A housing affordability and tenure of choice quantum deliverable model in South Africa
- Authors: Kabundu, Emmanuel Kizito
- Date: 2020
- Subjects: Housing -- Prices -- South Africa Housing -- Economic aspects -- South Africa
- Language: English
- Type: Thesis , Doctoral , PhD
- Identifier: http://hdl.handle.net/10948/49606 , vital:41740
- Description: The aim of this research was to develop a model that practically determines the tenure of choice and affordability of households in South Africa, which will thus help towards informed decision making by analysts and housing officials. Presently, there is no clear systematic means (except for simplistic ratios) of determining the degree of the effect of changes in the housing market (such as implemented policies) on the tenure of choice and affordability decisions of households. The research set out to improve upon the usage of ratios by basing its analysis on the theoretical underpinnings of both user costs of occupancy and an assumption of endogeneity between tenure of choice and affordability. The research used the general household survey data from Statistics South Africa for the analysis and validation. Generalized joint binary regression (on assumption of endogeneity between tenure of choice and affordability) was used as a check against the user costs of occupancy modelling. An independent market analysis carried out showed that South Africa has consistently faced increasing problems of acute housing shortages and housing affordability. Never the less, apart from subsidy programs, the option to promote renting, coupled with use of innovative building technologies showed promise of significantly alleviating these problems. More living space is especially more vital than ever, amid the current crisis of COVID-19 pademic. Statistical tests indicated strong evidence suggesting that the developed user costs of occupancy model (dynamic tenure model) is reliable at correctly recovering the tenure statuses of the households, with its recovery rates being better than those of the regression model. Both models provided useful unique, but different insights into the housing market and also correctly predicted the behavioural patterns of South African housing markets, such as significantly worsening affordability, and a market that is biased towards home ownership. The analysis also showed that affordability and tenure of choice were significantly affected by locational factors, household characteristics (such as race and age of household head), and most significantly, the age of the household head (which is a proxy to household income). The research successfully met its goal of model building but also recognized the need to merge these two models (dynamic tenure model and the regression model) into one model for more comprehensive housing related analysis. The research also recognized a need to fully operationalize the optimization, Monte Carlo and parallelization modules in order to improve the practical usefulness and effectiveness of the model. The significance of the study is that it it underpins the basis for proper tenure and affordability analysis, by assuming endogeneity between the two (2), and provides a modelling framework based on these criteria, that are useful for meaningful housing market analysis.
- Full Text:
- Date Issued: 2020
- Authors: Kabundu, Emmanuel Kizito
- Date: 2020
- Subjects: Housing -- Prices -- South Africa Housing -- Economic aspects -- South Africa
- Language: English
- Type: Thesis , Doctoral , PhD
- Identifier: http://hdl.handle.net/10948/49606 , vital:41740
- Description: The aim of this research was to develop a model that practically determines the tenure of choice and affordability of households in South Africa, which will thus help towards informed decision making by analysts and housing officials. Presently, there is no clear systematic means (except for simplistic ratios) of determining the degree of the effect of changes in the housing market (such as implemented policies) on the tenure of choice and affordability decisions of households. The research set out to improve upon the usage of ratios by basing its analysis on the theoretical underpinnings of both user costs of occupancy and an assumption of endogeneity between tenure of choice and affordability. The research used the general household survey data from Statistics South Africa for the analysis and validation. Generalized joint binary regression (on assumption of endogeneity between tenure of choice and affordability) was used as a check against the user costs of occupancy modelling. An independent market analysis carried out showed that South Africa has consistently faced increasing problems of acute housing shortages and housing affordability. Never the less, apart from subsidy programs, the option to promote renting, coupled with use of innovative building technologies showed promise of significantly alleviating these problems. More living space is especially more vital than ever, amid the current crisis of COVID-19 pademic. Statistical tests indicated strong evidence suggesting that the developed user costs of occupancy model (dynamic tenure model) is reliable at correctly recovering the tenure statuses of the households, with its recovery rates being better than those of the regression model. Both models provided useful unique, but different insights into the housing market and also correctly predicted the behavioural patterns of South African housing markets, such as significantly worsening affordability, and a market that is biased towards home ownership. The analysis also showed that affordability and tenure of choice were significantly affected by locational factors, household characteristics (such as race and age of household head), and most significantly, the age of the household head (which is a proxy to household income). The research successfully met its goal of model building but also recognized the need to merge these two models (dynamic tenure model and the regression model) into one model for more comprehensive housing related analysis. The research also recognized a need to fully operationalize the optimization, Monte Carlo and parallelization modules in order to improve the practical usefulness and effectiveness of the model. The significance of the study is that it it underpins the basis for proper tenure and affordability analysis, by assuming endogeneity between the two (2), and provides a modelling framework based on these criteria, that are useful for meaningful housing market analysis.
