975 resultados para Industrial equipment


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The study was undertaken to generate socio-economic information on fish market systems and performance of the industrial processing industry, which will guide the processes leading to modernization of the fisheries sector and, sustainability of Lake Victoria fisheries. The main objective of this study was to evaluate the socio-economic implications of the fish marketing systems with particular emphasis on fish export market in Uganda. The study thus, analysed the socio-economic characteristics of fishers and examinined fish marketing systems and the impacts on the fishing activities, food security, employment opportunities and incomes of fisher-folk communities.

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Industrialists have few example processes they can benchmark against in order to choose a multi-agent development kit. In this paper we present a review of commercial and academic agent tools with the aim of selecting one for developing an intelligent, self-serving asset architecture. In doing so, we map and enhance relevant assessment criteria found in literature. After a preliminary review of 20 multiagent platforms, we examine in further detail those of JADE, JACK and Cougaar. Our findings indicate that Cougaar is well suited for our requirements, showing excellent support for criteria such as scalability, persistence, mobility and lightweightness. © 2010 IEEE.

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Growing environmental concerns caused by natural resource depletion and pollution need to be addressed. One approach to these problems is Sustainable Development, a key concept for our society to meet present as well as future needs worldwide. Manufacturing clearly has a major role to play in the move towards a more sustainable society. However it appears that basic principles of environmental sustainability are not systematically applied, with practice tending to focus on local improvements. The aim of the work presented in this paper is to adopt a more holistic view of the factory unit to enable opportunities for wider improvement. This research analyses environmental principles and industrial practice to develop a conceptual manufacturing ecosystem model as a foundation to improve environmental performance. The model developed focuses on material, energy and waste flows to better understand the interactions between manufacturing operations, supporting facilities and surrounding buildings. The research was conducted in three steps: (1) existing concepts and models for industrial sustainability were reviewed and environmental practices in manufacturing were collected and analysed; (2) gaps in knowledge and practice were identified; (3) the outcome is a manufacturing ecosystem model based on industrial ecology (IE). This conceptual model has novelty in detailing IE application at factory level and integrating all resource flows. The work is a base on which to build quantitative modelling tools to seek integrated solutions for lower resource input, higher resource productivity, fewer wastes and emissions, and lower operating cost within the boundary of a factory unit. © 2012 Elsevier Ltd. All rights reserved.

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Vision-based object detection has been introduced in construction for recognizing and locating construction entities in on-site camera views. It can provide spatial locations of a large number of entities, which is beneficial in large-scale, congested construction sites. However, even a few false detections prevent its practical applications. In resolving this issue, this paper presents a novel hybrid method for locating construction equipment that fuses the function of detection and tracking algorithms. This method detects construction equipment in the video view by taking advantage of entities' motion, shape, and color distribution. Background subtraction, Haar-like features, and eigen-images are used for motion, shape, and color information, respectively. A tracking algorithm steps in the process to make up for the false detections. False detections are identified by catching drastic changes in object size and appearance. The identified false detections are replaced with tracking results. Preliminary experiments show that the combination with tracking has the potential to enhance the detection performance.

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Achieving higher particles energies and beam powers have long been the main focus of research in accelerator technology. Since Accelerator Driven Subcritical Reactors (ADSRs) have become the subject of increasing interest, accelerator reliability and modes of operation have become important matters that require further research and development in order to accommodate the engineering and economic needs of ADSRs. This paper focuses on neutronic and thermo-mechanical analyses of accelerator-induced transients in an ADSR. Such transients fall into three main categories: beam interruptions (trips), pulsed-beam operation, and beam overpower. The concept of a multiple-target ADSR is shown to increase system reliability and to mitigate the negative effects of beam interruptions, such as thermal cyclic fatigue in the fuel cladding and the huge financial cost of total power loss. This work also demonstrates the effectiveness of the temperature-to-reactivity feedback mechanisms in ADSRs. A comparison of shutdown mechanisms using control rods and beam cut-off highlights the intrinsic safety features of ADSRs. It is evident that the presence of control rods is crucial in an industrial-scale ADSR. This paper also proposes a method to monitor core reactivity online using the repetitive pattern of beam current fluctuations in a pulsed-beam operation mode. Results were produced using PTS-ADS, a computer code developed specifically to study the dynamic neutronic and thermal responses to beam transients in subcritical reactor systems. © 2012 Elsevier B.V.

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The concept of sustainable manufacturing is a form of pollution prevention that integrates environmental considerations in the production of goods while focusing on efficient resource use. Taking the industrial ecology perspective, this efficiency comes from improved resource flow management. The assessment of material, energy and waste resource flows, therefore, offers a route to viewing and analysing a manufacturing system as an ecosystem using industrial ecology biological analogy and can, in turn, support the identification of improvement opportunities in the material, energy and waste flows. This application of industrial ecology at factory level is absent from the literature. This article provides a prototype methodology to apply the concepts of industrial ecology using material, energy and waste process flows to address this gap in the literature. Various modelling techniques were reviewed and candidates selected to test the prototype methodology in an industrial case. The application of the prototype methodology showed the possibility of using the material, energy and waste resource flows through the factory to link manufacturing operations and supporting facilities, and to identify potential improvements in resource use. The outcomes of the work provide a basis to build the specifications for a modelling tool that can support those analysing their manufacturing system to improve their environmental performance and move towards sustainable manufacturing. © IMechE 2012.

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This paper explores the evolving industrial control paradigm of product intelligence. The approach seeks to give a customer greater control over the processing of an order - by integrating technologies which allow for greater tracking of the order and methodologies which allow the customer [via the order] to dynamically influence the way the order is produced, stored or transported. The paper examines developments from four distinct perspectives: conceptual developments, theoretical issues, practical deployment and business opportunities. In each area, existing work is reviewed and open challenges for research are identified. The paper concludes by identifying four key obstacles to be overcome in order to successfully deploy product intelligence in an industrial application. © 2013 Elsevier Ltd. All rights reserved.