DCU-Final-Year-Projects-Booklet-2025

95 189. Development of a Parts Feed for Station E of the FMS Rig The project aims to design and build an efficient and reliable parts feeding system for manual assembly. It focuses on station E of the FlexibleManagement System (FMS) rig located at DCU. As a proof of concept froma previous year, the project seeks to improve the process of feeding fasteners to the station for the automated assembly process. This includes enhancing previous mechanical systems and integrating with an existing Programmable Logic Controller (PLC) that is already part of the FMS rig. The main tasks involve the design, construction, and testing of a part presenter, incorporating a robust hopper design to allow automated presentation of parts to station E. Student Programme Mechanical andManufacturing Engineering (Year 4) Project Area Automation, Mechanical Design andManufacture Project Technology Solidworks Student Name(s) Stephen O’Shea Email stephen.oshea25@mail.dcu.ie Supervisor Dr Paul Young 190. Comparing the Accuracy and Repeatability of Different Methods of Composition Measurements of NiTi – EDX& andOES This project aims to determine the composition of NiTi lattice structures produced by PBF-LB using EDX and OESmethods and compare the results to determine the accuracy and repeatability of each method. The type of functional property exhibited by NiTi depends highly on the alloy composition. Even a slight deviation in the equiatomic ratio can significantly affect the transformation behaviours. Ni-rich is generally austenitic at room temperature and exhibits SE. Ti-rich composition is typically martensitic at room temperature and exhibits SME. It is, therefore, important to accurately determine the composition of NiTi parts. The most common method is EDX; however, it can be unreliable, as the parameters used can greatly change the results. An alternative for characterising NiTi is OES. Student Programme Mechanical andManufacturing Engineering (Year 5) Project Area AdditiveManufacturing, AdvancedMaterial Engineering, Automotive Technology, Biomedical Engineering, Mechanical Design andManufacture, Materials Testing, Rocketry Project Technology Excel/VB, R, Optical Emission Spectrometer & Energy-dispersive X-ray Spectroscopy & Laser Powder Bed Fusion Student Name(s) Diego Caton Rasines Email diego.catonrasines2@mail.dcu.ie Supervisor Prof Dermot Brabazon 191. Integrating UML Class DiagramRecognition into the Terminal This system enhances developer workflows by integratingmachine learning-powered image processing techniques to interpret UML class diagrams to allow terminal-based note-taking. Traditionally restricted to text, this approach allows the system to analyse and display diagrams essential for communicating design ideas, systemarchitecture, and workflows in software development. By leveragingmachine learning for image processing the system reads and interprets UML class diagrams allowing developers to view and interact with textual and visual content without leaving their terminal, by displaying UML class diagrams in ASCII art. This eliminates the need for external tools bridging the gap between design documentation and the coding environment. Student Programme Computer Science Project Area Computer Vision, Image/Video Processing, Optical Character Recognition, Software Development, Human-computer Interaction Project Technology Python, Machine Learning Student Name(s) Dzastina Laukaityte  |  FionnMcCloskey Email dzastina.laukaityte2@mail.dcu.ie  |  fionn.mccloskey2@mail.dcu.ie Supervisor Mr Renaat Verbruggen