M.B.A / Please refer to full text to view abstract

This dissertation is based on the assumption that the Port Elizabeth Municipality should deliver essential services effectively, efficiently and economically so as to attain excellence in service delivery. The essential services dealt with in this study are electricity; refuse collection; sewerage; and water services. Attaining excellence in service delivery will lead the Port Elizabeth Municipality to improve and sustain the quality of life of the local inhabitants. The primary objectives of this dissertation include, inter alia: An historical analysis of delivery systems of the former government prior to 1994, which provides the primary reasons and purposes of delivery systems, and the effects on the Port Elizabeth Municipality. Reformation and transformation of South African local government since 1994, with particular reference to the Port Elizabeth Municipality. A normative model for service delivery, which is designed to accelerate service delivery in the local spheres of government, with special reference to the Port Elizabeth Municipality as the locus of this study. The nature, extent and evaluation of the existing service delivery by the Port Elizabeth Municipality from 1994 to 1999. An empirical survey is conducted in the form of questionnaires to the directors, heads of departments, senior managers, as well as councillors. Approaches and strategies for attaining excellence in service delivery, which include, inter alia: a government-business paradigm and an equilibrium approach. Lastly, a number of recommendations are made and conclusions are drawn based on the findings of the empirical survey in order to deliver essential services equitably, efficiently, effectively and economically to attain excellence in service delivery in the Port Elizabeth Municipality.

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M.Phil. / A project is successful if it is finished on time, to cost and to quality. Time and cost are relatively easy to understand and measure, however it is not easy to measure quality during the project life cycle. In spite of quality being stated as one of the major criteria of project success, appropriate attention to this is not always given in the context of projects. There are several possible definitions of good quality on a project. A project is said to be of good quality if the project's outcome has the following [17]: • Meets the specification • Is fit for purpose • Meets the customer's requirements • Satisfies the customer. Projects based organisations design and build complex items/systems such as aircraft or locomotives in relatively low volumes, or design and construct bridges, processing plants, that are unique, and once-off projects. Products such as aircraft have extended working lives, therefore after-sales support such as maintenance, servicing and upgrading are more important than for product-based organisations. A great proportion of management and engineering effort is therefore absorbed by such support functions. In projects more effort goes into design and production or construction engineering compared with product based organisations. According to Carruthers [3] "Very often projects that have been successfully completed within nominal scope, time and cost from the project manager's point of view turn out to be failures in the long term because of operational, product quality and/or marketing problems. The positive or negative influence of quality lasts long after 'cost successes' or 'schedule compliance' have been discounted or even forgotten." Examples of projects, which failed due to what the author regards as 'poor quality', will be discussed at the end ofthis dissertation (i.e. in chapter five).

M.Ing. / Many small emerging engineering companies, in especially South Africa, employ only a single engineer (this is mainly due to the shortages of qualified engineering staff). The engineers in many small engineering companies find themselves in the situation where they are responsible for many areas and fields, from design, management and in some cases finances too. This leaves very little time to plan projects with the detailed attention that each and every project requires no matter how small or large. It was the famous and true words of Harvey MacKay, “If you fail to plan, you plan to fail”, that if any project is undertaken without planning is going to fail on some level. It is undertaken, in this dissertation, to investigate the classical project management process and to ascertain the possibility of simplifying this process so that engineers in small engineering companies have an effective project management process that is economically feasible and will fit into already tight project time lines. A survey was conducted in order to get a good understanding of how project management is viewed in small engineering companies. The results of the survey support the theory that project management in small engineering companies is sadly lacking, and is viewed as an expense rather than a tool. Two case studies were performed; these highlight the value of project management. Initially poor project management leads to successful although late projects; with an improvement of the project breakdown structure and improved project management skills the second case study had some very surprising results. Finally the conclusion highlights that project management has very positive impacts on even the smallest of projects. Unfortunately there are no shortcuts when it comes to project management and what you put in is what you can expect to get out.

