This module will provide students with a solid foundation in statistics and probability relevant to a manufacturing engineer. The module will develop the students' ability to analyse, solve and understand problems using relevant data in various applications in Manufacturing Engineering.

1. Implement suitable analytic procedures in problems involving discrete and continuous random variables and probability distributions.

2. Performstatistical analysis by hand and with appropriate software and interpret the results.

3. Identify, formulate and solve applied problems using relevant industry based data sets.

4. Communicate their knowledge of statistics and probability both orally and in writing.

This module focuses on the fundamentals of engineering metrology and its applications to manufacturing measurements.This module integrates the concepts, principles and techniques of mechanical measurement with the use of measuring instruments including micrometers, calipers, height gauges, and automated measurement systems.

1. Explain the concepts of metrology and use the language and systems of measurement.

2. Explain the basic features of measurement, gauging, and tolerances.

3. Apply the process of measurement with various measuring devices.

4. Explain of the purpose of critical dimensions in manufacturing and apply inspection, gauging and checking systems.

5. Analyse parts for dimensional and tolerance accuracy and functionality..

This module introduces pneumatic and electro-pneumatic technologies used to control machines. The student will analyse basic pneumatic/hydraulic manufacturing applications and develop automated solutions using Programmable Logic Control (PLC) technology. PLC ladder logic programmes will be designed, developed and tested in accordance with industrial safety standards.

1. Outline the working principles of electro-pneumatic components

2. Describe the components of pneumatic and hydraulics actuation.

3. Simulate basic and multi-actuator pneumatic and electro-pneumatic circuits.
4. Specify, size and select suitable pneumatic components for industrial applications
5. Construct ladder logic programmes using Boolean Logic, IOs, timers, counters, sequencing
6. Design and test PLC programs

7. Identify andimplementsafety measures in the design of automated systems

Manufacturing Engineering 2 develops the ability of learners to practically apply manufacturing engineering methodologies through the correct identification, selection and use of manufacturing processes. In particular, it develops the CNC programming skills of learners. It gives learners a broad experience of both the theoretical and practical elements of Manufacturing for industry.

1. Explain the basic physical, mechanical properties of engineering materials and main testing techniques used in industry.

2. Describe sustainable manufacturing processes and technologies appropriate to a range of applications

3. Generate/Write a CNC Programme for 2 Axis Turning and 3 Axis Milling using a simulator/CAM software

4. Analyse and interpret CNC programforbasic CNC turning and milling operations

5. Demonstrate practical application of manufacturing engineering methodologies through the correct identification, selection and use of manufacturing processes using laboratory equipment or workshop machinery.

Industry Module 2 is the "on the job learning" module, where supported learning takes place in the apprentice's company.

1. Select the appropriate tools, methodologies and techniques to solve manufacturing problems, and design and implement solutions.
2. Analyse, measure performance and continuously improve manufacturing processes with innovative technical solutions.
3. Communicate findings to teams and management, and work effectively as a team member.
4. Describe and communicate how the regulatory constraints affect the operations of the company, and how ethical considerations affect their conduct as a technician.
5. Apply management skills within their occupation as a technician.
6. Reflect on their experiential learning, and their ability to solve problems using a structured technical approach, and identify gaps.

This module develops the learner's skills in fixture design in support of manufacturing, taking into account operational considerations, maintenance and repair and design for manufacturability. Learners will perform three-dimensional (3D) Computer Aided Design (CAD) modelling, and construct solid models relating to parts and assemblies.

1. Explain the fundamentals of part orientation and principles of workholding.
2. Describe the design of systems for part orientation & holding
3. Select the relevant method of actuation of fixturing systems
4. Describe specific fixturing system types
5. Use CAD to design and implement a fixture related project

This module provides a solid understanding of the concepts, processes, and legislation for Risk Assessment, Risk Management, and Health and Safety Management. The module develops the student's ability to identify and select maintenance practices that are appropriate for real workplace scenarios and distinguish their respective impacts on system reliability.

