A productivity monitoring system is developed to incorporate productivity measurement at various organizational levels within manufacturing plants into the general information system. Classical productivity measures, defined as ratios of inputs and outputs of production, are used in the developed system. In addition to measuring the total and partial productivity, the system compiles the total factor productivity which is often applied in manufacturing to represent operational efficiency. In the developed system, reporting of productivity information is based on the organizational structure such that productivity measures are provided only when the corresponding organizational (work) units exist. Thus, the productivity monitoring system provides not only the responsibility-based productivity information, but is flexible in the aggregation of productivity performances of organizational units. The system is executed on the MARK IV File Management System (Informatics Inc.), and a real-world case is studied. Since the data required in the productivity monitoring system are commonly available and shared by other manufacturing subsystems, the system can be implemented as a subsystem of the general information system. / Ph. D.

by Lam Ka-chi, Ricky and Wong Suet-yee, Sheri. / Thesis (M.B.A.)--Chinese University of Hong Kong, 1994. / Includes bibliographical references (leaves 138-140). / ABSTRACT --- p.iii / TABLE OF CONTENTS --- p.iv / LIST OF FIGURES --- p.vii / LIST OF TABLES --- p.x / PREFACE --- p.xi / ACKNOWLEDGMENTS --- p.xii / Chapter / Chapter I. --- INTRODUCTION --- p.1 / Global Trend Towards Quality Improvement --- p.2 / Quality Improvement in Hong Kong --- p.5 / Chapter II. --- OBJECTIVES OF THE RESEARCH --- p.11 / General Objective --- p.11 / Ultimate Objective --- p.11 / Minor Objectives --- p.11 / Chapter III. --- METHODOLOGY --- p.13 / Primary Research - Questionnaire --- p.13 / Design of the Questionnaire --- p.13 / Content of the Questionnaire --- p.15 / Respondents of the Questionnaire --- p.16 / Primary Research - Interview --- p.18 / Secondary Research - Library Research --- p.19 / Chapter IV. --- LITERATURE REVIEW --- p.20 / Quality --- p.20 / Quality Productivity --- p.22 / Quality and Cost --- p.22 / Productivity and Cost --- p.24 / "Quality, Productivity and Cost" --- p.25 / Customers Satisfaction --- p.25 / Profitability --- p.25 / Quality: A Long-term Strategic Planning --- p.28 / Summing Up --- p.30 / Chapter V. --- DEFINITION --- p.33 / Some Operational Terms --- p.33 / Quality --- p.33 / Productivity --- p.33 / Company Performance --- p.34 / Quality Performance --- p.35 / Financial Performance --- p.35 / Gurus in Quality Management --- p.35 / Edward Deming --- p.35 / Joseph Juran --- p.39 / Philip Crosby --- p.42 / Armand V. Feigenbaum --- p.46 / Kaoru Ishikawa --- p.47 / Genichi Taguchi --- p.48 / Quality Improvement Techniques --- p.49 / Zero Defects --- p.49 / Quality Control Circle --- p.49 / Statistical Process Control (SPC) --- p.49 / Quality Control 7 Tools --- p.51 / Taguchi Method --- p.51 / Fool-proof (Poke Yoke) --- p.53 / Quality Function Deployment --- p.54 / International Standard Organization --- p.54 / Productivity Improvement Techniques --- p.56 / Work measurement --- p.56 / Layouts --- p.56 / Computer-integrated Manufacturing (CIM) --- p.56 / Material Requirements Planning (MRP) --- p.57 / Manufacturing Resources Planning (MRPII) --- p.57 / Just in Time (JIT) --- p.57 / Competitive Benchmarking --- p.58 / Self-directed Work Teams --- p.58 / Theory of Constraints --- p.58 / Chapter VI. --- HIGHLIGHT OF FINDINGS --- p.60 / Company Demographics --- p.60 / Company Size --- p.60 / Employees Turnover Rate --- p.60 / Company Sales Last Year --- p.61 / Number of Years Established --- p.61 / Overseas Branch or Subsidiary --- p.63 / Other Company Information --- p.65 / Company Performance --- p.69 / Customers Perception:Company Performance --- p.69 / Quality Performance --- p.73 / Financial Performance --- p.75 / Quality Improvement Techniques --- p.76 / Formal Approach to Quality Improvement --- p.76 / Separate Quality Department --- p.76 / Application of Quality Improvement Techniques --- p.81 / Quality Improvement -ISO 9000 --- p.92 / Quality Improvement - Understand & Specify Customer Requirements --- p.99 / Productivity Improvement Techniques --- p.105 / Formal Approach to Productivity Improvement --- p.105 / Productivity Improvement Techniques --- p.105 / Chapter VII. --- ANALYSIS AND DISCUSSION --- p.117 / Factor Analysis --- p.117 / Kaiser-Meyer-olkin Measure --- p.117 / Steps of Factor Analysis --- p.118 / VARIMAX Rotation --- p.118 / Interpretation of Factors --- p.118 / Factor 1 --- p.118 / Factor 2 --- p.121 / Factor 3 --- p.121 / Factor 4 --- p.122 / Factor 5 --- p.122 / Factor 6 --- p.123 / Regression --- p.123 / Total Quality Cost --- p.123 / Items Defective and Rework Cost --- p.126 / Returns and Warranty Cost --- p.126 / Internal Waste and Training Costs --- p.126 / Quality Performance --- p.127 / Financial Performance --- p.127 / Employee Turnover Rate --- p.127 / Employees' Satisfaction --- p.128 / Chapter VIII. --- CONCLUSION --- p.129 / APPENDIX --- p.131 / BIBLIOGRAPHY --- p.138