Chapter 1 gives a brief introduction to statistical quality control (SQC) and provides background information regarding the research conducted in this thesis. We begin Chapter 2 with the design of Shewhart-type Phase I S2, S and R control charts for the situation when the mean and the variance are both unknown and are estimated on the basis of m independent rational subgroups each of size n available from a normally distributed process. The derivations recognize that in Phase I (with unknown parameters) the signaling events are dependent and that more than one comparison is made against the same estimated limits simultaneously; this leads to working with the joint distribution of a set of dependent random variables. Using intensive computer simulations, tables are provided with the charting constants for each chart for a given false alarm probability. Second an overview of the literature on Phase I parametric control charts for univariate variables data is given assuming that the form of the underlying continuous distribution is known. The overview presents the current state of the art and what challenges still remain. It is pointed out that, because the Phase I signaling events are dependent and multiple signaling events are to be dealt with simultaneously (in making an in-control or not-in-control decision), the joint distribution of the charting statistics needs to be used and the recommendation is to control the probability of at least one false alarm while setting up the charts. In Chapter 3 we derive and evaluate expressions for the run-length distributions of the Phase II Shewhart-type p-chart and the Phase II Shewhart-type c-chart when the parameters are estimated. We then examine the effect of estimating and on the performance of the p-chart and the c-chart via their run-length distributions and associated characteristics such as the average run-length, the false alarm rate and the probability of a “no-signal”. An exact approach based on the binomial and the Poisson distributions is used to derive expressions for the Phase II run-length distributions and the related Phase II characteristics using expectation by conditioning (see e.g. Chakraborti, (2000)). We first obtain the characteristics of the run-length distributions conditioned on point estimates from Phase I and then find the unconditional characteristics by averaging over the distributions of the point estimators. The in-control and the out-of-control properties of the charts are looked at. The results are used to discuss the appropriateness of the widely followed empirical rules for choosing the size of the Phase I sample used to estimate the unknown parameters; this includes the number of reference samples m and the sample size n. Chapter 4 focuses on distribution-free control charts and considers a new class of nonparametric charts with runs-type signaling rules (i.e. runs of the charting statistics above and below the control limits) for both the scenarios where the percentile of interest of the distribution is known and unknown. In the former situation (or Case K) the charts are based on the sign test statistic and enhance the sign chart proposed by Amin et al. (1995); in the latter scenario (or Case U) the charts are based on the two-sample median test statistic and improve the precedence charts by Chakraborti et al. (2004). A Markov chain approach (see e.g. Fu and Lou, (2003)) is used to derive the run-length distributions, the average run-lengths, the standard deviation of the run-lengths etc. for our runs rule enhanced charts. In some cases, we also draw on the results of the geometric distribution of order k (see e.g. Chapter 2 of Balakrishnan and Koutras, (2002)) to obtain closed form and explicit expressions for the run-length distributions and/or their associated performance characteristics. Tables are provided for implementation of the charts and examples are given to illustrate the application and usefulness of the charts. The in-control and the out-of-control performance of the charts are studied and compared to the existing nonparametric charts using criteria such as the average run-length, the standard deviation of the run-length, the false alarm rate and some percentiles of the run-length, including the median run-length. It is shown that the proposed “runs rules enhanced” sign charts offer more practically desirable in-control average run-lengths and false alarm rates and perform better for some distributions. Chapter 5 wraps up this thesis with a summary of the research carried out and offers concluding remarks concerning unanswered questions and/or future research opportunities. / Thesis (PhD)--University of Pretoria, 2009. / Mathematics and Applied Mathematics / unrestricted

