Taylors theorem, Lagrange multipliers, discrete Fourier transforms, z-transforms, vector algebra.

1. Approximate functions with polynomials in one and several variables using Taylors Theorem
2. Apply Lagrange Multiples to find the maximumand minimum of functions of several variables

3. Find the discreteFourier transform of a signal

4. Solve difference equations using the z-transform

5. Compute area, volume and surface Integrals using polar, cylindrical and spherical coordinates.

Control Systems is all about plant and processes (systems) how they behave when subjected to certain inputs (system response) and how to get them to do what we want (system control). Control Systems 301 introduces the student to the characteristics of systems commonly encountered in mechatronics.

1. Use Laplace transform techniques to predict and interpret second order system response to step and ramp inputs.
2. Find the steady-state response of a system to a sinusoidal input by the substitution of j for s in the transfer function.
3. Use Laplace transform techniques to find the transient and steady-state response of a system to a sinusoidal input.
4. Use block diagram algebra, especially Mason’s theorem, to reduce elementary control system diagrams to canonical form.
5. Establish system stability or instability by the plotting of poles and zeros on the complex plane
6. Implement and tune control systems using aPID control strategy.

This module will give the learner the theory and practical experience in understanding the operation of common analog electronic components and circuits, through theory, practical laboratory sessions and small project building/testing. Learners will understand the operation and use of all major analog components, such as the diode, resistor, capacitor, inductor, transistor and be able to apply their knowledge in the areas such as transistor circuits, op-amp configurations and small analog circuits and voltage regulation.

1. Identify,explain and use fundamental analog electronic components in typical small signal circuits including the resistor, capacitor, inductor, diode, transistor, various power sources, op-amp and 555 timer.

2. Describe the operation of fundamental small signal analog circuits including R,RC, RL, RLC circuits, voltage, currentdivider circuits,

3. Calculate values for and demonstrate circuits employing amplification and oscillation methods/techniques such as Op Amps, the 555 timer and/or otheroscillator circuits

4. Distinguish between and explain the various forms of small signal a.c. and d.c. voltage regulation including transformers, diode circuits and regulation ICs.

5. Sketch and construct various small signal transistor circuits using switching and amplification techniques.

This module is designed to introduce students to engineering materials (including metals and polymers), their classification, their properties and how to alter those properties.

1. Explain the nature and structure of materials and determine the classification of various engineering materials.

2. Explain what properties of materials are in use, what they mean, and test them.
3. Determine how to alter properties of materials using heat treatment.
4. Describe the metallic alloys that exist and how to form them.

5. Analyse simple equilibrium phase diagrams and the IronCarbon system.
6. Describe the different categories of polymers, their applications and processing.

This module will give the students an introduction to pneumatic/electro pneumatic and hydraulic systems.It will cover basic pneumatic and hydraulic components and their use in complete systems. The student will also become acquainted with standard pneumatic and hydraulic symbols in accordance with IEC standards and be able to use a software simulation package to draw and simulate practical circuits.

This module will also cover advanced pneumatic and electro pneumatic circuits including sequencing of pneumatic cylinders. The circuits will be build and simulated in software.

1. Describe the components of a compressed air and air treatment system.

2. Demonstrate an understanding of pneumatic circuit operation, including sequence control.

3. Apply the cascade method to solve pneumatic sequentialproblems involvingcascade groups andcylinders.

4. Demonstrate an understanding ofbasic hydraulic systems.

5. Design and simulate electro-pneumatic circuits to sequence cylinders.

6. Employ formulae to calculate flow rate, piston force, system pressure and piston size.

Industrial Data communication is the manipulation of variables that can be implemented into the technology that automatically processes data. The technology under investigation include computers and other communications electronics that can collect, store, influence, formulate and allocate data to serve or control exact processes examples are motor control, electric switching, analogue to digital conversion, digital sampling.

.

1. Demonstrate a basic a basic knowledge of digital circuitry using logic.
2. Interface sensors and transducers
3. Explain the function of analogue communication.
4. Describe high-pass low-pass and band-pass filters
5. Understand Analogue to digital conversion and digital to analogue conversion.
6. Demonstrate an understanding of digital motor control

The aim of this module is to introduce students to the world of digital electronics. It is written in such a way as to give the student a good foundation to build upon as they continue in their chosen studies. The theoretical aspects of the module will be supported by practical laboratory sessions.

