Browsing by Subject "Quality assurance"
Now showing 1 - 3 of 3
Results Per Page
Sort Options
Item Defect rate estimation and cost minimization using imperfect acceptance sampling with rectification(1997-05) Wadhwa, Neerja, 1966-; George, Edward I.An important aspect of any quality control program is estimation of the quality of outgoing products. This dissertation applies Acceptance Sampling with rectification to the problem of quality assurance when the inspection procedure is imperfect. The objective is to develop effective rectification sampling plans and estimators based on these plans without making the assumption of a perfect inspection procedure. We develop estimators, under two different sampling plans, for the number of undetected defects remaining after a set of lots has been passed. We compare, by extensive simulation, the proposed estimators with existing ones in terms of Root Mean Squared Error (RMSE). One of our estimators, an empirical Bayes estimator, is seen to consistently obtain substantially lower RMSE overall. We also construct expected cost functions for sampling plans based on fixed sample sizes. We then show how intermediate empirical Bayes estimates of population characteristics can be used to obtain adaptive acceptance sampling plans which vary the sample sizes in order to reduce expected cost. We also compare the two sampling plans on the basis of RMSE and expected cost functions. We show that RMSE comparisons across different levels of machine imperfection can be misleading and propose a measure which accounts for MSE and expected cost simultaneously.Item Quality and competitive advantage: an empirical study of ISO 9000 adoption in the electronics industry(Texas Tech University, 2003-05) Morris, Philip WayneQuality and quality related issues have been a topic of research interest in the business field for sometime. Quality management practices are seen as a competitive advantage. The conventional wisdom is that better quality leads to higher revenues, decreases costs, and increased profits. Empirical archival financial studies concerning the link between quality and financial performance have been difficuU because the area of quahty management practices suffers from multiple definitions, varying degrees of implementation, and lack of specific implementation dates. These difficulties limit researchers' ability to examine the cost/benefit relationship between quality management and financial improvements. This dissertation attempts to overcome some of these research difficulties by focusing on firms that become ISO 9000 certified. ISO 9000 is a quality standard that provides guidelines that are generic and can be applied to any type of organization. Specifically, the effect of ISO 9000 certification on financial performance in the elecfronics industry is examined in this dissertation. Hypotheses and control variables were developed from resource advantage theory and the quality, ISO 9000, adaptive assets, and research and development literatures. Publicly available financial data was gathered for both ISO 9000 certified and non-certified companies and used to test the hypotheses. Pooled cross-sectional regressions were used in the testing of the hypotheses. The results of this study were mixed. However, in general they failed to support the major hypotheses. Firms that were ISO 9000 certified (and therefore following a quality management practice) did not have greater financial performance than did firms that were not ISO 9000 certified. Furthermore, ISO 9000 certified firms actually saw their financial performance decline after they became ISO 9000 certified when compared to the financial performance before becoming ISO 9000 certified.Item Temporal modeling of crowd work quality for quality assurance in crowdsourcing(2015-12) Jung, Hyun Joon; Lease, Matthew A.; Mooney, Raymond; Bennett, Paul; Fleischmann, Kenneth; Wallace, Byron CWhile crowdsourcing offers potential traction on data collection at scale, it also poses new and significant quality concerns. Beyond the obvious issue of any new methodology being untested and often suffering initial growing pains, crowdsourcing has faced a very particular criticism since its inception: given anonymity of crowd workers, it is questionable whether we can trust their contributions as much as work completed by trusted workers. To relieve this concern, recent studies have proposed a variety of methods. However, while temporal behavioral patterns can be discerned to underlie real crowd work, prior studies have typically modeled worker performance under an assumption that a sequence of model variables is independent and identically distributed (i.i.d). This dissertation focuses on the measurement and prediction of crowd work quality by considering its temporal properties. To better model such temporal worker behavior, we present a time-series prediction model for crowd work quality. This model captures and summarizes past worker label quality, enabling us to better predict the quality of each worker’s next label. Further- more, we propose a crowd assessor model for predicting crowd work quality more accurately. By taking account of multi-dimensional features of a crowd assessor, we aim to build a better quality prediction model of crowd work. Finally, this dissertation explores how the proposed prediction models work under realistic scenarios. In particular, we consider a realistic use case in which limited gold labels are provided for learning our proposed model. For this problem, we leverage instance weighting with soft labels, which takes ac- count of uncertainty of each training instance. Our empirical evaluation with synthetic datasets and a public crowdsourcing dataset has shown that our pro- posed models significantly improve prediction quality of crowd work as well as lead to an acquisition of better quality labels in crowdsourcing.