The Key to this module is to broaden the student's knowledge on Industrial PLC Systems. This module will focus on advanced Ladder logic coupled with Human Machine Interface and Motor Control all of which will be tied into the PLC via a networked system. On Completion the Learner will be able to engage in complex system design and work on debugging and troubleshooting advanced PLC Problems.

1. Explain advanced PLC ladder logic programmes.
2. Design, implement and test HMI applications.
3. Implement motor control in conjunction with variable speed drives and the PLC.
4. Explain the key concepts behind networked system such as Melsec-net, Modbus, Profibus and CAN.
5. Design and test emergency stop functions with integration via the PLC.
6. Explain key areas where automation can be appropriately integrated with robotics.

The aims of this syllabus are to understand and use the principles of mechanics to analyse and solve problems in shaft and rotor vibration, gyroscopic motion and the balance of reciprocating masses and to use the principles of mechanics of materials to analyse failure modes and fatigue.

1. Analyse and solve problems in the Vibration of complex Rotor systems
2. Develop solutions to problems in transverse Vibrations of beams and the Whirling of shafts
3. Evaluate couples and reactions due to Gyroscopic Motion
4. Analyse and solve problems in the balancing of Reciprocating masses
5. Produce solutions to problems in Fatigue and failure of components under static and time varying loads.

The aim of this module is to prepare students for a career in a range of industries requiring mechanical design and analysis or new product development using advanced tools and techniques. Students will develop their understanding of Computer Aided Analysis in the design process and production setting. The module gives the student an applied knowledge in two areas of computer aided engineering including mathematical modelling using appropriate software and engineering simulations using Finite Element Analysis.

1. Explain the role of analysis and simulation in the design process and productionsetting
2. Implement curve fitting techniques using appropriate software
3. Interpret, filter, sort, analyse and graphically present production performance data using an appropriate software
4. Generate an appropriate Finite Element Analysis (FEA) model from a 3D CAD (Computer Aided Design) model
5. Perform a Linear Static Stress Analysis using Finite Element Analysis (FEA) software
6. Carry out the necessary checks to verify & validate an FEA Stress Analysis.

The Engineering Management module will introduce the learner to the operations management field and how this contributes to the strategic success of an organisation. The learner will explore a variety of techniques used in engineering operations for planning and control. The module will enable the learner to demonstrate knowledge and understanding of a broad range of lean process improvement techniques within a service/manufacturing setting. Learners will develop their ability to visualise and solve problems using quantitative models.

1. Use inventory planning and control techniques to evaluate stock requirements.
2. Recognise and describe the essential elements of quality assured organisations.
3. Develop statistical control charts for attributes and variables to ensure processes are in control.
4. Explain how lean synchronisation and the associated tools can improve operations performance.
5. Measure and manage risk and recovery for an operation.

This module provides the learner with a further understanding of thermodynamic concepts and the physical and engineering aspects of renewable energy. Additionally, the learner is provided with a critical evaluation of the technology underpinning exploitation of mechanical sources of renewable energy. An awareness of the application of thermodynamics to sustainable energy management and its economic, social, economic and policy impacts is created.

1. Integrate thermodynamic systems and concepts for application in sustainable energy management.
2. Evaluate conduction and convection heat transfer for typical mechanical examples.
3. Predict radiation heat transfer for typical mechanical examples.
4. Compare the technology underpinning solar and photovoltaic energy generation.
5. Critique the technology supporting energy generation using hydroelectric, tidal, wind and wave sources.

This module provides students with the opportunity to undertake an independent research project in a selected area of Mechanical Engineering. The chosen from a very broad range topics from within the engineering discipline and can be associated with Industry or STEM activities within the institute. Students gain an appreciation of topic scope, breadth and challenge associated with isolating variables to be evaluated by typically two of the following options including: computer aided simulation, numerical methods and experimental procedures. Students learn to conduct a critical literature review and enhance their communication skills through presentation of their proposal in written, oral and poster formats.

1. Identify an engineering parameter that lends itself to optimisation
2. Interrogate literature and research theories beyond that taught at level 8
3. Identify key quantitative and qualitative variables associated with the selected area of research
4. Plan an analysis process using simulation, experimentation, or numerical methods
5. Communicate research and proposed methods through various media including PowerPoint
6. Apply research concepts, skills and techniques in the construction of a formal report.