Aspen Pharmacare is listed on the Johannesburg Securities Exchange South Africa (JSE) and is Africa’s largest pharmaceutical manufacturer. The company is a major supplier of branded pharmaceutical and healthcare products to the local and selected international markets. For decades, Aspen has manufactured a basket of affordable, quality, and effective products for the ethical, generic over-the-counter (OTC) and personal care markets. Aspen is also the leading supplier of generic medicines to the public sector, providing comprehensive coverage of the products on the Essential Drug List. Aspen continues to deliver on its commitment toward playing a role in social responsibility diseases such as HIV/AIDS, tuberculosis and malaria. In August 2003 Aspen developed Africa’s first generic anti-retroviral drug, namely Aspen-Stavudine. Aspen’s manufacturing facilities are based in Port Elizabeth (PE) and East London. Aspen has recently completed an Oral Solid Dosage (OSD) manufacturing facility worth approximately R150 million in PE. The Group manufactures approximately 20 tons of product daily and in excess of 400 tons of solid dosage pharmaceuticals, which equates to more than 2 billion tablets. In addition, more than 3 million litres of liquid pharmaceuticals and over 200 tons of pharmaceutical creams and ointments are produced per year [1]. Aspen excels at delivering quality products and services, exceeding customer expectations, complying with international standards in an environment that cultivates technical expertise and innovation. Following this philosophy through to the shop floor areas mean that there are always initiatives in continuous production improvement. One of these improvement projects introduced is called Six Sigma. 8 Ten members of the staff, selected from different expertise fields in the company were trained in Six Sigma. Knowledge gained from the two week training course were applied to different areas in the factory using Six Sigma principles. This dissertation focuses on the study undertaken in one of production areas, namely the filling process of the ointments and creams at the Aspen Port Elizabeth facility.

To stay competitive and to be able to sell high-class products in the modern automobile production it is absolutely necessary to check the quality standard of a manufactured vehicle. The normal measurement strategy to check the quality standard of a completely assembled car is through a complex measurement strategy whilst the vehicle is in the actual series production. This is an immensely time and money consuming process. Furthermore, measurement systems are fixed within a certain position and the flexible measurement of a produced vehicle is very difficult to realize. This project presents a measurement system compliant to all quality guidelines, with which it is possible to measure any mounted component from a completely assembled vehicle wherever and whenever required. For the first time it is possible to measure the vehicle quality and dimensional standard from the first body in white prototype assembled in production up to the completely assembled vehicle delivered to the customer. The result of this project is a measurement system that consists of a hardware tool and a specially programmed software add-on. The complete system could easily be carried to the vehicle that must be analysed. This gives a lot of advantages. Furthermore it is possible to use this developed technology for the whole Volkswagen Company including the other brands like Audi, Skoda and Seat.

The components of a quality assurance program for smaller hospitals in British Columbia have been defined. These components have been defined by a comparison of the normative standards as determined in the literature and by a survey of administrators. Sixteen administrators of predominantly acute-care, accredited, 20-50-bed hospitals in B.C. were surveyed. Twelve of these administrators were surveyed twice. A new requirement for accreditation was introduced by the Canadian Council on Hospital Accreditation (C.C.H.A.) called the Quality Assurance Standard (1985). This Standard required that quality assurance (QA) programs be established in every department or service in the hospital. The Standard does not give a clear description of the QA functions for each individual department in a smaller hospital. An important and relevant list of specific functions for a QA program were identified at various C.C.H.A. seminars held across Canada in late 1983 and early 1984. The literature review indicated that there were a number of controversial issues affecting the implementation of the QA Standard. In spite of many methodological problems associated with quality measurement and assurance, most hospitals will adopt a quality assurance model. The first survey asked the administrators to define the purpose, goals and objectives of a QA program. They were also asked to determine the QA functions for four areas: hospital board, dietary, nursing and pharmacy. Administrators were asked to identify who in the hospital is primarily responsible for the overall QA program and for the QA program in four areas; the problems and benefits encountered when trying to implement a QA program; and their opinion of the new QA requirements for accreditation. The second survey asked the administrators to assign a priority to those functions identified in Round I. The empirical findings were then compared with the normative standards. With some exceptions, the empirical data were consistent with the normative standards. The empirical findings shows that there are problems related to implementing a QA program but at the same time there are a number of benefits related to the program. The priority ratings of the functions indicated areas of high or low importance to the administrator. It is likely that these priority ratings are useful for planning when alternatives must be considered during this time of fiscal restraint. Government policies along with the strong voluntary support of accreditation programs make it vitally important that suitable models for implementing QA are developed. The Doll model is suggested as a basis for implementing QA. Further areas for research are presented. / Medicine, Faculty of / Population and Public Health (SPPH), School of / Graduate