1. Understand what is meant by digital signals.

2. Perform Simple Operations in Binary, Hexadecimal and BCD

3. Discern between different logic gates, including but not limited to AND, NAND, OR , NOR, XOR.

4. Simplification of Combinational Logic

5. Describe the operation of basic flip-flops and their applications.

6. Write up lab reports on practical exercises completed in the lab.

A geometric approach to vectors, matrices and vector fields and their applications to forces and velocities in three dimensions.

1. Find the scalar and cross product of vectors with applications includingthe projection of vectors, angles, areas, volumes and angular velocity

2. Find the vector equations of lines and planes in three dimensions

3. Determine the linear independence of vectors with geometric interpretation

4. Find linear transformations and isometriesas matrix operations includingrotation and reflection. Findeigenvalues and eigenvectors

5. Calculate the radial and tangential components of rotating systems

6. Calculatethe gradient of a scalar field and the divergence and curl of a vector field

Control Systems is all about plant and processes (systems) how they behave when subjected to certain inputs (system response) and how to get them to do what we want (system control). Control Systems 302 introduces the student to analog and digital strategies for controlling these systems

1. Carry out practicals using analog control techniques on mechanical and fluid equipment.

2. Derive the difference equations for numerical integrators and differentiators.
3. Test for discrete system stability by location of the z-plane poles.
4. Design digital controllers using cancellation pole placement, one-step-ahead and Kalmanand Diophantine pole placement strategies.

5. Implement simple machine learning strategies in linear regression, logistic regression and neural networks using Matlab/Octave software.

6. Use software (e.g. LabView, Simulink) to tune PID controllers.

This module deals with various automation technologies ranging from:

Advanced PLC Programming

Scripting to interface with PLC

Embedding C# or other languages into PLC applications

Safety BUS PILZ stop buttons

Apply these technologies to routine industry scenarios

1. Apply advanced PLC programming

2. EmbedC# or other languages into PLC applications

3. Apply scripting to interface with PLC

4. Implement machinery safety using Pilz SafetyBUS p standard

5. Apply the above technologies to routine real-life industry scenario

This is an introduction to robotics that entails the mathematical modelling of robotic movement as well as the programming of key movements for the building and design of basic robots.

1. Choose and integrate hardware components for a simple robotic system.

2. Design and synthesize simple software control systems for individual robotic joints

3. Develop and implement mathematical models of multi-link robots to describe the relationship between individual joints and the position and velocity of the robot’s end effector

4. Apply elementary computer vision techniques to control an intelligent robot.

5. Program simple paths and tasks on articulated robotic arm platform.

6. Design and report development of practical robotic systems that incorporate all of the above.

Review of Data Acquisition, Automation System Architecture – Hierarchical Levels, Functional Layered Models – OSI reference model, System engineering approach, Input / Output Structures, Control Unit Structure, Protocols, Communication principles and modes: network topology, transmission media, noise, cable characteristic and Instrumentation and control devices..

1. Understand the function of a bus protocol.
2. Perform the ID and IO check of an ASI Bus.
3. Explain alternating pulse modulation
4. Explain the functionality of Ethernet

5. Display an understanding of how the microprocessor computes data.
6. Demonstrate IEEE-488 devices and programming

7. Use LabVIEW client/server software

This module will involve preparation for the Work Placement modules and will address relevant industry standard and codes of practice. Students will identify gaps in personal knowledge and skills, devise personal career development plans and prepare for Continued Professional Development.

1. Identify gaps in personal knowledge and devise a personalised career development plan.
2. Outline the role that professional engineers play in the context of organisational teams, reporting structures, management practices and leadership styles.
3. Interpret the requirements of various industry standards in precision engineering and manufacturing industry.
4. Generate engineering documentation that reflect best practice.

Control Systems engineering is all about plant and processes (systems) – how they behave when subjected to certain inputs (system response) and how to get them to do what we want (system control). Control Systems Analysis and Design 401 addresses techniques for design of common industrial controllers.

1. Apply physics-based and System Identification techniques to obtain Laplace Transform models of first and second order systems

2. Obtain a root locus plotand understandits role in control system design and analysis

3. Understand the concept of frequency response and its role in control system design

4. Apply various design techniques to design of PID and Digital PID controllers

5. Use appropriate software for computer aided design, simulation, testing and analysis of the control design strategies outlined.
6. Write a professional report on the process of modelling, analysis and control system design applied to practical project work.

