Economic and economic–statistical designs of VSI Bayesian control chart using Monte Carlo method and ABC algorithm

The usual practice in using a Bayesian control chart to monitor a process is done by taking samples from the process with fixed sampling intervals. Recent studies on traditional control charts have shown that variable sampling interval (VSI) scheme compared to classical scheme (fixed ratio sampling, FRS) helps practitioners to detect process shifts more quickly. In this paper, the effectiveness of VSI scheme on performance of Bayesian control chart has been studied, based on economic (ED) and economic–statistical designs (ESD). Monte Carlo method and artificial bee colony algorithm have been utilized to obtain optimal design parameters of Bayesian control chart (sample size, sampling intervals, warning limit and control limit) since the statistic of this approach does not have any specified distribution. Finally, VSI Bayesian control chart has been compared to FRS Bayesian and VSI X-bar approaches based on ED and ESD, separately. According to the results, it has been found that the performance of VSI Bayesian scheme is better than FRS Bayesian and VSI X-bar approaches.     

Zero defects: a quality costs approach

Zero Defects has been advocated a s the ultimate target for quality control and assurance.Thispaper conducts an economic analysis of such a concept.The traditional frame work of quality

costs analysis is used to provide the bas is of analysis.A modified quality costs model is formulated to incorporate the revenue effects of quality and the dynamic nature of the manufacturing environment.It is shown that,for the quality cost model specified in this paper,the optimal dynamic strategy for the producer is to continuously improve product quality. Further more,the consumers'perspective and the existence of hidden or unidentifiable defects further reinforce the importance of quality improvement.In this way,a sound economic basis is provided for the Zero Defects concept.     

Robust algorithms for economic designing of a nonparametric control chart for abrupt shift in location

The existing statistical process control procedures typically rely on the fundamental assumption of a parametric distribution of the quality characteristic. However, when there is a lack of knowledge about the underlying distribution (as full knowledge is not available in practice), the performance of these parametric charts is very likely to be heavily degraded. Motivated by this problem, a one-sided nonparametric monitoring procedure using the single sample sign statistic is proposed for detecting a shift in the location parameter of a continuous distribution. An economic model of the control chart is developed to optimize the sample size, sampling interval, and control limits. Three data-dependent estimation approaches for the unknown parameter are evaluated and discussed. Simulation results exhibit that our proposed procedure generally performs well under a great variety of continuous distributions and hence it is recommended as an alternative scheme especially when the knowledge of the underlying distribution is imperfect. Furthermore, beneficial recommendations of estimation approach selection are provided for practical implementation of the control chart.     

经济安全及其评估

一、经济安全的涵义所谓经济安全,是在经济全球化的条件下,一国保持经济系统运行与经济发展不受到外来势力根本威胁的状态。之所以采用这个定义,主要是由于：第一,该定义符合“综合安全”的观念。在冷战结束之前,国家安全首先是军事安全和政治安全,经济安全并不象现...     

Statistical Monitoring of Nominal Logistic Profiles in Phase II

Statistical analysis of profile monitoring, a relatively new sub-area of statistical process control due to its applications in different industries, have urged researchers and practitioners to contribute to the developments of new monitoring methods. A statistical profile is a relationship between a quality characteristic (a response) and one or more independent variables to characterize quality of a process or a product. In this article, statistical profiles based on nominal responses are studied, where logistic regression is used to model the responses. Three approaches including likelihood ratio test (LRT), multivariate exponentially weighted moving average (MEWMA), and support vector machines (SVM) approaches are proposed to monitor quality of a process or product in Phase II. Performances of the proposed approaches are evaluated and compared using a case study. Moreover, the effect of two important factors on average run length (ARL) performance, number of levels and number of covariates, has been considered. Results indicate that performance of all approaches depends on the number of covariates and levels. As the number of these factors increases, SVM performance improves while performance of the other approaches deteriorates.     

Economic and economic statistical designs for three-level control charts

In some situations, an appropriate quality measure uses three or more discrete levels to classify a product characteristic. For these situations, some control charts have been developed based on statistical criteria regardless of economic considerations. In this paper, we develop economic and economic statistical designs (ESD) for 3-level control charts. We apply the cost model proposed by Costa and Rahim.[Economic design of X charts with variable parameters: the Markov chain approach, J Appl Stat 28 (2001), 875–885] Furthermore, we assume that the length of time that the process remains in control is exponentially distributed which allows us to apply the Markov chain approach for developing the cost model. We apply a genetic algorithm to determine the optimal values of model parameters by minimizing the cost function. A numerical example is provided to illustrate the performance of the proposed models and to compare the cost of the pure economic and ESD for three-level control charts. A sensitivity analysis is also conducted in this numerical example.     

