Thesis (Ph. D.)--Illinois State University, 1998. / Title from title page screen, viewed July 14, 2006. Dissertation Committee: Paul J. Baker (chair), Dianne E. Ashby, William C. Rau, Nancy E. Gibson. Includes bibliographical references (leaves 139-144) and abstract. Also available in print.

Thesis (M. Hous. M.)--University of Hong Kong, 2006.

Thesis (M.S.)--West Virginia University, 2006. / Title from document title page. Document formatted into pages; contains ix, 106 p. Vita. Includes abstract. Includes bibliographical references (p. 77-81).

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).

In this work, we have developed a robust daily quality assurance (QA) system for pencil-beam scanning (PBS) dosimetry. A novel phantom and multi-PTV PBS plan were used in conjunction with the Sun Nuclear Daily QA3 multichamber detector array to verify output, range, and spot position. The sensitivity to detect change in these parameters with our designed tests was determined empirically. Associated tolerance levels were established based on these sensitivities and guidelines published in recent American Association of Physics in Medicine (AAPM) task group reports. The output has remained within the 3% tolerance and the range was within ±1mm. Spot position has remained within ±2mm. This daily QA procedure is quick and efficient with the time required for setup and delivery at less than 10 minutes. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2020. / FAU Electronic Theses and Dissertations Collection

No description available.

Advances in microcomputing hardware and software over the last several years have resulted in personal computers with exceptional computational power and speed. As the costs associated with microcomputer hardware and software continue to decline, manufacturers have begun to implement numerous information technology components on the shop floor. Components such as microcomputer file servers and client workstations are replacing traditional (manual) methods of data collection and analysis since they can be used as a tool for real-time decision-making. Server-based and web-based shop floor data collection and monitoring software applications are able to collect vast amounts of data in a relatively short period of time. In addition, advances in telecommunications and computer interconnectivity allow for the remote access and sharing of this data for additional analysis. Rarely, however, does the method by which a manager reviews production and quality data keep pace with the large amount of data being collected and thus available for analysis. Visualization techniques that allow the decision maker to react quickly, such as the ability to view and manipulate vast amounts of data in real-time, may provide an alternative for operations managers and decision-makers. These techniques can be used to improve the communication between the manager using a microcomputer and the microcomputer itself through the use of computer-generated, domain-specific visualizations. This study explores the use of visualization tools and techniques applied to manufacturing systems as an aid in managerial decision-making. Numerous visual representations that support process and quality monitoring have been developed and presented for evaluation of process and product quality characteristics. These visual representations are based on quality assurance data and process monitoring data from a high-volume, discrete product manufacturer with considerable investment in both automated and intelligent processes and information technology components. A computer-based application was developed and used to display the visual representations that were then presented to a sample group of evaluators who evaluated them with respect to their ability to utilize them in making accurate and timely decisions about the processes being monitored. This study concludes with a summary of the results and provides a direction for future research efforts. / Ph. D.

Prostaglandin F2α (PGF2α) is commonly given to female cattle intramuscularly (IM) for the synchronization of estrus. A novel site for administration of PGF2α that improves beef quality assurance is the ischiorectal fossa (IRF). The objective of this study was to determine whether administration of PGF2α in the IRF results in a similar physiologic response to administration of PGF2α given IM. Yearling angus-cross heifers (n=112) were blocked by weight and randomly assigned within blocks to be injected with 5 mL PGF2α either IM in the neck or in the IRF. Blood samples were taken at 0, 8, 16, 24, 36, and 48 h post-injection. Serum samples were analyzed for progesterone concentration using a radioimmunoassay. Progesterone concentration curves for each heifer were plotted to determine luteolysis. The median times to luteolysis for neck and IRF injections were 18.1 hrs and 20.0 hrs, respectively (p=0.06). Angus cross commercial beef cows (n=1471) at least 30 days post-partum were blocked by age and randomly assigned to be injected with 5 mL PGF2α either IM in the neck muscle or in IRF as part of a 7-Day CO-Synch + CIDR ovulation protocol. Pregnancy diagnosis was performed via ultrasound at 60 days post insemination. Results were analyzed with Proc Glimmix (SAS). Pregnancy rates for neck and IRF injections were 52.6% and 57.2%, respectively (p=0.06). In summary, injection of PGF2α in the IRF for estrus synchronization and lysis of the corpus luteum did not differ from injection in the neck muscle. Utilizing the ischiorectal fossa as an injection site for PGF2α may be considered as an alternative that more closely aligns with beef quality assurance objectives. / Master of Science

No

by Wong Kwai Lin Christine. / Thesis (M.B.A.)--Chinese University of Hong Kong, 1996. / Includes bibliographical references (leaves 47-48). / ABSTRACT / TABLE OF CONTENTS / LIST OF FIGURES / LIST OF TABLES / ACKNOWLEDGMENT / Chapter / Chapter I. --- Introduction --- p.1 / Chapter II. --- Research --- p.3 / Exploratory Research --- p.3 / Literature Search --- p.4 / Quality Concepts --- p.4 / W. Edward Deming --- p.5 / Joseph Juran --- p.8 / Philip Crosby --- p.10 / Quality --- p.11 / ISO 9000 Series --- p.12 / The Malcolm Baldrige National Quality Award --- p.13 / Status of Promotion of Quality Management --- p.13 / Specific Research --- p.14 / Theoretical Basis --- p.15 / Descriptive Research --- p.17 / Data Collection Method --- p.18 / Method of Administration --- p.19 / Sample Design --- p.21 / Target Population --- p.21 / Sampling Frame --- p.21 / Sampling Procedure --- p.22 / Questionnaire Design --- p.22 / Part I - Company Demographics --- p.20 / Part II - Company Performance --- p.23 / Part III - Quality Improvement Techniques --- p.23 / Data Analysis --- p.24 / Response --- p.24 / Managerial Knowledge --- p.29 / Quality Performance --- p.30 / Financial Performance --- p.30 / Past Quality Performance --- p.30 / Market Place Environment --- p.31 / Corporate Support for Quality --- p.31 / Role of Management Leadership and Quality --- p.32 / Quality Data and Reporting --- p.33 / Strategic Quality Planning --- p.33 / Employees' involvement and Participation --- p.34 / Employees' Training --- p.34 / Feedback and Recognition of Employees' Performance --- p.35 / Employees' Relations --- p.36 / Product Service Design --- p.36 / Process Management --- p.36 / Supplier Quality Management --- p.37 / Role of Quality Department --- p.38 / Customer Feedback --- p.39 / Chapter III. --- SUMMARY OF FINDINGS --- p.40 / Difference between Manufacturing and Service Companies --- p.41 / Difference between Companies with without Separate Quality Department --- p.41 / Difference between Companies with or without Certification --- p.42 / Chapter IV. --- CONCLUSIONS --- p.44 / Chapter V. --- RECOMMENDATIONS --- p.46 / BIBLIOGRAPHY / Chapter APPENDIX 1 --- Sample Questionnaire / Chapter 2 --- Figures 2 to 18