This Module includes: Climate Change and associated challenges for sustainability, energy management and standards. Specific topics covered include; Climate Change & Green House Gases, Sustainability and Renewable Energy, Irish Energy Structure, EU/national targets, ISO 50001, SEAI programme in Ireland in terms of Energy Management, Energy Efficiency, , Environment Management /GHG/EPA.

1. Describe sustainability challenges from Engineering perspective (GHS, fossil fuel dependency trends, Energy Balance)

2. Describe key features of energy trading including wholesale and retail tariffs for gas and electricity.

3. Solve/analyseusing M&V reportof monitoring and verification based on IPMVP internal protocol

4. Develop understanding of new/emerging smart energy technologies – emphasis on smart grids and renewables/EVs.

5. Understand ISO 50001 and the structured approach to managing energy (Energy MAP approach).

6. have a strongand soundly technical appreciation of environmental management including role of EPA as statuary body Waste Management/Industrial Emissions Directive licensing from EPA.

This module presents the foundational image processing material that is required for diverse areas of Robotics, Remote Sensing, Computer Vision, Medical Imaging etc. It introduces what digital images are, how they are presented, how to analyse them and how to process them for specific use cases. Image Processing may be an end in itself, e.g. to present to a the image in a better form for human viewing, or as the first part of a computer vision pipeline.

1. Analyse the statistics of images

2. Perform appropriate operations on images to achieve a desired result

3. Enhance images with consideration of the ethical implications.

4. Restore Images based on prior knowledge

5. Segment images based on appropriate criteria.

On successful completion of this module the student will demonstrate competence in AC circuit analysis ,an understanding of electro-magnetic theory as applied to the construction and operation of DC motors and an ability to evaluate and demonstrate the behaviour of electronic DC drive circuitry.

1. Classify power electronic devices and circuits.
2. describe in block diagram form the structure of a motor drive system.
3. Apply Phasor techniques to problems in AC Network analysis, particularly to those circuits containing reactive impedances.
4. Develop the concept of an electric motor from first principles with the aid of electrical and electro-magnetic theory.
5. Evaluate the behaviour of basic converter circuits with the aid of computer simulation software.
6. Analyse the behaviour of a variety of conventional DC electric motors.

This module aims to provide learners with the statistical tools associated with the six sigma DMAIC philosophy specifically in the areas of Measure, Improve and control consistent with the ASQ and Quality America Green Belt Body of Knowledge. The student will be able to perform basic statistical analysis, develop and plots control charts, determine process and measurement capability. Minitab statistical software will be used to demonstrate and apply these statistical techniques.

1. Perform basic probability calculations by applying the probability rules and concepts
2. Describe and interpret the common probability distributions
3. Calculate, analyse and interpret measurement systems
4. Perform process capability and process perfromance analysis and interpret the results.
5. Perform exploratory data analysis using multi-vari charts, correlation and simple regression
6. Perform basic hypothesis testing eg. Hypothesis testing of means
7. Perform one way analysis of variance
8. Describe the experimental design terms and process
9. Develop control charts for variable and attribute data and interpret the results
10. Develop control charts with Minitab
11. Use the six sigma tools to implement control and monitoring systems

The work-placement/ internship component is an integral part of the academic programme. The aims of the component are to: Offer the student the opportunity to apply the knowledge and skills gained throughout the course in a relevant work-place setting; Facilitate the student in developing the practical competencies and communication skills necessary to function as an effective team member in the work environment.

Where it is not possible to secure a work placement for a student, an alternative of an industry related project will be available addressing the same learning outcomes.

1. Contextualise the knowledge gained in the programme in an area relevant a selected area of interest.

2. Describe the organisation of the host company/organisation and his/her role within it.

3. Describe the operational practices within the host enterprise

4. Apply the practical skills acquired on the academic programme within the workplace.

5. Work as a member of a team and have developed appropriate communication and interpersonal skills.

6. Understand and behave ethically in a range of work settings.

Level 8 Mathematics for 4th year classes in Mechatronics, Mechanical and Electronic Engineering.

