Mixture cumulative count control chart for mixture geometric process characteristics

A statistical process control chart named the mixture cumulative count control chart (MCCC-chart) is suggested in this study, motivated by an existing control chart named cumulative count control chart (CCC-chart). The MCCC-chart is constructed based on the distribution function of a two component mixture of geometric distributions using the number of items inspected until a defective item is observed ‘n’ as plotting statistics. We have observed that the MCCC-chart has the ability to perform equivalent to the CCC-chart when number of defective items follows geometric distribution and better than the CCC-chart when the number of defective items produced by a process follows a mixture geometric model. The MCCC-chart may be considered as a generalized version of CCC-chart.     

Fuzzy Control Chart A Better Alternative for Shewhart Average Chart

This paper through a real illustrative example and a power test shows that designing a fuzzy control chart for process average of a continuous (variable) quality characteristic with a warning line is a better alternative to Shewhart chart in many respects, like providing better neural view to inspectors, offering different strategic options for company to choose, detecting the desire shifts more quickly, and more sensibility to small shifts without any complexity augmentation to the chart.     

Expatriate adjustment from the inside out: an autoethnographic account

This paper identifies some of the dynamics of expatriate adjustment using an autoethnographic account of situations experienced by the first author during her first year of work at a financial services company in Hong Kong. Success in this cross-cultural assignment is dependent on the expatriate's ability to adjust to and master the new culture. Our theoretical analysis of the autoethnographic account suggests that culture shock may be a discontinuous process. Further, the analysis suggests that cultural acceptance can play a critical role in expatriate adjustment.     

Hotelling’s <Emphasis Type="Italic">T</Emphasis><Superscript>2</Superscript> control chart with two adaptive sample sizes

Some quality control schemes have been developed when several related quality characteristics are to be monitored. The familiar multivariate process monitoring and control procedure is the Hotelling’s T ² control chart for monitoring the mean vector of the process. It is a direct analog of the univariate shewhart [`(x)]{\bar{x}} chart. As in the case of univariate, the ARL improvements are very important particularly for small process shifts. In this paper, we study the T ² control chart with two-state adaptive sample size, when the shift in the process mean does not occur at the beginning but at some random time in the future. Further, the occurrence time of the shift is assumed to be exponentially distributed random variable.     

Application of fuzzy mathematical programming to imprecise project management decisions

In real-world project management (PM) decisions, the input data and environmental coefficients are generally imprecise/fuzzy because of incompleteness and unavailability of relevant information over the project planning horizon. This work aims to present a fuzzy mathematical programming approach to solve imprecise PM decision problems with fuzzy goal and fuzzy cost coefficients. The designed PM decision model attempts to minimize total project costs with reference to direct costs, indirect costs, contractual penalty costs, duration of activities and the constraint of available budget. The proposed approach achieves greater computational efficiency by employing the simplified triangular fuzzy number to represent imprecise goal and cost coefficients, and provides a systematic framework that facilitates the decision-making process, enabling a decision maker to interactively modify the imprecise data and related parameters until a satisfactory solution is obtained. An industrial case is implemented to demonstrate the feasibility of applying the proposed approach to practical PM problems. The computational methodology developed in this work can easily be extended to any other situations and can handle the realistic PM decisions in fuzzy environments.     

Determining the parameters of statistical tests by fuzzy constraints

In this paper an approach is presented how to determine the parameters of statistical tests by means of fuzzy constraints on the probabilities of the errors of type I and of type II and on the sample size; here the case of single sampling is considered. A general upper bound for the sample size of an optimal test is derived. Furthermore, the approach is illustrated by two applications: the determination of an optimal one-sided Gauß-test and the determination of an optimal test on a fraction particularly important in acceptance sampling.     

Simplified Jackknife Variance Estimates for Fuzzy Measures of Multidimensional Poverty

In this paper, we present a practical methodology for variance estimation for multi‐dimensional measures of poverty and deprivation of households and individuals, derived from sample surveys with complex designs and fairly large sample sizes. The measures considered are based on fuzzy representation of individuals' propensity to deprivation in monetary and diverse non‐monetary dimensions. We believe this to be the first original contribution for estimating standard errors for such fuzzy poverty measures. The second objective is to describe and numerically illustrate computational procedures and difficulties in producing reliable and robust estimates of sampling error for such complex statistics. We attempt to identify some of these problems and provide solutions in the context of actual situations. A detailed application based on European Union Statistics on Income and Living Conditions data for 19 NUTS2 regions in Spain is provided.     