1. Recognise the risks and hazards associated with machinery, equipment and workplaces, identify control measures necessary for Health and Safety management, and prepare relevant safety documentation

2. Analyse and compare different Maintenance Management strategies such as breakdown, planned and preventive maintenance techniques and apply them to appropriate workplace situations.

3. Illustrate the reasons for and benefits of maintenance systems such as TPM (Total Productive Maintenance) and RCM (Reliability Centred Maintenance) in a workplace environment

4. Develop an implementation plan for anew workplace maintenance system and schedule and appraise a maintenance system currently in place

5. Assess equipment effectivenss, maintenance economics, work scheduling and reliability, and FMEA (Failure Mode and Effects Analysis)

This module is designed to provide students with an understanding of the purpose of quality management systems, and of the relationship between the different ISO quality standards. Learners will appreciate the impact that Risk Assessment has on the decision-making process for manufacturing firms. The module also introduces Process Validation, and Corrective and Preventive Action.

1. Describe the purpose of a quality management system and explain the 8 principles of quality management.
2. Explain the purpose, content and interrelationship of quality management standards ISO9000, ISO13485, auditing and assessment standards ISO9004, ISO19011 and sustainability standards ISO14000, ISO15001 and ISO2600.

3. Explain Risk Management, how to identify and quantify risks, decide on the acceptability of those risks and re-evaluate risks following corrective actions. Explain the impact that ISO14971 Risk Management has on the decision-making process in the medical device industry.

4. Apply various risk assessment methodologies such as FMECA, Fault Tree Analysis and HAZOP.

5. Explain the context of Process Validation within the quality management system and describe the steps needed to conduct a Process Validation.
6. Identify and distinguish between a correction, corrective action and preventive action and identify a process to implement corrective/preventive actions.

This module gives an introduction to Lean Engineering Concepts and Tools (including Lean Manufacturing and Lean Services), and to the Principles of Change Management. Lean manufacturing, originally developed by Toyota, is widely practiced in Irish industry and is vital for its continued competitiveness.

1. Explain the principles of lean engineering and change management and their applicability to manufacturing, services and to the interaction with customers.
2. Perform data analysis in MS Excel to solve Lean Engineering problems.
3. Review and comment on lean case studies
4. Perform lean manufacturing analysis (Value Stream mapping, Overall Equipment Effectiveness, Takt Time Calculation, Process Throughput measurement, 5S) to identify areas for improvement, and solve problems
5. Evaluate problems and select optimisation solutions appropriately, in order to ensure that an ethical engineering approach, including addressing the impact on society and sustainability,is taken.

This module develops the learner's knowledge and skills in sensors, control theory and industrial robotics. Students gain an understanding of the application of electrical, electronic and mechanical sensors and actuators. This module introduces control in the engineering context and studies mechanical, electrical and fluid systems. Students are introduced to r obot anatomy, maintenance and safety and programming, materials handling and vision systems.

1. Describe the principle of operation andcharacteristicsof sensors and actuators

2. Identify the components of data acquisition including signal conditioning and digital interfacing.

3. Use appropriate technologies and software programming packages to measure, analyse and control systems
4. Analyse control concepts including open loop, closed loop, relays, motor control, sequential control, process control, PID control.
5. Identifythe environments in which control systems operate and calculate thesteady-state error, stability and speed of response of the system.

6. Investigate robotic capability, technology and anatomy
7. Develop and execute robotic simulation programmes; and practical training using 5 and/or 6 axis robots.

The module exposes the learner to modern manufacturing processes and techniques with special emphasis on non-traditional practices. It also incorporates the practical use of CAD/CAM and Mould & Cavity software to generate machine code. This module focuses on Modern Industrial Practices that can aid the learner in their Industry.