This module introduces students to a variety of Data Science and Machine Learning techniques, through practical experience of their use, application and evaluation in Engineering. Students will explore the tools and techniques available to read, analyse and create meaningful visualisations from quantitative and qualitative data to facilitate
decision making. Also, this module addresses the key elements of mathematics, Python and algorithms required to understand the field of Machine Learning and its application in Engineering. The module examines supervised and unsupervised approaches to Machine Learning with Regressions, Decision Trees, Random Forests, Ensemble Methods, Support Vector Machines, Clustering, Naive Bayes and Neural Networks encompassed as key topics.

1. Pre-process, manipulate and analyse a broad range of data types using Pandas.
2. Produce appropriate data frames and provide high quality visualisations for decision making.
3. Apply algorithms to develop mathematical models which resolve issues in Engineering.
4. Distinguish between supervised and unsupervised Machine Learning and apply these techniques.
5. Review the theoretical underpinning of Neural Networks and apply these techniques.

This module provides the learner with an understanding of the analysis of heat engine cycles, especially Air Standard cycles. Additionally, the learner is provided with a critical analysis of the benefit of bioenergy in renewable systems. The learner is introduced to the field of Psychrometrics and the analysis of air conditioning systems. The learner is provided with an awareness of the application of thermodynamics to sustainable energy management and its economic, social, economic and policy impacts.

1. Compare and critically analyse heat engine cycles through calculation of work output and efficiency.
2. Analyse the efficiency of various categories of bio-energy and their applications.
3. Perform design calculations for air-conditioning systems and cooling towers through the application of the principles of psychrometrics.
4. Critique the integration of thermodynamic systems and concepts and renewable energy sources in sustainable energy management.

This module will develop the technical knowledge of the student in areas relating to Computer Aided Engineering (CAE). The aim is to heighten awareness of developments in the field of CAE and to understand how CAE systems are integrated to enhance the product development process. Students will obtain an applied knowledge of the latest CAE technologies, including CADCAM and CNC (Computer Numerical Controlled) Simulation, Reverse Engineering/Scanning and Additive Manufacturing.

1. Recommend best practice in design methodologies and processes.
2. Select suitable tooling and processes for a variety of machining applications.
3. Create CNC programmes using CAM (Computer Aided Manufacturing) software to milled and turned components
4. Simulate and verify CNC programmes.
5. Carry out the scanning & reverse engineering of engineering parts.
6. Design a part/assembly for additive manufacturing.

This module ensures the learner understands project management tasks such as developing, managing, implementing, closing and evaluating the project plan. Students will gain an overview of the ethical and societal issues pertaining to engineering. This will review various intellectual property rights including copyright, patent, trademarks, and patents. Students will learn marketing techniques and practice these techniques by developing an online presence on linked in and other platforms to enhance their own employment opportunities. Students will examine Continuous Professional Development & Lifelong Learning.

1. Apply basic management ideas, principles and skills to the management of projects
2. Plan, schedule and control projects
3. Analyse ethical issues with respect to the design and manufacture of goods
4. Analyse various intellectual property rights including copyright, patents, trademarks and carry out a patent search
5. Explain key marketing concepts, marketing environment and marketing research
6. Develop personal marketing skills using LinkedIn or other platforms to attract employment opportunities

This module provides students with the opportunity to undertake an independent research project in a selected area of Mechanical Engineering. The aim of this module is to give the student the opportunity to apply their theoretical knowledge and practical experience in developing, implementing and critically assessing a detailed methodology for a defined problem within a prescribed timeframe. The learner works under the direction of a project supervisor and communicates the process, progress and outcomes of their work in a style and manner appropriate to professionals in the discipline.

1. Display initiative and problem solving skills in developing a detailed, viable methodology for addressing an open-ended problem
2. Design, plan and manage a project within a predefined timeframe
3. Perform critical assessment and review of the research, analysis and solutions derived in a project in an engineering, business and ethical context
4. Develop, design, analyse and apply theory within practical constraints
5. Communicate analysis results by oral means including PowerPoint and Poster Presentation
6. Construct a formal technical report detailing work undertaken and explaining results obtained