The concept of risk management in the renewable sector.

This study explores the perception of risk and the level of risk management implementation in the renewable sector. Risk management is emerging as a key issue due to the loss of confidence amongst banks, causing the attainment of financing to be difficult over the next few years. To attract financing, there is a fundamental requirement to manage risk in a way that minimizes the probability of a negative financial impact on the project. Miller and Lessard (2001) argue that successful projects are not selected but shaped with risk resolution in mind. Rather than evaluating projects at the outset based on projections of the full set of benefits, costs and risks over their lifetime, successful developers start with project ideas that have the potential of becoming viable. Therefore, this study bridges the gap that exists within the renewable sector in relation to risk management literature. This study succeeds through a detailed comparative case study analysis where two developers and two financiers were questioned through qualitative semi-structured interviews on the concept of risk management and its level implementation within the industry. It is believed that the growth in financed renewable energy projects depends on the adequate design and implementation of risk management to mitigate inherent project risks. However, this study revealed that are certain types of developers in existence within the renewable sector, which underestimate the magnitude of risk and view the development of projects as a ‘money racket’. Therefore, it can be concluded that perception of risk will also differ, causing risk and uncertainty to vary from project to project, resulting in investment reluctance to be associated with certain projects. The study originality lies in how it demonstrates to developers the concept of risk management, outlining the simplicity and benefits of implementing it in project development. Finally, this study contributes to the knowledge by enhancing the awareness and understanding of the presence and nature of risk in a RE project environment.

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.