In the area of indoor built environment modelling, the main focus was usually put on the accuracy of the modelled equipment within the given environment. There was not enough attention placed on the modelling of occupants inside the building, who represent the ultimate end?users and should be the most important element of an indoor built environment model. This deficiency was mainly due to the difficulties of modelling human behaviour with the traditional mathematical modelling methods usually adopted in the field. Therefore, in order to model the occupants more effectively, a more appropriate alternative approach is needed. This thesis examined the suitability of agent?based modelling and simulation (ABMS) for the indoor built environment. Philosophies of ABMS for the built environment were discussed, with the natural flow of progression stages in indoor built environment models outlined and explored, showing the need for switching a problem of simplicity to one in which a complex organised system was defined. Scenarios of single active agent case in ABMS for indoor built environment were used to demonstrate the effectiveness of this approach, with the finding that ABMS was versatile in modelling different types of occupants. It provided an illustration of the difference between people with different sensation time, and estimated energy savings between occupants with varied understanding of the environment. A classification scheme for different types of indoor built environment models with different levels of complexities was proposed and discussed. Based on the classification scheme, models with different levels of complexities were applied to the same building to explore the feasibility and practicality of the scheme. It was found that the simulation results provided insightful figures on probable energy consumption for different types of occupants and their crowd behaviour when interactions between occupants were considered. Findings included the amount of energy saved (around 10%) by a knowledgeable occupant over a less informed one, and the tendency for the majority (?66%) of occupants trying to save energy by assessing the environment themselves under different conditions. To further assist building management and the implementation of ABMS approach in built environment for simulations, the concepts of geographic information system (GIS) were modified for applications in the indoor environment, based on its similarity with ABMS for a grid?based environment. A prototype program was developed to test the applicability of the proposed concepts, with OPC connectivity for connections to real?world equipment. It was found that the idea of indoor GIS helps to solve problems such as the facility layout problem or the difficulties of information storage/retrieval in facility management, and this concept also integrated well with ABMS. With the successful modelling of different types of occupants and simulation results consistent with real data, it can be concluded from the work that ABMS is a promising approach for future generations of indoor built environment models. Also, with the inspiring framework of indoor GIS, the combination of ABMS and GIS in an integrated platform will certainly bring a powerful tool to the field. / published_or_final_version / Mechanical Engineering / Doctoral / Doctor of Philosophy

Environmental protection is a hot issue around in the world. Many governments and industries have put a lot of resources and efforts to take their responsibility of environmental protection in their daily operation and to establish correspondence environmental management system in their field. One of the international standards - ISO 14001 is a standard to assist to monitor and standardize the environmental management system in a company. Many studies have reported that implementation of ISO 14001 can provide different advantages to the company, such as improvement of image, improvement of environmental performance, improvement of efficiency of environmental policies, etc.. However, in the point of view of environmental protection, the most important is the actions of a person. Environmental protection should be done by everyone in the world, but not just in a company or an industry. If the implementation of ISO 14001 can affect a person to become more environmental friendly, it is worth to the environment. Nevertheless, there are few studies to investigate the effects and impacts of implementation of ISO 14001 to a person, especially in the property management industry. Therefore, in this paper, the impacts of implementation of ISO 14001 to the residents in the property management industry had been studies qualitatively. Three impacts, which are behaviors, awareness and knowledge of environmental protection, to the residents are investigated. The result found out that these are positively affected when ISO 14001 has been implemented in the properties. In conclusion, further research should be carried out to get an in-depth investigation as the sample size in this paper is limited and an absolute result cannot be got. However, the result is encouraging as implementation of ISO 14001 can positively affect the person living in the property and there are benefits to the environment due to their actions. / published_or_final_version / Housing Management / Master / Master of Housing Management

published_or_final_version / Housing Management / Master / Master of Housing Management

No description available.

Sustainable development is often described in three dimensions, namely social, environmental and economic. Environmental Management Accounting (EMA) is a management accounting approach which brings the environmental impact of the process to the attention of the stakeholders whilst also looking at the economic aspect so as to control costs. While EMA’s application has been adopted widely in developed countries, does the same apply in South Africa? Seeking to understand the level of current EMA being conducted at the corporate level will assist government and corporations in South Africa to understand the factors encouraging better accounting sustainability. The focus of this study was confined to leaders of organisations operating in the KwaZulu-Natal (KZN) province of South Africa. Quantitative research was conducted on 40 organisations that operated in KZN. The organisations sampled ranged from small to large enterprises, and operated in a number of different industries. The study centred on analysing the organisation’s attitude towards environmental sustainability, the types of EMA reports generated and reasons for or against using EMA. The research revealed that the attitude by each organisation towards environmental sustainability was vital in encouraging organisations to implement EMA as a method of controlling pollution. The majority of organisations had applied some form of EMA in their KZN organisation. A major finding was that for those who chose to apply EMA, their most important reason was to control costs better. The second reason for applying EMA was legislation. Planned implementation of EMA was analysed and a number of specific industries and sizes of industries were highlighted for their implementation of EMA or lack thereof. This research is useful to the reader as it has analysed the current application of EMA to encourage sustainable development, identify the general obstacles encountered to application of EMA and recommend strategies that can be employed to overcome them. These recommendations include government involvement through education programmes to improve the understanding and attitude towards EMA. Secondly, government should pass legislation making environmental reporting a compulsory disclosure for all organisations. Organisations themselves should use advanced computerised recording systems to develop their application of EMA. Larger businesses should encourage and assist smaller organisations in their supply chains to become more active in their own environmental protection. / Thesis (MBA)-University of KwaZulu-Natal, Westville, 2011.

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.

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.

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.

Thesis PlanB (M.S.)--University of Wisconsin--Stout, 2007. / Includes bibliographical references.

Thesis (Ph.D.)--McMaster University, 2002. / Advisor: Susan Elliott. Includes bibliographical references. Also available on World Wide Web.