Digital Elevation Models have been in use for more than three decades and have become a major component of geographic information processing. The intensive use of DEMs has given rise to many accuracy investigations. The accuracy estimate is usually given in a form of a global measure such as root-mean-square error (RMSE), mostly from a producer's point of view. Seldom are the errors described in terms of their spatial distribution or how the resolution of the DEM interacts with the variability of terrain. There is a wide range of topographic variation present in different terrain surfaces. Thus, in defining the accuracy of a DEM, one needs ultimately to know the global and local characteristics of the terrain and how the resolution interacts with them. In this thesis, DEMs of various resolutions (i.e., 10 arc-minutes, 5 arc-minutes, 2 km, 1 km, and 50 m) in the study area (Prince George, British Columbia) were compared to each other and their mismatches were examined. Based on the preliminary test results, some observations were made regarding the relations among the spatial distribution of DEM errors, DEM resolution and the roughness of terrain. A hypothesis was proposed that knowledge of the landscape characteristics might provide some insights into the nature of the inherent error (or uncertainty) in a DEM. To test this statistically, the global characteristics of the study area surfaces were first examined by measures such as grain and those derived from spectral analysis, nested analysis of variance and fractal analysis of DEMs. Some important scale breaks were identified for each surface and this information on the surface global characteristics was then used to guide the selection of the moving window sizes for the extraction of the local roughness measures. The spatial variation and complexity of various study area surfaces was characterized by means of seven local geomorphometric parameters. The local measures were extracted from DEMs with different resolutions and using different moving window sizes. Then the multivariate cluster analysis was used for automated terrain classification in which relatively homogeneous terrain types at different scale levels were identified. Several different variable groups were used in the cluster analysis and the different classification results were compared to each other and interpreted in relation to each roughness measure. Finally, the correlations between the DEM errors and each of the local roughness measures were examined and the variation of DEM errors within various terrain clusters resulting from multivariate classifications were statistically evaluated. The effectiveness of using different moving window sizes for the extraction of the local measures and the appropriateness of different variable groups for terrain classification were also evaluated. The major conclusion of this study is that knowledge of topographic characteristics does provide some insights into the nature of the inherent error (or uncertainty) in a DEM and can be useful for DEM error modelling. The measures of topographic complexity are related to the observed patterns of discrepancy between DEMs of differing resolution, but there are variations from case to case. Several patterns can be identified in terms of relation between DEM errors and the roughness of terrain. First of all, the DEM errors (or elevation differences) do show certain consistent correlations with each of the various local roughness variables. With most variables, the general pattern is that the higher the roughness measure, the more points with higher absolute elevation differences (i.e., horn-shaped scatter of points indicating heteroscedasticity). Further statistical test results indicate that various DEM errors in the study area do show significant variation between different clusters resulting from terrain classifications based on different variable groups and window sizes. Cluster analysis was considered successful in grouping the areas according to their overall roughness and useful in DEM error modelling. In general, the rougher the cluster, the larger the DEM error (measured with either the standard deviation of the elevation differences or the mean of the absolute elevation differences in each cluster). However, there is still some of the total variation of various DEM errors that could not be accounted for by the cluster structure derived from multivariate classification. This could be attributed to the random errors inherent in any of the DEMs and the errors introduced in the interpolation process. Another conclusion is that the multivariate approach to the classification of topographic surfaces for DEM error modelling is not necessarily more successful than using only a single roughness measure in characterizing the overall roughness of terrain. When comparing the DEM error modelling results for surfaces with different global characteristics, the size of the moving window used in geomorphometric parameter abstraction also has certain impact on the modelling results. It shows that some understanding of the global characteristics of the surface is useful in the selection of appropriate/optimal window sizes for the extraction of local measures for DEM error modelling. Finally, directions for further research are suggested. / Arts, Faculty of / Geography, Department of / Graduate