Economic and economic statistical design of T 2 control chart with two adaptive sample sizes

The Hotelling's T ² control chart, a direct analogue of the univariate Shewhart X¯ chart, is perhaps the most commonly used tool in industry for simultaneous monitoring of several quality characteristics. Recent studies have shown that using variable sampling size (VSS) schemes results in charts with more statistical power when detecting small to moderate shifts in the process mean vector. In this paper, we build a cost model of a VSS T ² control chart for the economic and economic statistical design using the general model of Lorenzen and Vance [The economic design of control charts: A unified approach, Technometrics 28 (1986), pp. 3–11]. We optimize this model using a genetic algorithm approach. We also study the effects of the costs and operating parameters on the VSS T ² parameters, and show, through an example, the advantage of economic design over statistical design for VSS T ² charts, and measure the economic advantage of VSS sampling versus fixed sample size sampling.     

Phase II Monitoring of Nonlinear Profiles

In many practical cases, the quality of a product or process is characterized by multiple measurements constituting a line or curve that is referred to as a profile. In this article, we develop two approaches for monitoring process and product nonlinear profiles. The first approach consists of control chart methods to monitor nonlinear profiles using parametric estimates of regression model. In order to avoid the problems arising from complexity of coefficient estimation of nonlinear profiles, the second approach, which consists of using metrics to measure deviation from a reference curve, is proposed. The performance of the methods is evaluated through a numerical example using average run length criterion. The effect of sample size on the performance of both approaches is also investigated in this article.     

An integrated model for economic design of chi-square control chart and maintenance planning

Considered process in this article is a two-stage dependent process. Each item in this process has two quality characteristics as x and y while x and y are related to the stage 1 and 2, respectively. Each stage has two operational states as the in-control state and out-of-control state and transition time from the in-control state to the out-of-control state follows a general continues distribution function. The process is monitored using a chi-square control chart. An integrated model that coordinates the decisions related to the economic design of the used control chart and maintenance planning is presented. For the evaluation of the integrated model performance, a stand-alone maintenance model is also presented, and the performance of these two models is compared with each other.     

Estimating process capability index Cpk: classical approach versus Bayesian approach

Process capability index C_pk has been the most popular one used in the manufacturing industry dealing with problems of measuring reproduction capability of processes to enhance product development with very low fraction of defectives. In the manufacturing industry, lower confidence bound (LCB) estimates the minimum process capability providing pivotal information for quality engineers to monitoring the process and assessing process performance for quality assurance. The main objective of this paper is to compare and contrast the LCBs on C_pk using two approaches, Classical method and Bayesian method.     

Phase II statistical process control for functional data

In the manufacturing process, a sequence of measurements of quality characteristic is increasingly taken across some continuum, producing a curve that represents the quality of the item. This curve provides the so-called profile or functional data. Regardless of a linear or nonlinear profile, the common approaches of the control chart are based on the multivariate control chart by monitoring the estimated parameter of the pre-defined linear or nonlinear model. Usually, the model is difficult to know practically, and it is also difficult to identify the abnormal pattern from the outlying parameter. The functional data control chart we propose can provide a better solution to these problems. In the Monte-Carlo simulations, we show that the functional data control chart is sensitive when the underlying process status is changed. By applying the vertical density profile data, the new method exhibits a good performance.     

新常态下地方经济增长质量监测预警的理论与方法

构建新常态下地方经济增长质量监测预警系统,在评价当前经济增长质量的运行状态、准确预测未来经济发展变化趋势的基础上,更侧重于对中国地方经济增长质量进行监测和预警,以及时把控未来经济的变动方向,对地方经济增长质量的提高起到良性指示作用。本文首先给予宏观经济预警系统新的视角,基于经济增长的质量和效益多维度进行监测预警,区别于传统的经济增长速度和数量。其次,明确了经济增长质量监测预警的价值判断和内在机理,对经济增长质量监测预警系统的基本框架做出相应的界定。最后,从经济增长质量的动态监测、趋势预测、识别预警以及政策选择四大模块构建新常态下地方经济增长质量的监测预警系统,提供各模块的方法选择,并以陕西省为例进行演示分析和指数模拟。     

Optimization of design parameters for control charts with multiple assignable causes

Duncan's economic model of Shewhart's original x¯ chart has established its optimal and economic application for processes with the Markovian failure characteristic. As the sample statistics show some indications of process variations, the variable-sampling-interval (VSI) control charts perform more effectively than the fixed sampling interval (FSI) ones due to a higher frequency in the sampling rate. Regarding the economic design of control charts, most studies have been dedicated to the FSI scheme. In 1998, Bai & Lee considered the production process with a single assignable cause and proposed an economic VSI design for a general x¯ control chart. However, in real cases, there are multiple assignable causes in the production process. Therefore, concerning the operation characteristics of the real industry, this research develops an economic model for the VSI control chart with multiple assignable causes based on stochastic and statistics theory and determines the optimal design parameters of the chart. A numerical example is also provided to demonstrate the effectiveness of the proposed model and the result indicates that VSI performs more effectively than a FSI control chart.     

