An improved approach for automatic process plan generation of complex borings

The authors are grateful for funding provided to this project by the French Ministry of Industry, Dassault Aviation, Dassault Systemes, and F. Vernadat for his review and recommendations.The research concerns automated generation of process plans using knowledge formalization and capitalization. Tools allowing designers to deal with issues and specifications of the machining domain are taken into account. The main objective of the current work is to prevent designers from designing solutions that would be expensive and difficult to machine. Among all available solutions to achieve this goal, two are distinguished: the generative approach and the analogy approach. The generative approach is more adapted to generate the machining plans of parts composed of numerous boring operations in interaction. However, generative systems have two major problems: proposed solutions are often too numerous and are only geometrically but not technologically relevant. In order to overcome these drawbacks, two new concepts of feature and three control algorithms are developed. The paper presents the two new features: the Machining Enabled Geometrical Feature (MEGF) and the Machinable Features (MbF). This development is the result of the separation of the geometrical and the technological data contained in one machining feature. The second objective of the paper is to improve the current Process Ascending Generation (PAG) system with control algorithms in order to limit the combinatorial explosion and disable the generation of unusable or not machinable solutions

An improved approach for automatic process plan generation of complex borings

The authors are grateful for funding provided to this project by the French Ministry of Industry, Dassault Aviation, Dassault Systemes, and F. Vernadat for his review and recommendations.The research concerns automated generation of process plans using knowledge formalization and capitalization. Tools allowing designers to deal with issues and specifications of the machining domain are taken into account. The main objective of the current work is to prevent designers from designing solutions that would be expensive and difficult to machine. Among all available solutions to achieve this goal, two are distinguished: the generative approach and the analogy approach. The generative approach is more adapted to generate the machining plans of parts composed of numerous boring operations in interaction. However, generative systems have two major problems: proposed solutions are often too numerous and are only geometrically but not technologically relevant. In order to overcome these drawbacks, two new concepts of feature and three control algorithms are developed. The paper presents the two new features: the Machining Enabled Geometrical Feature (MEGF) and the Machinable Features (MbF). This development is the result of the separation of the geometrical and the technological data contained in one machining feature. The second objective of the paper is to improve the current Process Ascending Generation (PAG) system with control algorithms in order to limit the combinatorial explosion and disable the generation of unusable or not machinable solutions

A graph-based approach for the retrieval of multi-modality medical images

Medical imaging has revolutionised modern medicine and is now an integral aspect of diagnosis and patient monitoring. The development of new imaging devices for a wide variety of clinical cases has spurred an increase in the data volume acquired in hospitals. These large data collections offer opportunities for search-based applications in evidence-based diagnosis, education, and biomedical research. However, conventional search methods that operate upon manual annotations are not feasible for this data volume. Content-based image retrieval (CBIR) is an image search technique that uses automatically derived visual features as search criteria and has demonstrable clinical benefits. However, very few studies have investigated the CBIR of multi-modality medical images, which are making a monumental impact in healthcare, e.g., combined positron emission tomography and computed tomography (PET-CT) for cancer diagnosis. In this thesis, we propose a new graph-based method for the CBIR of multi-modality medical images. We derive a graph representation that emphasises the spatial relationships between modalities by structurally constraining the graph based on image features, e.g., spatial proximity of tumours and organs. We also introduce a graph similarity calculation algorithm that prioritises the relationships between tumours and related organs. To enable effective human interpretation of retrieved multi-modality images, we also present a user interface that displays graph abstractions alongside complex multi-modality images. Our results demonstrated that our method achieved a high precision when retrieving images on the basis of tumour location within organs. The evaluation of our proposed UI design by user surveys revealed that it improved the ability of users to interpret and understand the similarity between retrieved PET-CT images. The work in this thesis advances the state-of-the-art by enabling a novel approach for the retrieval of multi-modality medical images

Do healthcare services behave as complex systems? Analysis of patterns of attendance and implications for service delivery