物流设施规划综合效果评价的灵敏度分析

在研究有关物流设施规划理论基础上,详细分析影响物流设施规划的因素,然后在充分考虑影响因素的基础上,利用模糊控制理论建立物流设施规划综合效果评价模型。通过该评价模型对影响物流设施规划的因素进行灵敏度分析,在因素输入值变化时得到综合效果的变化趋势图,从而整体上了解影响因素的灵敏程度;再根据影响因素与综合效果的关系,量化影响因素灵敏度,最后通过一个实例说明灵敏度分析的应用。     

Run length distributions for estimated attributes charts

Attributes control charts, such as c and p charts, are popular methods for detecting out of control signals when it is practical only to obtain qualitative information about a process; in such cases, variables control charts, such as the , s and R charts, cannot be used. The run length distributions have previously been studied for variables charts when the control limits have been estimated. Little has been done in the case of attributes charts. In this paper, the run length distributions for the c chart and p chart are derived for the case when the control limits are estimated. It is shown that, as for variables charts, the effect of estimation on quantities such as the average run length (ARL) can be quite dramatic, but when the underlying process is in control, the ARL is potentially misleading as a basis for comparison. Received: September 1998     

基于Wilcoxon秩和检验的多元非参数控制图

在统计过程控制(SPC)中,对多元数据的监测仍然是一个重要且具有挑战性的问题。当缺乏或有限的关于潜在过程分布的认知时,特别是当过程测量是多变量的时候,非参数控制图在统计过程控制(SPC)中是有用的。文章基于Wilcoxon秩和检验结合广义加权移动平均(GWMA)控制方案来制定图表统计量,得到一个新的多元非参数控制图,用于监测多元数据的位置参数变化。文章的理论和数值研究表明,所提出的控制图能够为任意数据分布位置偏移检测提供令人满意的性能。     

A fuzzy clustering approach used in evaluating technical efficiency measures in manufacturing

Comparing analytical approaches is crucial when important policy decisions of corporations or government agencies may be influenced by results that depend on the methodologies certain disciplines customarily use. Technical efficiency can be measured by a full-frontier production function model or by linear programming specifications. By using these modeling approaches observations pertaining to three linerboard manufacturing facilities are classified as efficient, inefficient, scale inefficient, and other. However, observations may or may not be consistently classified into these four groups when employing the two modeling approaches. In order to validate the efficiency designations of the two modeling approaches and to determine the uniqueness of observations, a fuzzy K-means clustering approach that uses a modified hat matrix H ^* as a similarity or information matrix is employed. This approach permits observations to be allocated to clusters in a fuzzy way by defining a membership function from 0 to 1. As the degree of fuzziness increases, a sensitivity analysis with respect to individual observations belonging to some cluster can be evaluated. At the same time, this fuzzy approach assists the analyst to assess the inconsistencies that can arise when using the mathematical programming and full-frontier modeling approaches of technical efficiency.The refereeing process of this paper was handled through Rolf Färe. The majority of this research work was completed when Bill Seaver was at the Department of Management Information Resources, College of Business Administration, Western Illinois University, Macomb, IL 61455.     

Asymmetric control limits for small samples

When designing control charts, it is usually assumed that the measurement in the subgroups are normally distributed. The assumption of normality implies that the control limits for a chart for sample averages will be symmetrical about the centerline of the chart. However, the assumption of an underlying normal distribution of the data may not hold in some processes. If the measurements are asymmetrically distributed then the decision maker may choose different actions. One thing that can be done is to consider the degree of skewness. If the nature of the underlying distribution is skewed, then the traditional Shewhart individuals chart may not be valid. This paper presents a technique for constructing appropriate asymmetric control limits when the distribution of data cannot be assumed to be a normal distribution. Meanwhile, it proposes a skewness correction method for the generated Burr, lognormal and exponential distributions. Some numerical calculations are generated for n  =  2, 3, 4 by using MATLAB.     

The application of change management theory to HR portal implementation in subsidiaries of multinational corporations

HR portals are complex information technology (IT) applications that can be accessed by all employees of a given organization. By placing more applications and information online, HR portals reduce the reliance employees have on HR personnel. Given this relational change, from human to computer, the HR portal implementation process must take into account the challenges of both change management and technology acceptance. By integrating change management theories with IT user acceptance models, this article adds to HR's collective knowledge of ways to effectively implement HR portals. In addition, this article describes the cross‐national challenges that exist when a global firm attempts to implement an HR portal around the world. Thus, this article will present a model that (1) integrates change management theories and IT user acceptance models and (2) illustrates the ways in which change management plans may need to be adapted to be effective in various subsidiaries. A case study of Hewlett‐Packard's (HP's) worldwide implementation of their @HP Employee Portal in the Italian subsidiary of HP illustrates the key issues of these theories. © 2005 Wiley Periodicals, Inc.     