Kwan Wing Kai. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1996. / Includes bibliographical references (leaves 85-93). / Abstract / Acknowledgment / Chapter Chapter 1. --- Introduction --- p.1 / Chapter 1.1 --- A Review of Recent Studies on the Productivity of Chines Economy --- p.3 / Chapter 1.2 --- Aims of Study --- p.10 / Chapter Chapter 2. --- The Sources of Productivity Growth --- p.16 / Chapter 2.1 --- Degree of Government Intervention --- p.16 / Chapter 2.2 --- Ownership Structure --- p.18 / Chapter 2.3 --- Output Structure --- p.24 / Chapter 2.4 --- Changes in Regional Development Strategy --- p.25 / Chapter 2.4.1 --- Regional Development Strategy before1979 --- p.27 / Chapter 2.4.2 --- Regional Development Strategy since1979 --- p.29 / Chapter 2.4.3 --- The Impacts of Different Regional Strategies on Productivity Change --- p.31 / Chapter Chapter 3. --- Theoretical Framework and Estimation Methods --- p.33 / Chapter 3.1 --- Methed I: The Conventional Approach --- p.35 / Chapter 3.2 --- Method II: Replacing the Variable of the Growth of Capital Stock by Investment-Output Ratio --- p.40 / Chapter 3.3 --- Method III: Approximation of the Production Function by Taylor Expansion --- p.45 / Chapter Chapter 4. --- Empirical Results of the Three Different Methods --- p.51 / Chapter 4.1 --- Estimation Results of the Three Different Methods --- p.51 / Chapter 4.2 --- Comparison of the Estimation Results of the Three Methods --- p.63 / Chapter 4.3 --- An Assessment of Provincial Productivity Growth --- p.66 / Chapter 4.4 --- Regional Productivity Difference since1979 --- p.75 / Chapter Chapter 5. --- Conclusion --- p.82 / References --- p.85 / Appendix 1. List of the Abbreviations for Provinces --- p.94 / Appendix 2. A Summary of Notations --- p.95 / Appendix 3. Estimates of Provincial Capital Stock (1979-1992) --- p.97 / Chapter A3.1 --- Initial value of Capital Stock --- p.98 / Chapter A3.2 --- Net Increase of Capital Stock --- p.101 / Chapter A3.3 --- Estimating the Annual Series of Capital Stock --- p.102 / Appendix 4. The Process of Fiscal Decentralization and Deterioration of Regional Redistribution --- p.106 / Chapter A4.1 --- The Process of Fiscal Decentralization --- p.106 / Chapter A4.2 --- The deterioration of Regional Redistribution --- p.110 / Appendix 5. Estimation Results of the Three Different Methods --- p.114

Thesis (Ph. D.)--University of Hong Kong, 1999. / Includes bibliographical references (leaves 101-112).