ICT提升中国经济增长质量的机理与效应分析

信息通信技术（ICT）作为新一轮产业革命的核心与通用目的技术，有利于提升经济增长质量，其基本机理是：大规模ICT资本投资、ICT生产部门生产率迅速增长以及ICT对传统产业部门的大规模信息化改造，将显著提升要素生产率，优化产业结构。本文利用增长核算模型和两部门模型，在测算我国ICT生产性资本存量的基础上，对ICT提升我国经济增长质量的效应进行了实证分析。结果表明：1995-2015年，我国ICT资本投入增长迅速且资本深化效应明显，ICT资本对经济总产出的贡献份额呈上升趋势；ICT产业TFP增长率显著高于整体经济平均水平，且对整体经济生产率提升作用逐渐强化；ICT产业对产业结构优化升级的直接带动作用较明显，但溢出效应尚不显著且存在一定的时滞；相较于ICT制造业，软件业对其他产业的溢出效应不明显。为此，应着力提升ICT投资效率，强化ICT核心技术自主创新，进一步深化ICT融合应用，全面提升产业协同创新能力。     

共享经济的统计测度：界定、困境与展望

当前对共享经济的研究集中讨论了这种新经济模式的客观影响,而缺乏如何统计和测度这种新经济模式的思考。本文围绕共享经济的界定与测度,明晰从“共享”到“共享经济”的概念演变,系统整理国内外共享经济的测度体系,分析了传统统计测度理论难以适用于共享经济的原因。随后指出在共享经济背景下,传统经济统计的四类统计困境：①共享经济参与者身份相对模糊。②共享经济统计的行业分类困难。③传统经济统计方法失准。④传统经济数据采集方式低效。由此针对性地提出了改革传统统计调查和经济核算制度等应对措施,试图构建反映共享经济发展和变化的统计指标体系。     

Monitoring correlated processes with binomial marginals

Few approaches for monitoring autocorrelated attribute data have been proposed in the literature. If the marginal process distribution is binomial, then the binomial AR(1) model as a realistic and well-interpretable process model may be adequate. Based on known and newly derived statistical properties of this model, we shall develop approaches to monitor a binomial AR(1) process, and investigate their performance in a simulation study. A case study demonstrates the applicability of the binomial AR(1) model and of the proposed control charts to problems from statistical process control.     

Monitoring and change-point estimation for spline-modeled non-linear profiles in phase II

In some applications of statistical quality control, quality of a process or a product is best characterized by a functional relationship between a response variable and one or more explanatory variables. This relationship is referred to as a profile. In certain cases, the quality of a process or a product is better described by a non-linear profile which does not follow a specific parametric model. In these circumstances, nonparametric approaches with greater flexibility in modeling the complicated profiles are adopted. In this research, the spline smoothing method is used to model a complicated non-linear profile and the Hotelling T² control chart based on the spline coefficients is used to monitor the process. After receiving an out-of-control signal, a maximum likelihood estimator is employed for change point estimation. The simulation studies, which include both global and local shifts, provide appropriate evaluation of the performance of the proposed estimation and monitoring procedure. The results indicate that the proposed method detects large global shifts while it is very sensitive in detecting local shifts.     

Economic design of non parametric sign control chart

An economic design of sign chart to control the median is proposed. Since the sign chart is distribution free, it can easily be applied to any process without prior knowledge of process quality distribution. The effect on loss cost observed for different shifts in location shows that the sign chart performs better for large shifts. The economic statistical performance study reveals that statistical performance of sign chart can be improved sufficiently for moderate shifts in the process. Sensitivity study shows that design is more sensitive for change in values of penalty loss cost and time required for search and repair of an assignable cause.     

An economic statistical design of the Poisson EWMA control charts for monitoring nonconformities

An economic statistical model of the exponentially weighted moving average (EWMA) control chart for the average number of nonconformities in the sample is proposed. The statistical and economic performance of proposed design are evaluated using the average run length (ARL) and the hourly expected cost, respectively. A Markov chain approach is applied to derive expressions for ARL. The cost model is established based on the general cost function given in Lorenzen and Vance [The economic design of control charts: a unified approach. Technometrics. 1986;28:3–11]. An example is provided to illustrate the application of the proposed model. A sensitivity analysis is also carried out to investigate the effects of model parameters on the solution of the economic statistical design by using the design of experiments (DOE) technique.