Background: The science of complex systems has been proposed as a way of understanding health services and the demand for them, but there is little quantitative evidence to support this. We analysed patterns of healthcare use in different urgent care settings to see if they showed two characteristic statistical features of complex systems: heavy-tailed distributions (including the inverse power law) and generative burst patterns. Methods: We conducted three linked studies. In study 1 we analysed the distribution of number of contacts per patient with an urgent care service in two settings: emergency department (ED) and primary care out-of-hours (PCOOH) services. We hypothesised that these distributions should be heavy-tailed (inverse power law or log-normal) in keeping with typical complex systems. In study 2 we analysed the distribution of bursts of contact with urgent care services by individuals: correlated bursts of activity occur in complex systems and represent a mechanism by which overall heavy-tailed distributions arise. In study 3 we replicated the approach of study 1 using data systematically identified from published sources. Results: Study 1 involved data from a PCOOH service in Scotland (725,000) adults, 1.1 million contacts) and an ED in New Zealand (60,000 adults, 98,000 contacts). The total number of contacts per individual in each dataset was statistically indistinguishable from an inverse power law (p &gt; 0.05) above 4 contacts for the PCOOH data and 3 contacts for the ED data. Study 2 found the distribution of contact bursts closely followed a heavy-tailed distribution (p &lt; 0.008), indicating the presence of correlated bursts. Study 3 identified data from 17 studies across 8 countries and found distributions similar to study 1 in all of them. Conclusions: Urgent healthcare use displays characteristic statistical features of large complex systems. These studies provide strong quantitative evidence that healthcare services behave as complex systems and have important implications for urgent care. Interventions to manage demand must address drivers for consultation across the whole system: focusing on only the highest users (in the tail of the distribution) will have limited impact on efficiency. Bursts of attendance - and ways to shorten them - represent promising targets for managing demand.</p

A distributed decision support system for turning and milling operations using the internet

The machine tool industry is highly dependent on the tooling which is needed to machine the components used to make the range of products seen in today's society. The range of tooling available to machinists is prolific and subject to continual growth. Those engineers faced with the task of process planning require advanced systems to support the decisions that need to be made for the production process to operate smoothly. The tooling data made available by these systems is a key factor in defining the efficiency with which the production processes can be carried out. This research examines the technical decision support systems made available to industrialists and highlights the scope to provide tooling engineers with up-to-date tooling performance and use data that can be used both in the planning stages as well as dealing with problems encountered during production. Specifically, this research identifies the role performed by widespread tool trials, associated with new tools or new materials, and goes on to show how the information obtained from tool trials can be collated in a structured manner and used to enhance the provision of data with which to carry out the process planning task. The goal of this research was to develop and implement a framework capable of collecting and disseminating data related to tool trials in a coherent and supportive fashion using distributed methods. This target resulted in the deployment of a system named JadeT, which is capable of receiving and analysing data from tool trials and subsequently enhancing the process planning task by basing cutting parameter selection on a combination of fundamental cutting parameter algorithms in parallel with using the approved data generated from tool trials. The JadeT system was tested via the creation of a database using actual tool trial reports, and the manner in which this data was used to provide cutting parameters was analysed. The JadeT system has been developed, deployed and evaluated. The opportunity to use data contained within tool trial reports to support process planning tasks has been identified and exploited. The testing of JadeT indicates that the system fulfils the initial goals and was able to provide suggestions for further research in this area

Manufacturing code generation for rotational parts in a feature based product modelling environment

An important element for the integration of CAD/CAM is the representation and handling of data used during the design and manufacturing activities. The use of features and product modelling techniques bring a better handling of this data and provide CAD/CAM with an excellent platform for integration. The thesis explores the use of a predefined set of features in a product modelling environment for the design and machining of rotational components. Theword features in this research implies a set of functional, geometrical and technological information with a unique form. Those features are pre-defined and comprise of a limited number of elements which carry the information related to design and manufacturing activities. The thesis is divided into three main parts. The first part contains a review of topics related to the research e. g. group technology, component features, CAD/CAM and also contains a literature survey of related research works. In the second part the "features" are defined and presented. Also the product modelling environment is explained and the basic rule based procedures which are used to automatize the operation planning activities are presented. In the last part a description of the case-studies used for automatic NC code generation is presented followed by a discussion of the results. Lastly, the conclusions are drawn and ideas for further work presented