- Full Text:
- Date Issued: 2020
Ultra-high precision diamond turning of advanced contact lens polymers
- Authors: Liman, Muhammad Mukhtar
- Date: 2020
- Subjects: Contact lenses , Electrostatic lenses Lenses -- Design and construction
- Language: English
- Type: Thesis , Doctoral , PhD
- Identifier: http://hdl.handle.net/10948/46108 , vital:39496
- Description: Contact lens polymer-based materials are extensively used in the optical industry owing to their excellent corrosion resistance, the possibility of mass production and their ability to be processed without external lubrication. Owing to the fast growth in optical industries, contact lens (CL) requires high accuracy and a high surface quality. The demand for high-accuracy and minimal surface roughness drives the development of ultra-high precision machining technology with regard to single point diamond turning (SPDT). Ultra-high precision diamond turning is an advanced manufacturing technique employed in the machining of CLs owing to its capability of producing high optical surfaces with complex shapes and nanometric accuracy. Yet, even with the advances in ultra-high precision machining (UHPM), it is not continuously easy to achieve a highquality surface finish during polymers machining as the adhesion of the tool chip around the tool dictates the presence of electrostatic charges. The electrostatic charges encountered by a cutting tool when turning advanced CLs are important as they reflect the quality and condition of the tool, machine, fixture, and sometimes even the finished surface, which is responsible for tool wear and poor surface quality. This study investigates the role of cutting parameters, namely cutting speed, feed rate and depth of cut on surface roughness (Ra), electrostatic charge (ESC) and material removal rate (MRR), which determines machine economics and the quality of machining contact lens polymers. The experiments were mainly conducted on two different advanced polymeric materials: polymethyl methacrylate (PMMA) and Optimum Extreme (Roflufocon E) CLs. Experimentation was carried out on the Nanoform 250 ultra-grind turning machine with a monocrystalline diamond-cutting tool for machining the PMMA and Roflufocon E CL polymers, covering a wide range of machining parameters. Before conducting the experiments, a design of experiment was conducted according to the response surface methodology (RSM) that is based on the Box-Behnken Design (BBD). In addition, the research study focused on the determination of the optimum cutting conditions leading to minimum Ra and ESC as well as maximum productivity in the SPDT of the PMMA and Roflufocon E CL polymers, using a monocrystalline diamondcutting tool. The optimization was based on RSM together with the desirability function approach. In addition, a mathematical model was developed for Ra, ESC and MRR using a RSM regression analysis for PMMA and Roflufocon E CL polymers by means of Design Expert software. RSM allowed for the optimization of the cutting conditions for minimal Ra and ESC as well as maximal MRR, which provides an effective knowledge base for process parameters to enhance process performance in the SPDT of CL polymers. Furthermore, this study also deals with the development of Ra, ESC and MRR prediction models for the diamond turning of PMMA and Roflufocon E CL polymers, using the fuzzy logic based artificial intelligence (AI) method. The fuzzy logic model has been developed in terms of machining parameters for the prediction of Ra, ESC and MRR. To judge the accuracy and ability of the fuzzy logic model, an average percentage error was used. The comparative evaluation of experiments and the fuzzy logic approach suggested that the obtained average errors of Ra, ESC and MRR using the fuzzy logic system were in agreement with the experimental results. Hence, the developed fuzzy logic rules can be effectively utilized to predict the ESC, Ra and MRR of PMMA and Roflufocon E CL polymers in automated optical manufacturing environments for high accuracy and a reduction of computational cost. Moreover, owing to the brittle nature of optical polymers, the Roflufocon E CL polymer requires ductile-mode machining for improved surface quality. Molecular Dynamics (MD) simulation methods are thus applied to investigate the atomistic reaction at the tool/workpiece surface to clearly study and observe conditions occurring at nanometric scale in polymer machining. This research study is particularly concerned with the comparative analysis of experiments and a MD study of the Roflufocon E optical polymer nano cutting approach to the atomistic visualization of the plastic material flow at the tool/workpiece interface during cutting. The simulated MD acting force, machine stresses, and the temperature at the cutting region were evaluated to access the accuracy of the model. Hence, the nanomachining simulations were found to have a correlation to the experimental machining results.