1. Explain the basic elements of modern advanced manufacturing techniques and production processes and explain the benefits of innovated technologies, including Internet of Things (IoT), interoperability, information transparency, and decentralized decisions for Industry 4.0 and 5.0.

2. Summarise the principles of traditional manufacturing processes.

3. Summarise the principles of non-traditional manufacturing processes.

4. Use CAM software in the generation ofG and M codes for the manufacture of components on CNC machine tools, in line with Sustainable Engineering best practices.

5. Apply principle(s) of Advanced Manufacturing Processes to an Industrial Application.

The Polymer Processing Module focusses on the materials, processes and tooling used in relation to polymers, particularly analysis of the polymer flow processes involved in injection moulding and extrusion. The practical aspect supports the design and manufacture of the tooling used in these processes.

1. Explain relevant techniques to manufacture plastic parts, in a Sustainable world.

2. Explain the fundamentals of the synthesis of plastic materials

3. Explain polymer melts rheology and its effect on polymer processing parameters.

4. Use mould cavity software to generate,design and optimise Moulds.

5. Useappropriate software to analyse flow and other parameters of the mould.

The module delivers the essentials of programming/coding skills to automate and visualize data analysis problems appropriate to the needs of the engineer in manufacturing or related industry.

1. Describe the core concepts of computer programming.

2. Writeprogrammes/codes, incorporating core programming conceptssuch assequential, conditional, iterative and control structures

3. Design an effective event-based software application incorporating spreadsheets to address basic engineering and production requirements.

4. Construct the designed software application using a commercial application development environment.

5. Roll out the constructed application, including performing Test, Debug and Demonstration activities.

Industry Module 3 is the "on the job learning" module, where supported learning takes place in the apprentice's company.

1. Lead technical projects and design and implement technical solutions under quality systems and procedures.
2. Participate in process planning according to company quality policies and system.
3. Investigate, analyse, evaluate and report on the performance of a process plan.
4. Undertake a six sigma project and communicate the findings to staff and management.
5. Apply management skills within their occupation as an engineer and describe their ethicial obligations as an engineer.
6. Reflect on their experiential learning and their ability to solve problems using an engineering approach, identify gaps and devise self-learning strategies.

The aims of this module are to help the students develop an understanding of the underlying knowledge and related methods of Process Planning and Computer Aided Process Planning, and to equip the students with the skills required in carrying out the process planning (PP) function.

1. Describe the process planning functions, the role of process planning in manufacturing, the characteristics of traditional and Computer
Aided Process Planning (CAPP) systems, the structure of typical CAPP systems and Group Technology (GT).

2. Implement Manual Process Planning system in consideration of process planning criteria, and industrial considerations.

3. Implement Computer Aided Process Planning (CAPP) systems in consideration of process planning criteria, and industrial considerations

4. Identify relevant principles of Design for Manufacture and Assembly (DFMA), philosophy, implementation and functionality, assembly systems and costing

5. Identify issues relevant to green manufacturing, design for environment and recycling, part life cycle assessment, sustainability.

An introduction to Six Sigma, which will both explain the concepts and involve using the tools and techniques of Six Sigma.

1. Explainthe Define, Measure, Analyse, Improve and Control steps in Six Sigma.

2. Use ‘Define’ phase tools to decide on the process improvement of a Six Sigma project
3. Determine the current performance using a variety of ‘Measure’ tools
4. Use the ‘Analyse’ tools, including inferential statistics to determine the issues to be addressed.
5. Apply the ‘Improve’ tools, to develop and assess the process optimisation.
6. ‘Control’ the process to verify the variances are corrected, select appropriate statistical process control (SPC) techniques.

This module provide an introduction to key principles, strategies, models and techniques used by organisations in the management of their operations.

1. Identify the legal structures of organisations,role, tools and impact of Operations Management, asorganisations transition to Industry 4.0 and 5.0, within the context of emerging technology trends, such as Big data, GIS (Geographical Information Systems), Cloud computing, IoT (Internet of Things)and blockchains.

