Globalisation has opened up international markets for South African companies, but has also introduced competition in the domestic market. As a result, South African organisations are forced to attain global efficiency levels if they are to compete on the world market as well as maintain their domestic market share. Organisations have to come with creative methods that can enhance their competitiveness, one of them being the Six Sigma. Six Sigma is a measurement-based strategy that focuses on process improvement and variation reduction as a means towards performance improvement. The methodology has a reputation of success, however a number of organisations believe that the methodology is not relevant to their specific competitive needs. Six Sigma is seen as another continuous improvement tool applicable to first world country organisations which will fade away with time. The study was undertaken to find out challenges and successes of implementing a Six Sigma methodology at Continental Tyre SA. The findings of the study revealed that the experience of implementing Six Sigma methodology at Continental Tyre SA is similar to those experienced by first world organisations. It is concluded that Six Sigma methodology can improve organisation processes and yield financial benefits irrespective of organisation location or background. However, organisations must follow a systematic guideline when implementing the methodology. The study provides recommendations on how Continental Tyre SA can align their strategy in order to achieve organisational objectives. The following recommendations were made: Roll out Six Sigma to support departments; Align the strategy to address critical success factors; Improve project turnover time and measure the success on financial savings and number of projects completed.

D.Comm. / In recent years, the criticality of increased productivity and competitiveness has accelerated in step with global trends towards privatisation, marketisation, and democratisation, coupled with a more highly educated, more vocal and more demanding consumer market. At a time when the technological gap between South Africa, North America, Europe, and the Pacific Rim is shrinking, competitive boundaries are expanding and, as a consequence, consumers have a growing range of products from which to choose. Quality increasingly guides produce selection. Consumer spending patterns have also changed to reflect increased concern for durability, partially as a response to environmental concerns. Increasing recognition of the inadequacies of traditional quality control functions to address the demand for higher quality products and services has launched a seminal transition to a more comprehensive, integrated approach to quality management. Total Quality Management (TQM) refers to the implementation of a "continuous improvement" process to address inefficiencies at all levels of the organisation. There is no single theoretical formulation of the TQM approach nor any definitive short list of practices that are associated with it. It is the product of the work of such quality experts as Crosby, Deming, Juran, and Ishikawa. The writings of these Gurus, as well as characteristics typical of most successful TQM processes. TQM is best viewed as a management philosophy which combines the teaching of Deming and Juran on statistical process control and group problem-solving processes with values concerned with quality and continuous improvement. TQM is endorsed as a powerful vehicle in the transition from the traditional price focus to quality strategies driven by customer expectations. Improving quality and adopting a customer focused orientation are so fundamental that they must take root in the very essence of the organisation. To achieve ambitious quality goals, the TQM philosophy must permeate all aspects of organisational functioning, underscoring the criticality of human resource excellence to total quality processes. The TQM approach is frequently endorsed by the impressive results attributable to it. Marked improvements in productivity and efficiency, profits, customer satisfaction, management-employee relations, job satisfaction, morale, and reductions in costs, inventory, defects and inspection requirements are among an array of reported benefits to be derived from TQM initiatives. The positive relationship between quality and productivity may be largely rooted in the involvement of all employees to execute quality agendas. The benefits of employee involvement from increased productivity, job satisfaction and performance to reduced absenteeism and turnover are well documented. Great emphasis is placed on including all employees in the TQM culture. Employees are expected to take responsibility for quality in two important respects. They are expected to call attention to quality problems as they do their normal work. Perhaps more important, they are expected to accept the continuous improvement culture and look for ways to do their work better. They are also expected to look for ways in which the overall operation of the organisation can be improved to enhance customer service. The most important overall focus of employee involvement concerns locating decisions at the lowest level possible in the organisation. This approach consistently advocates a bottom-up approach to management. Jobs or work at the lowest level are thought of as designed best when individuals or teams do a whole and complete part of an organisation's work process. In addition, it is argued that the individuals or teams should be given the power, information, and knowledge they need to work autonomously or independently of management control. The task of management is seen as one of enabling and empowering individuals or teams to function in an autonomous manner. Management is an enabler, culture setter, and supporter rather than a direction of employee action. This study focuses on the development of the TQM philosophy, and the development of a TQM model to be used as reference in the design of a TQM process in a manufacturing environment. It also endeavours to formulate an implementation process that can be used as guideline for implementing TQM in an organisation. Research has been based on literature studies, extensive experience in the workplace, and interaction with a wide variety of practitioners in the TQM environment. The study concludes that South African organisations can address the issues prohibiting real economic growth by continuously improving every product and service produced through the involvement of an empowered workforce, operating in teams, with the objective of achieving optimum customer satisfaction in the long-term.

