An improved sampling plan by variables inspection with consideration of process yield and quality loss

Repetitive group sampling (RGS) plan, a modified version of single sampling (SS) plan, has been shown to be more efficient than the SS plan for lot sentencing. However, because it does not consider the valuable sample information from preceding lots, that could reduce its sampling efficiency and discriminatory power. Therefore, this study proposes a modified-RGS plan by considering the quality history of preceding lots based on the C_pmk index. Additionally, the mathematical model for the plan parameters is formulated such that the objective function is to minimize the average sample number (ASN), and the required quality levels and risks as specified by producer and consumer are satisfied. The performance of the proposed plan is examined and compared with traditional sampling plans. Finally, an example is presented to illustrate its applicability.     

A multivariate non-parametric kernel estimator for global sensitivity analysis

The fact of estimating how a model output is influenced by the variations of inputs has become an important problematic in reliability and sensitivity analysis. This article is interested in estimating sensitivity indices useful to quantify the contribution of inputs to the variance of model output. A multivariate mixed kernel estimator is investigated since, until now, discrete and continuous inputs have been separately considered in kernel estimation of sensitivity indices. To illustrate the differences between the influence of mixed, discrete, and continuous inputs, analytical expressions of Sobol sensitivity indices are expressed in these three cases for the Ishigami test function. Besides, the performance of the mixed kernel estimator is illustrated through simulations in which the Bayesian procedure is applied for bandwidth parameter choice. An application is also realized on a real example. Finally, the use of an appropriate kernel estimator according to the type of inputs is found to be influential on the accuracy of sensitivity indices estimates.     

农户信用评价体系构建研究

在述评前人研究的基础上,结合农户特征,从农户的家庭特征、偿债能力、经营情况、信誉状况及其他指标五大方面,构建了由农户户主的年龄、健康状况、受教育程度、特殊技术和技能、婚姻状况等28个二级指标构成的农户信用评价指标体系。在此基础上,运用层次分析法构造指标判断矩阵并进行指标权重的计算,为科学评价农户信用奠定基础。     

Process capability analysis for serially dependent processes of Poisson counts

Process capability indices evaluate the actual compliance of a process with given external specifications in a single number. For the case of a process of independent and identically distributed Poisson counts, two types of index have been proposed and investigated in the literature. The assumption of serial independence, however, is quite unrealistic for practice. We consider the case of an underlying Poisson INAR(1) process which has an AR(1)-like autocorrelation structure. We show that the performance of the estimated indices is degraded heavily if serial dependence is ignored. Therefore, we develop approaches for estimating the process capability (both for the observation and innovation process), which explicitly consider the observed degree of autocorrelation. For this purpose, we introduce a new unbiased estimator of the innovations’ mean of a Poisson INAR(1) process and derive its exact as well as asymptotic stochastic properties. In this context, we also present new explicit expressions for the third- and fourth-order moments of a Poisson INAR(1) process. Then the capability indices and the performance of their estimators are analysed and recommendations for practice are given.     

Evaluation of process capability in multivariate nonlinear profiles

ABSTRACT

Process capability indices measure the ability of a process to provide products that meet certain specifications. Few references deal with the capability of a process characterized by a functional relationship between a response variable and one or more explanatory variables, which is called profile. Specifically, there is not any reference analysing the capability of processes characterized by multivariate nonlinear profiles. In this paper, we propose a method to measure the capability of these processes, based on principal components for multivariate functional data and the concept of functional depth. A simulation study is conducted to assess the performance of the proposed method. An example from the sugar production illustrates the applicability of this approach.     

Asymptotic random extremal ratio and product based on generalized order statistics and its dual

The extremal ratio has been used in several fields, most notably in industrial quality control, life testing, small-area variation analysis, and the classical heterogeneity of variance situation. In many biological, agricultural, military activity problems and in some quality control problems, it is almost impossible to have a fixed sample size, because some observations are always lost for various reasons. Therefore, the sample size itself is considered frequently to be an random variable (rv). Generalized order statistics (GOS) have been introduced as a unifying theme for several models of ascendingly ordered rvs. The concept of dual generalized order statistics (DGOS) is introduced to enable a common approach to descendingly ordered rvs. In this article, the limit dfs are obtained for the extremal ratio and product with random indices under non random normalization based on GOS and DGOS. Moreover, this article considers the conditions under which the cases of random and non random indices give the same asymptotic results. Some illustrative examples are obtained, which lend further support to our theoretical results.     

Entropic representation and estimation of diversity indices

This paper serves a twofold purpose. First, a unified perspective on diversity indices is introduced based on an entropic basis. It is shown that the class of all linear combinations of the entropic basis, referred to as the class of linear diversity indices, covers a wide range of diversity indices used in the literature. Second, a class of estimators for linear diversity indices is proposed and it is shown that these estimators have rapidly decaying biases and asymptotic normality.     

Applying a fuzzy analytic network process to construct a purchase project. A case for the purchase of a slicing diamond cutting machine

In this paper we propose a fuzzy extension of the analytic network process (ANP) that uses uncertain human preferences as input information in the project evaluation of precision diamond cutting machines. The resulting fuzzy ANP enhances the potential of the ANP for dealing with imprecise and uncertain human comparison judgments. It allows for multiple representations of uncertain human preferences, as crisp, interval, and fuzzy judgments and can find a solution from incomplete sets of pair-wise comparisons. An important feature of the proposed method is that it measures the inconsistency of the uncertain human preferences by an appropriate consistency index. Simultaneously, process capability indices are presented to demonstrate and verify the feasibility and effectiveness of the proposed methods. In the future, the proposal can provide the best way to control and calculate effective purchasing of diamond cutting machines for wafer slicing by project buyers. This purchasing project will save cost and ease the case of purchase.     

论可持续发展指标评价体系

我们应本着科学、求实的工作态度 ,建立起科学合理的指标评价体系。只有这样 ,我们的建设事业才能生生不息 ,走真正的可持续发展之路     

Developing a Model for the Measurement of Social Inclusion and Social Capital in Regional Australia

This paper reviews the literature on social inclusion and social capital to develop a framework to guide the selection of items and measures for the forthcoming SA Department of Human Services Survey of Social Inclusion to be held in the region of Northern Adelaide in South Australia. Northern Adelaide is a region with areas of high socio-economic disadvantage, characterized by high unemployment and poverty. Survey respondents’ perceptions of social inclusion and social capital in Northern Adelaide will be examined by developing indices, which address the theoretical schema discussed in this paper. Epistemological differences between seminal theorists on social inclusion and social capital suggest the development of a broad suite of indices is required to enable the collection of data of interest to researchers from differing theoretical perspectives. Data collected in the survey will be mapped using Geographic Information System (GIS) technologies against locations within Northern Adelaide and in relation to existing Australian Bureau of Statistics, Commonwealth and State Government databases on age, gender, relative socio-economic disadvantage and other variables.