Thesis (Ph. D.)--University of California, Berkeley, 1991. / Includes bibliographical references (leaves 155-163).

Thesis (Ph.D.) - University of Queensland, 2004. / Includes bibliography.

Thesis (M.S.)--Virginia Polytechnic Institute and State University, 1994. / Vita. Abstract. Includes bibliographical references (leaves 171-176). Also available via the Internet.

M.Ing. / The aim of this research is to develop a Project Management Maturity Measurement Model to evaluate project management efficiency in a large Parastatal such as Eskom Distribution. This model will identify areas of improvement to assist a large Parastatal in improving their project management performance. It will eventually assist the organisation to build a culture of project management excellence. The hypotheses for the study were that firstly, the Parastatal does implement project management practice processes as advocated by project management bodies of knowledge. Secondly, a Project Management Maturity Measurement Model can be successfully implemented at a large Parastatal and help the Parastatal to identify project management grey areas that require improvement. Thirdly, a Project Management Maturity Measurement Model could assist a large Parastatal with project management improvement as a result of areas of recommendations. The method used to collect the required data for analysis and interpretation was the descriptive survey method. A customised survey questionnaire was developed to obtain data from research sample. Data was analysed using appropriate statistical techniques. The research sample was defined as the people who are primarily responsible for project, programme and portfolio management at a large Parastatal. The results of the data analysed pin pointed project management process weaknesses and possible improvement opportunities. Three main areas of improvement have been identified, namely applying lessons learned from previous project into future project, performing benchmarking to improve performance and project control processes. The findings of this study support the abovementioned hypotheses, and the insights provided and recommendations made will be of great help to a large Parastatal on its road to continuous improvement and building a culture of project management excellence.

M.Ing. / The purpose of this research investigation is to develop and simulate a current manufacturing production line, for a company by the name of Aerosud, using a 3- dimensional software tool called Delmia Quest ®. The company in question is a mechanical and aeronautical manufacturing organisation that supplies components to both the civil and military sectors to a variety of global points. The aim of this investigation was to develop a simulation model that, initially, mapped the actual workings of the real production line with the use of actual time data recorded through measurement. Secondly, various observations were made to discover how much work-in-progress (WIP) remains idle during the manufacturing procedure and how much productivity is reached after a standard production week of forty-five hours. Hence, the aim of the simulation model is to improve those two factors by increasing the productivity of the entire production line and reduce the amount of WIP idle to a minimum. To achieve this, the author created a baseline model for both the throughput time and the WIP at each cell of production. The results of these curves were obtained using actual statistical time data obtained during the observation period. These results were then plotted onto individual axis to visually identify the outputs. Next, the author analysed the baseline model, within the 3D virtual world of the software, to witness where possible errors exist in terms of throughput time and the amount of WIP idle at various stations of production. It was clearly identified that the cell with the most production problems, was assembly. The author thus identified possible methods of reducing these problems and simulated those actions. The results showed various improvements in the amount of throughput time gained as well as a significant reduction to the amount of WIP idle at that particular cell. The simulations were thus mapped onto the same axis as the baseline model, in terms of throughput time and WIP respectively. This provides visual identification to the outcome of such simulations so that the reader can identify clarity in the results. A basic comparison of each simulation was described with reference to the baseline curve in order to clarify what the results had shown. Finally, the investigation was concluded highlighting that the baseline model created was a good start to analysing the company’s production line; however, as further research, it was recommended that various types of improvements can still be made to this model in order to improve its realism when compared to the real production line.

M.Com. (Business Science) / Please refer to full text to view abstract