Developments in cutting tools, coolants, drives, controls, tool changers, pallet changers and the philosophy of machine tool design have made ground breaking changes in machine tools and machining processes. Modern Machining Centres have been developed to perform several operations on several faces of a workpiece in a single setup. On the other hand industry requires high value added components, which have many quality critical features to be manufactured in an outsourcing environment as opposed to the traditional in-house manufacture. The success of this manufacture critically depends on matching the advanced features of the machine tools to the complexity of the component. This project has developed a methodology to represent the features of a machine tool in the form of an alphanumeric string and the features of the component in another string. The strings are then matched to choose the most suitable and economical Machine Tool for the component’s manufacture. Literature identified that block structure is the way to answer the question ‘how to systematically describe the layout of such a machining centre’. Incomplete attempts to describe a block structure as alphanumeric strings were also presented in the literature. Survey on sales literature from several machine tool suppliers was investigated to systematically identify the features need by the user for the choice of a machine tool. Combining these, a new alphanumeric string was developed to represent machine tools. Using these strings as one of the ‘key’s for sorting a database of machine tools was developed. A supporting database of machine tools was also developed. Survey on machining on the other hand identified, that machining features can be used as a basis for planning the machining of a component. It analysed various features and feature sets proposed and provided and their recognition in CAD models. Though a vast number of features were described only two sets were complete sets. The project was started with one of them, (the other was carrying too many unwanted details for the task of this project) machining features supported by ‘Expert Machinist’ software. But when it became unavailable a ‘Feature set’ along those lines were defined and used in the generation of an alphanumeric string to represent the work. Comparing the two strings led the choice of suitable machines from the database. The methodology is implemented as a bolt on software incorporated within Pro/Engineer software where one can model any given component using cut features (mimicking machining operation) and produce a list of machine tools having features for the machining of that component. This will enable outsourcing companies to identify those Precision Engineers who have the machine tools with the matching apabilities. Supporting software and databases were developed using Access Database, Visual Basic and C with Pro/TOOLKIT functions. The resulting software suite was tested on several case studies and found to be effective.

Deep learning approaches have been explored for surgical tool classification in laparoscopic videos. Convolutional neural networks (CNN) are prominent among the proposed approaches. However, concerns about the robustness and generalisability of CNN approaches have been raised. This paper evaluates CNN generalisability across different procedures and in data from different surgical settings. Moreover, generalisation performance to new types of procedures is assessed and insights are provided into the effect of increasing the size and representativeness of training data on the generalisation capabilities of CNN. Five experiments were conducted using three datasets. The DenseNet-121 model showed high generalisation capability within the dataset, with a mean average precision of 93%. However, the model performance diminished on data from different surgical sites and across procedure types (27% and 38%, respectively). The generalisation performance of the CNN model was improved by increasing the quantity of training videos on data of the same procedure type (the best improvement was 27%). These results highlight the importance of evaluating the performance of CNN models on data from unseen sources in order to determine their real classification capabilities. While the analysed CNN model yielded reasonably robust performance on data from different subjects, it showed a moderate reduction in performance for different surgical settings.

Dawson (2009) suggested a twelve step methodology for implementing knowledge management solutions following research which showed that implementing knowledge management solutions was not as successful as expected. This thesis investigates the third of this twelve step methodology which requires finding a knowledge management solution in the context of the problem. The aim of the research is to determine a methodology that will provide a systematic way for managers to select an appropriate knowledge management tool given a particular working environment. Two organisations are investigated to confirm that there is a need for a systematic methodology for selecting knowledge management tools and how a methodology may help in achieving selecting an appropriate tool. This investigation is carried out using case studies, action research and interviews and results in discovering that organisations do not have a systematic method for selecting tools which leads to tools being selected haphazardly and not always successfully. Two tools are developed to aid a manager in selecting a knowledge management tool: the House of Knowledge Management Tool Selection and the Knowledge Management Tool Classification Grid. The House tool helps to identify the knowledge problem being solved and evaluates all potential knowledge management tools against the problem. The barriers to the potential success of the tools are also examined. The grid identifies potential tools by classifying them against knowledge problems. The two tools are further refined and developed using the two organisations as case studies to demonstrate how and when the tools can be used. This leads to development of the Barrier House and the Evaluation Grid. A framework and associated methodology are then developed that can be used as a guide to using the tools, offering a systematic approach to selecting knowledge management tools given any environment and thus accomplishing the aim of the thesis.

The European standard EN 50128 "Railway applications - Communication, signalling and processing systems - Software for railway control and protection systems" is one of the European standards for European Railway systems. It is intended for software aspects, specifying procedures and technical requirements for the development of programmable Electronic systems, which are used in railway control and protection applications. Since 2017- 04-25 the original version EN 50128:2001 has been replaced by the updated new version EN 50128:2011. The update is quite extensive and will effect many parts of the existing Railway systems. The aim of this study is to investigate the effect of the EN 50128 update. The work for this study includes literature study, document research and interview with the relevant supplies and experts. Qualitative and quantitative methods have been used in the study to reach the possible best results. The effects due to the EN 50128 update have been extensively investigated. The following issues have been addressed: - How can the update of the standard EN 50128 be done smoothly by the companies? - How much money have they spent to update their process to follow the 2011 version? - What parts of the process have been the most extensive and expensive to change due to the standard update? The results of the work are useful for an organized and professional assessor to help and support the companies dealing with this complex software, in order for them to be prepared for the upcoming standard update as well as possible. If the affected companies have been proactive in their own development of their methods/techniques, the 2011 version of the standard will not be a major work to follow for their process. A standard is a guideline and a support in the way to a safer system.