
 Symmetric cryptography – block and stream ciphers, DES, AES
 Publickey cryptography – RSA, El Gamal, Elliptic Curve Cryptography
 Key exchange, digital signatures
 Hashing
 Cryptanalysis and codebreaking
By the end of this module you should be able to:
 Demonstrate an understanding of the current cyber security threats to a simple IT system, including threats to the storage of information.
 Define, select and evaluate practical cyber security measures to counteract intentional and unintentional human misbehaviour.
 Understand and synthesise the essential components of cryptography
 Understand the principles of symmetric, asymmetric and publickey encryption and hashing techniques to provide enhanced cyber security
 Understand and explain key management, digital signatures and digital certificates.
Assessment Information
Assignment (45%)
Assignment demonstration/presentation (15%)
Examination (40%)