- Full Text:
- Date Issued: 2020
- Authors: Liman, Muhammad Mukhtar
- Date: 2020
- Subjects: Contact lenses , Electrostatic lenses Lenses -- Design and construction
- Language: English
- Type: Thesis , Doctoral , PhD
- Identifier: http://hdl.handle.net/10948/46108 , vital:39496
- Description: Contact lens polymer-based materials are extensively used in the optical industry owing to their excellent corrosion resistance, the possibility of mass production and their ability to be processed without external lubrication. Owing to the fast growth in optical industries, contact lens (CL) requires high accuracy and a high surface quality. The demand for high-accuracy and minimal surface roughness drives the development of ultra-high precision machining technology with regard to single point diamond turning (SPDT). Ultra-high precision diamond turning is an advanced manufacturing technique employed in the machining of CLs owing to its capability of producing high optical surfaces with complex shapes and nanometric accuracy. Yet, even with the advances in ultra-high precision machining (UHPM), it is not continuously easy to achieve a highquality surface finish during polymers machining as the adhesion of the tool chip around the tool dictates the presence of electrostatic charges. The electrostatic charges encountered by a cutting tool when turning advanced CLs are important as they reflect the quality and condition of the tool, machine, fixture, and sometimes even the finished surface, which is responsible for tool wear and poor surface quality. This study investigates the role of cutting parameters, namely cutting speed, feed rate and depth of cut on surface roughness (Ra), electrostatic charge (ESC) and material removal rate (MRR), which determines machine economics and the quality of machining contact lens polymers. The experiments were mainly conducted on two different advanced polymeric materials: polymethyl methacrylate (PMMA) and Optimum Extreme (Roflufocon E) CLs. Experimentation was carried out on the Nanoform 250 ultra-grind turning machine with a monocrystalline diamond-cutting tool for machining the PMMA and Roflufocon E CL polymers, covering a wide range of machining parameters. Before conducting the experiments, a design of experiment was conducted according to the response surface methodology (RSM) that is based on the Box-Behnken Design (BBD). In addition, the research study focused on the determination of the optimum cutting conditions leading to minimum Ra and ESC as well as maximum productivity in the SPDT of the PMMA and Roflufocon E CL polymers, using a monocrystalline diamondcutting tool. The optimization was based on RSM together with the desirability function approach. In addition, a mathematical model was developed for Ra, ESC and MRR using a RSM regression analysis for PMMA and Roflufocon E CL polymers by means of Design Expert software. RSM allowed for the optimization of the cutting conditions for minimal Ra and ESC as well as maximal MRR, which provides an effective knowledge base for process parameters to enhance process performance in the SPDT of CL polymers. Furthermore, this study also deals with the development of Ra, ESC and MRR prediction models for the diamond turning of PMMA and Roflufocon E CL polymers, using the fuzzy logic based artificial intelligence (AI) method. The fuzzy logic model has been developed in terms of machining parameters for the prediction of Ra, ESC and MRR. To judge the accuracy and ability of the fuzzy logic model, an average percentage error was used. The comparative evaluation of experiments and the fuzzy logic approach suggested that the obtained average errors of Ra, ESC and MRR using the fuzzy logic system were in agreement with the experimental results. Hence, the developed fuzzy logic rules can be effectively utilized to predict the ESC, Ra and MRR of PMMA and Roflufocon E CL polymers in automated optical manufacturing environments for high accuracy and a reduction of computational cost. Moreover, owing to the brittle nature of optical polymers, the Roflufocon E CL polymer requires ductile-mode machining for improved surface quality. Molecular Dynamics (MD) simulation methods are thus applied to investigate the atomistic reaction at the tool/workpiece surface to clearly study and observe conditions occurring at nanometric scale in polymer machining. This research study is particularly concerned with the comparative analysis of experiments and a MD study of the Roflufocon E optical polymer nano cutting approach to the atomistic visualization of the plastic material flow at the tool/workpiece interface during cutting. The simulated MD acting force, machine stresses, and the temperature at the cutting region were evaluated to access the accuracy of the model. Hence, the nanomachining simulations were found to have a correlation to the experimental machining results.
- Full Text:
- Date Issued: 2020
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