1,721,095 research outputs found
PERFORMANCE ANALYSIS FOR CDMA SOFT HANDOFFS BETWEEN MSC'S UNDER HEXAGONAL CONFIGURATION
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Attribute Control Charts for the Weibull Distribution under Truncated Life Tests
No full textIn this article, an attribute control chart is proposed when the lifetime of a product follows a Weibull distribution, which is based on the number of failures from a truncated life test. The coefficients of the proposed control chart and the test duration are determined so that the average run length when the process is in control is close to the target value. Tables reporting the out-of-control average run lengths are given for various shift parameters. A case study is given to illustrate the proposed control chart for industrial use.112116sciescopu
Flexible patient rule induction method for optimizing process variables in discrete type
No full textThis paper deals with process optimization, which establishes the optimal settings of process variables to achieve a better quality. To this end, the patient rule induction method (PRIM), widely used in various application areas, could be adopted. However, the PRIM may fail to provide successful solutions when some process variables are in discrete types. Thus, we propose a new PRIM-like method specially to deal with ordinal discrete variables. For an illustrative purpose, the proposed method is applied to a real steel-making process. Also, performance of the proposed method is compared with the original PRIM through an extensive simulation using artificial data sets. (c) 2007 Elsevier Ltd. All rights reserved.X119sciescopu
SIMULATING THE AVERAGE RUN-LENGTH FOR CUSUM SCHEMES USING VARIANCE REDUCTION TECHNIQUES
No full textSome variance reduction techniques utilizing the total hazard are developed to estimate the average run lengths of the cumulative sum charts through simulation when the process follows a general probability distribution. Particularly, we propose the hazard estimator and the cycle estimator. Simulation results are shown for the exponential case and these estimators are compared with the raw simulation estimator. Applicability to multivariate CUSUM schemes is briefly discussed in the conclusion.X114sciescopu
SOME VARIANTS OF POLYGON-TO-CHAIN REDUCTIONS IN EVALUATING RELIABILITY OF UNDIRECTED NETWORK
No full textWe propose some network reduction techniques applicable to the structures which could not be handled by the existing polygon-to-chain reduction techniques. The relationship is derived between the reliabilities of the original graph and the reduced graphs; The efficiency of these techniques is shown through the several numerical examples.X1110sciescopu
Designing of a variables two-plan system by minimizing the average sample number
No full textThis article proposes a variables two-plan sampling system called tightened-normal-tightened (TNT) sampling inspection scheme where the quality characteristic follows a normal distribution or a lognormal distribution and has an upper or a lower specification limit. The TNT variables sampling inspection scheme will be useful when testing is costly and destructive. The advantages of the variables TNT scheme over variables single and double sampling plans and attributes TNT scheme are discussed. Tables are also constructed for the selection of parameters of known and unknown standard deviation variables TNT schemes for a given acceptable quality level (AQL) and limiting quality level (LQL). The problem is formulated as a nonlinear programming where the objective function to be minimized is the average sample number and the constraints are related to lot acceptance probabilities at AQL and LQL under the operating characteristic curve.X112118sciescopu
Use of contagious distributions in the semiconductor yield models considering cluster effect
No full textAs semiconductor chips become larger, more than one cluster can be expected to form on a single chip and consequently defect density variations may be apparent not only among chips but also within a chip. In order to reflect this situation more effectively, we propose semiconductor yield models based on the contagious distributions. These models incorporate the probability that a defect or a cluster becomes fatal. Furthermore, we consider various limiting forms of the proposed contagious distribution by taking extreme values of the related parameters. A simplified form of the proposed yield formula based on the limiting distribution is also derived and its performance is compared with others using computer simulation. The proposed three yield models are shown in a simulation study to outperform alternative models based on the existing ideas.X115sciescopu
Semiconductor yield models using contagious distributions and their limiting forms
No full textIn order to set up a semiconductor yield model, one should consider defect density variations not only among chips but also within a chip. In this paper, we propose semiconductor yield models based on the contagious distributions reflecting the variations. These models incorporate the probability that a defect becomes fatal. We also consider various limiting forms of a proposed contagious distribution by taking extreme values of the related parameters. A simplified form of the proposed yield formula based on the limiting distribution is derived and its performance is compared with others using computer simulation. The proposed three yield models are shown in a simulation study to outperform alternative models based on the existing ideas. (C) 2002 Elsevier Science Ltd. All rights reserved.X112sciescopu
Learning Bayesian network structure using Markov blanket decomposition
No full textCausal structure learning algorithms construct Bayesian networks from observational data. Using non-interventional data, existing constraint-based algorithms may return I-equivalent partially directed acyclic graphs. However, these algorithms do not fully exploit the graphical properties of Bayesian networks, and require many redundant tests that reduce both speed and accuracy. In this paper, we introduce ideas to exploit such properties to increase the speed and accuracy of causal structure learning for multivariate normal data. In numerical experiments on five benchmarking networks our proposed algorithm was faster and more accurate than recently-developed algorithms. (c) 2012 Elsevier B.V. All rights reserved.X1198sciescopu
Use of reference distributions when dealing with unknown regression errors
No full textA problem of estimating regression coefficients is considered when the distribution of error terms is unknown but symmetric. We propose the use of reference distributions having various kurtosis values. It is assumed that the true error distribution is one of the reference distributions, but the indicator variable for the true distribution is missing. The generalized expectation-maximization algorithm combined with a line search is developed for estimating regression coefficients. Simulation experiments are carried out to compare the performance of the proposed approach with some existing robust regression methods including least absolute deviation, Lp, Huber M regression and an approximation using normal mixtures under various error distributions. As the error distribution is far from a normal distribution, the proposed method is observed to show better performance than other methods.X110sciescopu
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