101 resultados para Industrial standards


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The objective of this paper is to test various available turbulent burning velocity models on an experimental version of Siemens small scale combustor using the commercial CFD code. Failure of burning velocity model with different expressions for turbulent burning velocity is observed with an unphysical flame flashback into the swirler. Eddy Dissipation Model/Finite Rate Chemistry is found to over-predict mean temperature and species concentrations. Solving for reaction progress equation with its variance using scalar dissipation rate modelling produced reasonably good agreement with the available experimental data. Two different turbulence models Shear Stress Transport (SST) and Scale Adaptive Simulation (SAS) SST are tested and results from transient SST simulations are observed to be predicting well. SAS-SST is found to under-predict with temperature and species distribution.

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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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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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As operational impacts from buildings are reduced, embodied impacts are increasing. However, the latter are seldom calculated in the UK; when they are, they tend to be calculated after the building has been constructed, or are underestimated by considering only the initial materials stage. In 2010, the UK Government recommended that a standard methodology for calculating embodied impacts of buildings be developed for early stage design decisions. This was followed in 2011-12 by the publication of the European TC350 standards defining the 'cradle to grave' impact of buildings and products through a process Life Cycle Analysis. This paper describes a new whole life embodied carbon and energy of buildings (ECEB) tool, designed as a usable empirical-based approach for early stage design decisions for UK buildings. The tool complies where possible with the TC350 standards. Initial results for a simple masonry construction dwelling are given in terms of the percentage contribution of each life cycle stage. The main difficulty in obtaining these results is found to be the lack of data, and the paper suggests that the construction and manufacturing industries now have a responsibility to develop new data in order to support this task. © 2013 The Authors. Published by Elsevier B.V. All rights reserved.

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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.