2. Apply the stage gate process and engineering tools to Product, Process and Facility design.
3. Use an Enterprise Resource Planning system to perform capacity planning, inventory management and materials requirements planning applying the techniques used in Enterprise Resource Planning (ERP) and Manufacturing Execution Systems (MES).

4. Solve basic operations’ improvement problems of capacity, flow design andjob design taking budgetary concernsand commercial principlesinto consideration.

5. Compare and contrast appropriate strategies and competitive behaviour for sustainable organisations.Factors to include environmental sustainability and corporate social responsibility.

This module teaches students how to professionally plan and manage complex projects for industry using standard approaches. The student learn through in class projects how to use industry standard software tools to support this work.

1. Articulate and explain structured approaches to project planning and management.

2. Apply the principles, methodologies , tools and techniques of project management, including associated financial analysis.

3. Use Project management software to assist in planning and managing projects.

4. Define, plan and manage team-based projects

5. Communicate effectively throughout the project lifecycle, including all necessary reports and presentations required in project planning and management in a real work environment

This module will help students grasp the impact of decision theory and data analytics on manufacturing efficacy and pinpoint relevant applications, also offering a deep dive into data tools like Excel, Power BI, and Tableau.

Simultaneously, this module will develop students' proficiency in data preparation, visualisation, and reporting, bolstered by hands-on practice, online tutorials, and collaborative learning forums.

1. Critically evaluate the role of decision theory in enhancing manufacturing employee and organisational performance as well as contributing to sustainable development goals.
2. Evaluate and contrast different decision-making methods and data analytical software tools.
3. Critically evaluate different methods for identifying and managing risk and uncertainty in decision making.
4. Apply advanced tools and techniques for analysis and visualisation of data.
5. Evaluate and contrast different data visualisations and interactive dashboards.

This module will look at the data architecture of a manufacturing plant from Level 0 [Field Devices] up to Level 4 [Enterprise] in accordance with the ISA-95. On a practical level students will build a SCADA system integrating data from various equipment.

1. Assess the existing data architecture of a manufacturing plant and its components.

2. Design specification for a data architecturebased on user requirements consideringsustainable development goals.

3. Plan horizontal and vertical integration of a data architecture in a manufacturing system, considering validation.
4. Develop a data management system at SCADA level.

5. Evaluate the different Industrial Ethernet protocols EtherNet/IP, PROFINET, EtherCAT, and assign IP addresses to automation equipment, including PACs/PLCs, HMIs, Laptops and IO Link Masters.

This module will look at automated technologies that can support digitalisation of manufacturing, continuous improvement and faster time to market.

1. Investigate the use of Automated Guided Vehicles (AGV), Autonomous Mobile Robots (AMR), Cobots and intelligent conveyors in optimizing process flow.

2. Investigate the industrial uses, safety standards, feasibility and cost-effectiveness of cobotic and robotic systems.

3. Programme PLCs in a manufacturing cell, using the IEC 61131-3 languages.
4. Connect and programme analog sensors within an automated cell.

5. Discuss and assess the requirements for the set-up of an optimal environment for an industrial vision system.

6. Integrate relevant technologies into an automated manufacturing cell, to enablemonitoring,data collection and decision making.

7. Develop a User Requirements Specification (URS) for an advanced automated system for a given application

This module introduces students to emerging and novel technologies, which will impact on industry, and will contribute to the development of sustainable manufacturing enterprises. This include emphasis on emerging trends, such as sustainability, new physical manufacturing technologies and manufacturing line simulation.

1. Research, analyse and review emerging trends in Sustainable Manufacturing

2. Select and justify appropriate smart Additive, Subtractive or Formative Manufacturing processes, and materials suitable for the manufacture of different product types.
3. Produce a variety of products using smart Additive, Subtractive or Formative manufacturing processes
4. Appraise the benefits of adopting Digital Twin technologies when planning a new manufacturing process and optimising an existing process.
5. Develop a 3D simulation model of a manufacturing process

6. Develop a plan for implementing Smart Manufacturing technologies in the industrial context.

This module aims to provide learners with a broad understanding of Validation and Verification in the manufacturing context, including New Product Introduction and new Process or Equipment introduction.