Engineering problems often involve many conflicting quality characteristics that must be optimized simultaneously. Engineers are required to select suitable design parameter values which provide better trade-off among all quality characteristics. Multiresponse optimization is one of the most essential tools for solving engineering problems involving multiple quality characteristics. Optimizing several quality characteristics when the quality characteristics are correlated makes the optimization process more complex. The aim of this research is to evaluate the performance of several existing multiresponse optimization methods and investigate their capabilities in dealing with correlated quality characteristics. This study also investigates the impact of uncertainty in terms of input parameter selection. A new multi-response optimization approach has been proposed for solving correlated quality characteristics. The proposed approach is compared with the existing methods and found more robust in terms dealing with uncertainty in target selection. The comparative study and application of the proposed approach is demonstrated by considering two examples from the literature having correlated quality characteristics.

The purpose of this study is three-fold. First, based on the synthesis of literature on quality concepts, critical factors that must be practiced to achieve effective quality management in an organization were identified. A framework to be used by organizations to evaluate their quality assurance practices were developed. Second, a field survey was conducted to identify the degree to which quality assurance is being practiced in Indian Manufacturing organizations and to locate the organizational areas where better management control can make the quality assurance system more effective. Finally, an attempt was made to develop models that could be used to forecast the level of quality achieved.

American industry is about nine to 12 years behind in utilizing a new product development and introduction process known as Quality Function Deployment (Q.F.D.). American industry must learn to compete internationally; the American automotive industry alone directly and indirectly employs millions of workers and has billions of dollars in annual sales and profits at stake. With the cooperation of one American automotive company research has been conducted on Q.F.D. The research objectives were to identify: what variables affect Q.F.D., what are the outcomes from Q.F.D., what relationships exist between Q.F.D. variables and outcomes, and what guidelines may be offered to Q.F.D. practitioners. A Multiple Perspectives systems approach was used in developing both what and how Q.F.D. was to be researched. After a literature search a descriptive Q.F.D. model was developed. A Q.F.D. measurement instrument was developed and used to collect technical data. Interviews were used to collect organizational and personal data. An 80% questionnaire response was obtained. Of the model's four outcomes Improved Design and Improved Communications had strong positive results with Improved Cost and Improved Time-to-Market unchanged. Explanations of these results were offered. A Factor Analysis was performed which verified that the three-level Q.F.D. model was appropriate and explained most of the response variation. A Reliability Assessment was conducted and the scales were found to be within or have exceeded the acceptable beginning research coefficient alpha range. A MANOVA Analysis was conducted, and five of the 17 Q.F.D. model's variables were identified as candidates for deletion for this company's present Q.F.D. system. A Ratio Data Assessment was conducted and used to develop five guidelines for this company's practitioners. Organizational and Personal Data Assessments were conducted and their similarities with the Technical Data Assessment were noted. Top Management Commitment, Customer Information Availability, Team Composition and Dynamics and Project Completion Time were identified as important similar Q.F.D. variable findings. Improved Design and Improved Communications were identified as important similar Q.F.D. outcomes. No major discontinuities between the three assessments were found. Research conclusions, contributions and future research work were identified.