A fuzzy model to assess the resilience of Protection and Civil Defense Organizations

Resilience is the intrinsic ability of a system to adjust its functioning prior to, during, or following changes and disturbances, so that it can sustain required operations under expected and unexpected conditions. Protection and Civil Defense Organizations (PCDOs), communities and cities deal with disaster management involving routine, non-routine and even unpredictable/unforeseen situations with varying degrees of complexity. It is important that such organizations continually assess their resilience, enable them to learn on their weaknesses and real capacities to cope with emergency situations. This research aimed the development of an Organization Resilience Indicator System (ORIS) based on a fuzzy model to enable PCDOs self-assesses their resilience. Based on a literature review on organizational and community’s resilience, a system of resilience indicators was defined. This system was validated by experts using fuzzy set theory to aggregate opinions in the development of a resilience ideal pattern. Then, the resilience of four PCDO organizations was self-evaluated. The results were accordingly to maturity level of the organizations evaluated, indicating that the ORIS is valuable to measure PCDOs resilience.     

简论内部管理审计在公司治理中的作用及其措施

内部管理审计是公司治理结构的重要组成部分,在公司治理中起着重要作用。然而我国公司对内部管理审计却较为忽略,导致内部审计问题众多。为了完善公司治理,提高管理效率,必须通过调整内部管理审计的组织结构、规范内部审计程序、提高审计师素质和能力、以及优化具体审计措施等方面强化内部管理审计。     

The effect of the individual chart with variable control limits on the river pollution monitoring

This study performs a model to evaluate the river water quality monitoring system. The standard River Pollution Index which includes dissolved oxygen (DO), biochemical oxygen demand (BOD₅), suspended solids (SS), and ammonia nitrogen (NH₃-N) is collected from years 2006 to 2010 for monitoring of river water quality. Furthermore, control chart technology can monitor the river pollution and signal the aggravation of water quality. This study proposes an individual control chart with variable control limits (VCL individual chart) and verifies this chart can quickly signal the mean change of both normal can skew populations in statistical performances. In addition, this study also presents a real case that VCL individual chart is applied on monitoring the water quality of Taiwan’s river. This case shows the VCL individual chart controls successfully the river pollution, and this chart is very suitable to apply monitoring the water quality of rivers.     

Polynomial approximations in cross-sectional models

The time-series distributed lag techniques of econometrics can be usefully applied to cross-sectional, spatial and cross-section time-series situations. The application is perfectly natural in cross-section, time-series models when regression coefficients evolve systematically as the cross-section grouping variable changes. The evolution of such coefficients lends itself to polynomial approximation or more general smoothing restrictions. These ideas are not new, Gersovitz and McKinnon (1978) and Trivedi and Lee (1981) providing two of the earliest applications of cross-equation smoothing techniques. However, their applications were in the context of coefficient variation due to seasonal changes and this may account for the non-diffusion of these techniques. The approach here is illustrated in the context of age-specific household formation equations based on census data, using Almon polynomials when the regression coefficients vary systematically by age group. A second application is provided, using spatial data, explaining the incidence of crime, by region; using polynomial and geometric smoothing to model distance declining regional effects.     

Comparisons of control schemes for monitoring the means of processes subject to drifts

Although statistical process control (SPC) techniques have been focused mostly on detecting step (constant) mean shift, drift which is a time-varying change frequently occurs in industrial applications. In this research, for monitoring drift change, the following five control schemes are compared: the exponentially weighted moving average (EWMA) chart and the cumulative sum (CUSUM) charts which are recommended detecting drift change in the literature; the generalized EWMA (GEWMA) chart proposed by Han and Tsung (2004) and two generalized likelihood ratio based schemes, GLR-S and GLR-L charts which are respectively under the assumption of step and linear trend shifts. Both the asymptotic estimation and the numerical simulation of the average run length (ARL) are presented. We show that when the in-control (IC) ARL is large (goes to infinity), the GLR-L chart has the best overall performance among the considered charts in detecting linear trend shift. From the viewpoint of practical IC ARL, based on the simulation results, we show that besides the GLR-L chart, the GEWMA chart offers a good balanced protection against drifts of different size. Some computational issues are also addressed.     

On the properties of the hotelling��s T2 control chart with variable sampling intervals

When T ² control chart is used to monitor a process, it is usually assumed that the samples of size n ₀ is taken at constant intervals t ₀ . In this paper, we investigate the T ² control chart for monitoring the process mean vector when the sampling intervals are variable. Recent studies have shown that the variable sampling interval (VSI) scheme helps practitioners detect process shifts more quickly than the classical scheme Fixed Ratio Sampling (FRS). In this paper, it is assumed that the length of time the process remains in control is exponentially distributed.     

模糊综合评价法在工业污水处理投资中的应用

工业污水处理在企业发展进程中显得越来越重要,其项目投资决策的准确与否直接关系到该企业生存状态,以至于会影响到一个地区的整体环境水平。本文就模糊综合评价法的基本概念和基本原理进行描述,并结合实例阐述在该类型决策中如何应用模糊评价法,以提高项目投资决策的准确率,为工业污水处理设施的选择提供决策依据。