Training and development in Irish technology companies

The sustained economic growth that has been experienced in the Irish economy in recent years has relied, to a large extent, on the contribution and performance of those industry sectors that possess the ability to provide high-value-added products and services to domestic and international markets. One such contributor has been the Technology sector. However, the performance of this sector relies upon the availability of the necessary capabilities and competencies for Technology companies to remain competitive. The Expert Group on Future Skills Needs have forecasted future skills shortages in this sector. The purpose of this research has been to examine the extent to which Irish Technology companies are taking measures to meet changing skills requirements, through training and development interventions. Survey research methods (in the form of a mail questionnaire, supported by a Web-based questionnaire) have been used to collect information on the expenditure on, and approach to, training and development in these companies, in addition to the methods, techniques and tools/aids that are used to support the delivery of these activities. The contribution of Government intervention has also been examined. The conclusions have been varied. When the activities of the responding companies are considered in isolation, the picture to emerge is primarily positive. Although the expenditure on training and development is slightly lower than that indicated in previous studies, the results vary by company size. Technical employees are clearly the key focus of training provision, while Senior Managers and Directors, Clerical and Administrative staff and Manual workers are a great deal more neglected in training provision. Expenditure on, and use of, computer-based training methods is high, as is the use of most of the specified techniques for facilitating learning. However, when one considers the extent to which external support (in the form of Government interventions and cooperation with other companies and with education and training providers) is integrated into the overall training practices of these companies, significant gaps in practice are identified. The thesis concludes by providing a framework to guide future training and development practices in the Technology sector.

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.