Optimising the design and manufacture of a customised, prescription fit, Maxillo-facial prosthesis

This thesis is a continuation of the Enterprise-Ireland Research Innovation Fund (RIF) Project entitled’ "Design and Manufacturing of Customised Maxillo-Facial Prostheses" The primary objective of this Internal Research Development Program (IRDP) project was to investigate two fundamental design changes 1 To incorporate the over-denture abutments directly into the implant. 2 To remove the restraining wings by the addition of screws, which affix the. implant to the dense material of the jawbone. The prosthetic was redesigned using the ANSYS Finite Element Analysis software program and analysed to* • Reduce the internal von Mises stress distribution The new prosthetic had a -63.63 % lower von Mises stress distribution when compared with the original prosthetic. • Examine the screw preload effects. A maximum relative displacement of 22 6 * lO^mm between the bone and screw was determined, which is well below the critical threshold of micromotion which prevents osseointegration • Investigate the prosthetic-bone contact interface. Three models of the screw, prosthesis, and bone, were studied. (Axisymmetnc, quarter volume, and full volume), a recommended preload torque of 0 32 Nm was applied to the prosthetic and a maximum von Mises stress of 1.988 MPa was predicted • Study the overdenture removal forces. This analysis could not be completed because the correct plastic multilinear properties of the denture material could not be established The redesigned prosthetic was successfully manufactured on a 3-axis milling machine with an indexing system The prosthetic was examined for dimensional quality and strength The research established the feasibility of the new design and associated manufacturing method.

Development of a semi-automatic self learning pattern recognition system for the control of electronic boards

This project was funded under the Applied Research Grants Scheme administered by Enterprise Ireland. The project was a partnership between Galway - Mayo Institute of Technology and an industrial company, Tyco/Mallinckrodt Galway. The project aimed to develop a semi - automatic, self - learning pattern recognition system capable of detecting defects on the printed circuits boards such as component vacancy, component misalignment, component orientation, component error, and component weld. The research was conducted in three directions: image acquisition, image filtering/recognition and software development. Image acquisition studied the process of forming and digitizing images and some fundamental aspects regarding the human visual perception. The importance of choosing the right camera and illumination system for a certain type of problem has been highlighted. Probably the most important step towards image recognition is image filtering, The filters are used to correct and enhance images in order to prepare them for recognition. Convolution, histogram equalisation, filters based on Boolean mathematics, noise reduction, edge detection, geometrical filters, cross-correlation filters and image compression are some examples of the filters that have been studied and successfully implemented in the software application. The software application developed during the research is customized in order to meet the requirements of the industrial partner. The application is able to analyze pictures, perform the filtering, build libraries, process images and generate log files. It incorporates most of the filters studied and together with the illumination system and the camera it provides a fully integrated framework able to analyze defects on printed circuit boards.