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Quality perceptions of three major softwood lumber consumers: wood treaters, truss manufacturers, and home centers were investigated to determine their definition of softwood lumber quality. Data was gathered through a mail survey of buyers in each of the three groups. In total, 867 responses were received. Respondents rated the importance of product and service characteristics to quality. These characteristics were based on dimensions of product quality developed by Garvin (1984) and dimensions of service quality developed by Parasuraman et aI. (1988). A total of 80 product and service quality characteristics were assembled to represent, or measure, twelve dimensions of total product quality. Analysis indicated that the twelve dimension model, derived from previous work, was not applicable to softwood dimension lumber. Thus, exploratory factor analysis was used to assess the underlying dimensions of quality and a five dimension model resulted. The dimensions, ranked in order of importance, were: Lumber Characteristics, Supplier/Salesperson Characteristics, Lumber Performance, Supplier Services, and Supplier Facilities. These findings share few similarities with past research. In fact, they suggest that the concept of quality as a higher order abstract (i.e., dimensions of quality are similar regardless of product) may be flawed. Respondent groups differed in the importance they placed on three of the five dimensions. No difference in importance levels were found for Supplier/Salesperson Characteristics and Lumber Characteristics. However, truss manufacturers perceived Lumber Performance to be more important than treaters or home centers and Supplier Services was perceived to be more important by home centers than the other two groups. Finally, Supplier Facilities was perceived to be most important by treaters. Data gathered in a follow-up questionnaire indicated that the model developed in this study was understood by buyers of softwood lumber and that they buy from suppliers who perform well on dimensions of quality. Buyers also indicated that they pay more for better quality lumber and better service. This evidence indicates that suppliers of softwood dimension lumber can differentiate themselves based on quality and in tum command a higher price. Given these findings, strategies for utilizing quality, and the model developed in this study, to gain competitive advantage are discussed. / Ph. D.

No description available.

Networks of distributed, remote sensors are providing ecological scientists with a view of our environment that is unprecedented in detail. However, these networks are subject to harsh conditions, which lead to malfunctions in individual sensors and failures in network communications. This behavior manifests as corrupt or missing measurements in the data. Consequently, before the data can be used in ecological models, future experiments, or even policy decisions, it must be quality controlled (QC'd) to flag affected measurements and impute corrected values. This dissertation describes a probabilistic modeling approach for real-time automated QC that exploits the spatial and temporal correlations in the data to distinguish sensor failures from valid observations. The model adapts to a site by learning a Bayesian network structure that captures spatial relationships among sensors, and then extends this structure to a dynamic Bayesian network to incorporate temporal correlations. The final QC model contains both discrete and continuous variables, which makes inference intractable for large sensor networks. Consequently, we examine the performance of three approximate methods for inference in this probabilistic framework. Two of these algorithms represent contemporary approaches to inference in hybrid models, while the third is a greedy search-based method of our own design. We demonstrate the results of these algorithms on synthetic datasets and real environmental sensor data gathered from an ecological sensor network located in western Oregon. Our results suggest that we can improve performance over networks with less sensors that use exhaustive asynchronic inference by including additional sensors and applying approximate algorithms. / Graduation date: 2013

This study uses simulation to examine differences between fixed sampling interval (FSI) and variable sampling interval (VSI) Shewhart X-bar control charts for processes that produce positively autocorrelated data. The influence of sample size (1 and 5), autocorrelation parameter, shift in process mean, and length of time between samples is investigated by comparing average time (ATS) and average number of samples (ANSS) to produce an out of control signal for FSI and VSI Shewhart X-bar charts. These comparisons are conducted in two ways: control chart limits pre-set at ±3σ_x / √n and limits computed from the sampling process. Proper interpretation of the Shewhart X-bar chart requires the assumption that observations are statistically independent; however, process data are often autocorrelated over time. Results of this study indicate that increasing the time between samples decreases the effect of positive autocorrelation between samples. Thus, with sufficient time between samples the assumption of independence is essentially not violated. Samples of size 5 produce a faster signal than samples of size 1 with both the FSI and VSI Shewhart X-bar chart when positive autocorrelation is present. However, samples of size 5 require the same time when the data are independent, indicating that this effect is a result of autocorrelation. This research determined that the VSI Shewhart X-bar chart signals increasingly faster than the corresponding FSI chart as the shift in the process mean increases. If the process is likely to exhibit a large shift in the mean, then the VSI technique is recommended. But the faster signaling time of the VSI chart is undesirable when the process is operating on target. However, if the control limits are estimated from process samples, results show that when the process is in control the ARL for the FSI and the ANSS for the VSI are approximately the same, and exceed the expected value when the limits are fixed.