1. Use Taylor’s series to approximate transcendental functions

2. Use Fourier series to approximate periodic functions

3. Calculate Discrete Fourier Transforms and inverse Discrete Fourier transforms of signals

4. Solve first and second order difference equations using z-transforms
5. Demonstrate an understanding of the concepts of vector space, dimension, rank, linear independence and spanning sets

6. Solve geometrical problems using the i, j, k orthogonal triad system, and compute dot products and cross products. Compute projections and angles between vectors and interpret results geometrically
7. Use first and second order differential and difference equations and linear algebra to model and solve engineering problems

The subject aims to give the student the skills to design and build Supervisory Control And Data Acquisition (SCADA) and distributed control systems software using graphical programming techniques

1. Acquire the necessary skills to produce visual models of real world events
2. Demonstrate a proficiency in the design and development of a HMI
3. Broaden a knowledge of the theory behind and techniques employed in program design
4. Use visual programming techniques (i.e. Labview) to interface with industrial hardware
5. Understand the function and application of networkingprotocols

6. Understand the deployment of SCADA software for the development of increasingly complex tasks.
7. Be able to implement remote telemetry over a Client/Server architecture.
8. Understand OPC Server and Client communication.

The aims of this module are to investigate current electronic motor drive technology as it applies to both DC and AC electric machines.The module is delivered by way of lectures, practical demonstration of motor and drive types and student simulation of a vareity of drive circuitry using PSIM software.

1. Analyse the operation of single and 3-phase controlled rectifier circuits
2. Perform computer aided solutions and simulations, where appropriate.
3. describe in block diagram form the structure of a motor drive system.
4. Analyse the behaviour of coventional AC Induction motors
5. Comprehend the operation of AC VAriable Speed Drives and DC motor drives.
6. Develop the AC motor equivalent circuit and the DC motor transfer function for conventional machines.

Robotics is revolutionary and transformative technology that will influence all areas of society. It is an important application of the mechatronics discipline. This module extends the introductory module AUTO07035: Introduction to Robotics. The unit introduces the fundamental technologies and mathematical techniques that underpin modern mobile robotics. After completing this course, students will be able to choose suitable algorithms and software techniques for a mobile robot design required to implement intelligent localisation, navigation and control functions.

1. Design and implement motion controllers for a wheeled mobile robot.

2. Design and implement a navigation system to plan the motion of a mobile robot to a goal.

3. Design and implement a localization system to determine the position of a mobile robot with respect to its environment.

4. Apply probabilistic estimation techniques to problems in mobile robot localization and mapping.

This module introduces students to the research process, methodologies and methods and the preparation of a dissertation proposal. The module supports the production of a dissertation in further stages/studies.

1. Provide an overview of the research process and the skills of the researcher
2. Undertake a preliminary literature search
3. Distinguish quantitative and qualitative approaches and methods and discuss issues of reliability and validity in research design
4. Frame a research/dissertation proposal
5. Select appropriate methods for data collection and analysis

Industrial Networking introduces the student to the concept of integrating factory floor industrial networks and process plant floor control networks with company enterprise networks.

1. Demonstrate a basic knowledge of industrial data networks
2. Use network simulator software to build a virtual Industrial Network
3. Demonstrate the ability to build aTCP/IP based network to a specified topology design using network simulator software

4. Demonstrate the ability to build a subnetted network infrastructure using router configuration techniques

5. Demonstrate an understanding of the characteristics and challenges of integrating fieldbus and enterprise networks in the same network domain

Engineers can expect to be involved in making strategic decisions and so will need to be able to understand how financial decisions are made. As engineers move up to management roles they should be able to understand and control the performance of the company and influence the decisions taken.

1. Understand annual and management accounts and interpret balance sheets.

2. Be able to cost products.

3. Be able to participate in investment decisions, calculating rate of return, payback periods, and net present value.

4. Understand how the stock market operates and how decisions taken by management can influence share price.

5. Formulate a business plan

This module presents the fundamental processes that allow computers to view and make sense of the world. Computer Vision includes both the physical hardware for acquiring the image, the environment in which the image is acquired and the classical algorithms for understanding the acquired image. This may be taken as a standalone module or in conjunction with an Image Processing and Deep Learning module to complete the low, mid and high-level computer vision domains.

1. Categorise and explain the various parts of an image acquisition system

2. Identify and match features in corresponding images

3. Re-construct 3D features from stereo images

4. Track the movement of features between corresponding images

5. Perform computational photography techniques on image sets.

This module investigates the physical and technical foundations, strengths and weaknesses of sensors systems used in Advanced Driver Assistance Systems and Self Driving Vehicles.

