11 resultados para Machinery -- Manufacturing processes

em CentAUR: Central Archive University of Reading - UK


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We review the process of electrospinning and how this new technique for generating a rich morphology of nano and micro scale fibres sits alongside established procedures for rapid manufacturing. We introduce the key elements of electrospinning and how these influence the nature and distribution of the fibres produced. We describe the range of polymers available for electrospinning and the limitations to the use of these materials. Using this base we review the potential approaches to using electrospinning as part of a broader rapid manufacturing system and the possible applications for such a hybrid system.

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In the ten years since the first edition of this book appeared there have been significant developments in food process engineering, notably in biotechnology and membrane application. Advances have been made in the use of sensors for process control, and the growth of information technology and on-line computer applications continues apace. In addition, plant investment decisions are increasingly determined by quality assurance considerations and have to incorporate a greater emphasis on health and safety issues. The content of this edition has been rearranged to include descriptions of recent developments and to reflect the influence of new technology on the control and operations of automated plant. Original examples have been retained where relevant and these, together with many new illustrations, provide a comprehensive guide to good practice.

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The overall operation and internal complexity of a particular production machinery can be depicted in terms of clusters of multidimensional points which describe the process states, the value in each point dimension representing a measured variable from the machinery. The paper describes a new cluster analysis technique for use with manufacturing processes, to illustrate how machine behaviour can be categorised and how regions of good and poor machine behaviour can be identified. The cluster algorithm presented is the novel mean-tracking algorithm, capable of locating N-dimensional clusters in a large data space in which a considerable amount of noise is present. Implementation of the algorithm on a real-world high-speed machinery application is described, with clusters being formed from machinery data to indicate machinery error regions and error-free regions. This analysis is seen to provide a promising step ahead in the field of multivariable control of manufacturing systems.

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Data assimilation algorithms are a crucial part of operational systems in numerical weather prediction, hydrology and climate science, but are also important for dynamical reconstruction in medical applications and quality control for manufacturing processes. Usually, a variety of diverse measurement data are employed to determine the state of the atmosphere or to a wider system including land and oceans. Modern data assimilation systems use more and more remote sensing data, in particular radiances measured by satellites, radar data and integrated water vapor measurements via GPS/GNSS signals. The inversion of some of these measurements are ill-posed in the classical sense, i.e. the inverse of the operator H which maps the state onto the data is unbounded. In this case, the use of such data can lead to significant instabilities of data assimilation algorithms. The goal of this work is to provide a rigorous mathematical analysis of the instability of well-known data assimilation methods. Here, we will restrict our attention to particular linear systems, in which the instability can be explicitly analyzed. We investigate the three-dimensional variational assimilation and four-dimensional variational assimilation. A theory for the instability is developed using the classical theory of ill-posed problems in a Banach space framework. Further, we demonstrate by numerical examples that instabilities can and will occur, including an example from dynamic magnetic tomography.

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We present a novel but simple enteric coated sphere formulation containing probiotic bacteria (Lactobacillus casei). Oral delivery of live bacterial cells (LBC) requires live cells to survive firstly manufacturing processes and secondly GI microbicidal defenses including gastric acid. We incorporated live L. casei directly in the granulation liquid, followed by granulation, extrusion, spheronization, drying and spray coating to produce dried live probiotic spheres. A blend of MCC, calcium-crosslinked alginate, and lactose was developed that gave improved live cell survival during manufacturing, and gave excellent protection from gastric acid plus rapid release in intestinal conditions. No significant loss of viability was observed in all steps except drying, which resulted in approximately 1 log loss of viable cells. Eudragit coating was used to protect dried live cells from acid, and microcrystalline cellulose (MCC) was combined with sodium alginate to achieve efficient sphere disintegration leading to rapid and complete bacterial cell release in intestinal conditions. Viability and release of L. casei was evaluated in vitro in simulated GI conditions. Uncoated spheres gave partial acid protection, but enteric coated spheres effectively protected dried probiotic LBC from acid for 2 h, and subsequently released all viable cells within 1h of transfer into simulated intestinal fluid.

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This paper describes the novel use of cluster analysis in the field of industrial process control. The severe multivariable process problems encountered in manufacturing have often led to machine shutdowns, where the need for corrective actions arises in order to resume operation. Production faults which are caused by processes running in less efficient regions may be prevented or diagnosed using a reasoning based on cluster analysis. Indeed the intemal complexity of a production machinery may be depicted in clusters of multidimensional data points which characterise the manufacturing process. The application of a Mean-Tracking cluster algorithm (developed in Reading) to field data acquired from a high-speed machinery will be discussed. The objective of such an application is to illustrate how machine behaviour can be studied, in particular how regions of erroneous and stable running behaviour can be identified.

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The building industry is often berated for its short comings in meeting up with the demand for the provision of new housing. Addressing the need for new housing stock is a challenge that has led to debates among professional bodies, the construction sector, housing industry and government. The introduction of new manufacturing technologies is often offered as a solution, but the challenges of increasing the amount of off-site construction in residential building are well known and well-rehearsed. The modern flying factory (MFF) is a concept that involves the manufacture of specific components or modules in temporary off- or near- site locations using relatively simple and quick to set up and dismantle technologies and processes. The aim is to produce short batches and hence achieve some of the benefits of off-site manufacture on a much smaller scale than in dedicated factory environments. A case study of a modern flying factory being set up to produce pre-assembled utility cupboards for a large residential development in London is presented, involving participant observation and informal interviews with key actors on the design and operationalising of the process. The case reveals that although there are costs, efficiency and health and safety benefits to using MFF approaches, there are also challenges to overcome over the time required to set up and establish the process for relatively short runs, and in evaluating whether the MFF or traditional site based production is most effective for particular aspects of projects.