1. Investigate the ethical and regulatory basis for Validation and the related requirements of the manufacturing sector from regulatory bodies.
2. Communicate the key steps required for anyValidation and fully comprehendthe underpinning principles of specification and verification.

3. Implement the principles of Validation to design and develop Validation documents.

4. Apply risk management and change control to Validation activities and Validated entities, e.g. Process, Equipment, Test Methods.

5. Determine and assess the key validation characteristics of a test method and factors that influence test method variability.

This module focuses on the application of statistical tools to the solution of manufacturing problems, with particular emphasis on process characterisation and performance optimisation. Emphasis is placed on the use of a structured problem-solving approach, statistical analysis, hypothesis testing and Design of Experiments.

1. Design a solution to a process characterisation problem, using a structured problem-solving methodology, such as Six Sigma DMAIC or A3 Problem-Solving, and statistical problem-solving tools, while complying with relevant ethical guidelines, and present the project in A3 format.
2. Describe the behaviour of variables, using statistics and probability distributions, conduct Multi-Vari analyis to identify sources of variability, and prioritise input variables by determining which have the biggest impact on the output Y variable, using models of relationships between variables (performing linear, non-linear and multiple regression).
3. Perform Hypothesis testing to evaluate the statistical significance of the effect of engineering modifications to production processes on product quality and variability, using software and first principles,including paired tests, and tests for mean, variance, goodness of fit and proportions, ANOVA and construct confidence Intervals for means, variance and proportion
4. Create an Experimental Design, incorporating selection of appropriate structure, (screening, full and fractional factorial, response surface, Taguchi) and including identification of appropriate inputs, outputs and variables and identification/justification of critical Ys\”.
5. Conduct experiments, analyse the experimental results and residuals, develop prediction equations and make appropriate recommendations.

Industry Module 4 is the "on the job" module for the B Eng (Hons) in Advanced Manufacturing Engineering (Apprentice Mode). Learners work as trainee engineers in the workplace, supported by an Industry Mentor and an Academic Supervisor. The module involves the conducting and reporting on a Final Year Engineering Project.

1. Apply knowledge of the science,technology, engineering and mathematics underpinning Advanced Manufacturing Engineering, in the design and improvement of manufacturing systems.

2. Identify, formulate and critically analyse problems ina Technical Project, using a rigorous, structured, industry-standardProblem-Solving Approach (e.g. DMADV, DMAIC, 8-Steps, A3) and a formal Project-Planning methodology

3. Design appropriate solutions to Manufacturing Engineering problems, employing technology-based solutions and systems-based solutions to enhanceeffectiveness and competitiveness.

4. Investigate to facilitate the solution of manufacturing problems by conducting searches of literature and consulting databases, synthesising and reporting the findings in a written, correctly referenced Literature Review.

5. Contribute effectively to the business, acting ethically and professionally, while considering the sustainability of processes and systems for manufacturing and the role of the Advanced Manufacturing Engineer in society and at work.

6. Work effectively independently and in diverse and inclusive teams, including acting as a Team Leader and Change Agent.

7. Communicate effectively on Manufacturing Engineering activities to diverse audiences,both a concise way (e.g. Verbal update in industry meetings, Shift Hand-over report, Industry Problem Logs, Powerpoint Presentation, Short Video, Academic Poster), and in a detailed way in a written report, structured as a Fourth-Year Engineering Academic Thesis.

8. Select and apply business and engineering management principles, tools and techniques to develop solutions leading to increased competitiveness for the organisation.

9. Reflect on their experiential learning and their ability to solve problems using an engineering approach, identify gaps and devise self-learning strategies.