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Lifetime monitoring of appliances for reuseMazhar, Muhammad Ilyas, Mechanical & Manufacturing Engineering, Faculty of Engineering, UNSW January 2006 (has links)
Environmental awareness and legislative pressures have made manufacturers responsible for the take-back and end-of-life treatment of their products. Therefore, manufacturers are struggling to find ways to recover maximum value from returned products. This goal can best be achieved by promoting multiple reuse programs as reuse is one of the most effective ways to enhance a sustainable engineering economy. Since the essential goal of the reuse strategy is to reuse parts, the reliability of used parts becomes a core issue. Research indicates that reuse is technologically feasible, associated with a significant manufacturing cost saving, and it does not compromise product quality. However, it is not easy to be applied in reality. There are several uncertainties associated with reuse, the most common is the uncertainty of the product???s quality after use. A widespread implementation of the reuse strategy could be triggered, subject to the availability of reliable methods to assess the useful remaining life of parts. The evolution of such a methodology would play a pivotal role in making decisions on the supply chain process and the recovery value of returned products. Reliability assessment by life cycle data analysis is the basis of this research. The proposed methodology addresses the problem of reliability assessment of used parts by considering two important aspects. It performs statistical as well as condition monitoring data analysis for decision-making on reuse. The analysis is carried out in two stages. Firstly, a wellknown reliability assessment procedure, the Weibull analysis, is applied to analyse time-tofailure data to assess the overall reuse potential of components. In the second stage, the used capacity (actual life) of components is determined by analysing their operating history (condition monitoring data). The linear and nonlinear regression analysis, Kriging procedures and artificial neural networks (ANN) are employed in this stage. Finally, the Weibull analysis and ANNs are integrated to estimate the remaining useful life of components/assemblies of a product at the end of its first life cycle. The model was validated by using life cycle data from consumer products.
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Zero emission managementLam, Lai Fong Janna. January 2001 (has links) (PDF)
Author's name appears as Lam Lai Fong Janna on front cover. Bibliography: leaves 117-120.
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Commercial and retail waste recycling in the Adelaide Central Business DistrictChung, Shan Shan. January 1991 (has links) (PDF)
Bibliography: leaves 70-71.
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System dynamics study and assessment on municipal solid waste management for MacaoChoi, Fei January 2012 (has links)
University of Macau / Faculty of Science and Technology / Department of Civil and Environmental Engineering
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115 |
A computer model for in-flight black liquor combustion in a kraft recovery furnaceWalsh, Allan R. 01 1900 (has links)
No description available.
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116 |
Strategic Network Growth with Recruitment ModelWongthatsanekorn, Wuthichai 10 April 2006 (has links)
In order to achieve stable and sustainable systems for recycling post-consumer goods, it is frequently necessary to concentrate the flows from many collection points to meet the volume requirements for the recycler. This motivates the importance of growing the collection network over time to both meet volume targets and keep costs to a minimum. This research addresses a complex and interconnected set of strategic and tactical decisions that guide the growth of reverse supply chain networks over time. This dissertation has two major components: a tactical recruitment model and a strategic investment model. These capture the two major decision levels for the system, the former for the regional collector who is responsible for recruiting material sources to the network, the latter for the processor who needs to allocate his scarce resources over time and to regions to enable the recruitment to be effective. The recruitment model is posed as a stochastic dynamic programming problem. An exact method and two heuristics are developed to solve this problem. A numerical study of the solution approaches is also performed. The second component involves a key set of decisions on how to allocate resources effectively to grow the network to meet long term collection targets and collection cost constraints. The recruitment problem appears as a sub-problem for the strategic model and this leads to a multi-time scale Markov decision problem. A heuristic approach which decomposes the strategic problem is proposed to solve realistically sized problems. The numerical valuations of the heuristic approach for small and realistically sized problems are then investigated.
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117 |
The role of property manager in improving the recycling rate in Hong Kong: incentives for residents to changetheir waste practicesChan, Chin-yee., 陳展誼. January 2008 (has links)
published_or_final_version / Housing Management / Master / Master of Housing Management
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118 |
Food [w]ork: multi-scale food waste treatement networkChau, Sau-man., 周秀雯. January 2013 (has links)
published_or_final_version / Architecture / Master / Master of Landscape Architecture
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119 |
A study of the recycling of domestic solid waste in Hong Kong雷學良, Lui, Hok-leung, Michael. January 2003 (has links)
published_or_final_version / Public Administration / Master / Master of Public Administration
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120 |
Recycling municipal solid waste: problems andprospect陳麗瑩, Chan, Lai-ying. January 2001 (has links)
published_or_final_version / Geography and Geology / Master / Master of Philosophy
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