1. Assess optical radiation, radiometric and photometric quantities.

2. Explain the hardwarearchitecture of visible and infrared spectrum camera systems and their role in the automotive environment.

3. Summarise the functional characteristics and properties of modern Lidar, Radar, Ultrasonic and other relevant sensor systems and their applications in self-driving vehicles.

4. Evaluate the strengths and weaknesses of sensing technologies for specific applications in autonomous vehicles.

5. Select suitable sensor systems for perception and localisation tasks in self-driving vehicles

Control Systems Engineering is all about plant and processes (systems) how they behave when subjected to certain inputs (system response) and how to get them to do what we want (system control). Control Systems Analysis and Design 402 introduces the student to the state-space method of modelling and controlling multiple input and output systems.

1. Derive in matrix form, the set of state equations for a multiple-input-multiple-output (MIMO) system ( simple mechanical (linear and torsional), electrical and electro-mechanical systems)
2. Use matrix methods to determine whether a system is controllable and/or observable.
3. Design State Variable Feedback regulators for MIMO systems

4. Design tracking system controllers in state-space

5. Design full order state observers for state-space systems

6. Use Computer Aided Analysis and Design software in the simulation, analysis and design of state-space models and controllers

7. Write a professional report on the process of modelling, analysis and control system design applied to practical project work.

This course develops skills for designing, funding, and implementing renewable energy projects globally, focusing on power grid infrastructure changes. Students learn to design photovoltaic, wind, biomass, geothermal, and other large-scale sustainable energy operations. The course covers best practices for engaging rural and indigenous communities, promoting economic development and social equity. Additionally, students explore land rights, long-term energy agreements, green certificates, and governance. They also learn to prepare project proposals and assess viability for international financial institutions and private investors.

1. Plan and design a solar photovoltaic farm, wind farm,waste to energy gasification and bio-digester to produce gasplant for connectionat High Voltage and local microgridand understand the impact of thesetechnologies on the power grid

2. Implement best practices and adherance to international standards and protocolsfor managing and building infrastructure projects related to renewable energies in a range of geographies

3. Calculate the basic health and environmental effects of implementing different renewable energies (clean electricity and biofuel options) in different sites around the world)

4. Understand governance regarding green energy(contracts, green certs), manage the supply chain for supplies, components and assemblies of renewable energy systems (solar panels, wind turbines, bio-refinery supplies, etc.)), prepare business plans for renewable energy projects and present these projects to potential investors

5. Understand the technologies relating to Industrial 4.0 including fundamentals of electric vehicles, industrial load requirements,power requirements(battery charging, STATCOM)and trends in consumer electrical requirementsgoing forward

In Project 400 students will undertake a significant piece of independent work under supervision. The module aims to encourage innovation, exploratory learning and to act as an integrating module to allow the student to draw on knowledge learned in previous years. The module exposes the student to the application of research methodologies and aims to develop critical thinking and analysis skills.

1. Develop a major project by working either individually or in a small team to a deadline involving, inter alia, planning, and coordination of design & development activities, setting realistic work objectives, and presenting and documenting the work undertaken.
2. Undertake a comprehensive review of relevant and appropriate literature to determine current knowledge in the project area.
3. Demonstrate initiative, analytical, and problem-solving skills in developing a detailed, viable methodology for addressing an open-ended problem.
4. Integrate and evaluate the relevance, strengths, and weaknesses of approaches developed throughout the programme.
5. Produce a written thesis which meets the required standards of scholarship and technical expertise.
6. Demonstrate the appropriate written and oral communication skills required of a professional practitioner.

This module presents the cutting edge of Computer Vision. While Deep Learning is not new, it has only recently revolutionised Computer Vision due to the wide availability of large image data sets and the computing power necessary to train deep neural networks. This module will look at the methods for designing, training and testing both classification/recognition type networks as well as image-to-image and generative networks. This module can be taken as a standalone or as the final part of stream, which includes Image processing and Computer Vision modules.

1. Assess the performance of Deep Learning models

2. Train Deep Learning models for visual recognition

3. Devise an appropriate architecture to solve a computer vision problem

4. Question the ethics and bias of Deep Learning algorithms

5. Interpret state of the art Deep Learning literature