基于文献计量学的技术成熟度研究及实证分析

企业对技术成熟度的研究与评价可以有效控制其技术研发的风险.文章在梳理已有技术成熟度的评价方法的基础上,提出了采用基于文献计量学方法来分析技术成熟度,包括期刊与会议论文比例法、文献类型变换法和Fisher-Pry模型法,并以城市污水处理系统的智能控制技术为例,时其进行技术成熟度实证分析,为技术成熟度评价提供了一种思路.     

在质量体系中正确运用统计技术应解决的几个问题

统计技术是指企业在质量体系的建立与运行过程中 ,通过恰当选择和正确使用统计方法 ,进行质量分析、质量控制与质量改进等活动 ,科学有效地达到描述统计与推断统计的应用技巧 ,以保持或改善产品质量、工程质量或服务质量。它在企业应用范围非常广泛 ,是一种投资少、见效快、简便易行的深化企业质量管理的有效技术。一、选择适宜的统计技术要想运用好统计 ,让统计技术在生产过程、体系运行中真正发挥作用 ,首先必须选择适宜的统计技术 ,统计技术选择不适宜 ,可操作性不强 ,作用不明显等都将会给统计技术的正确运用带来巨大的阻力。选择适宜的…     

健康保险与财产保险的定价比较

面对日益开放的团险和健康险市场,不仅要从经营风险,筹资渠道等方面加强管理,还要从技术层面上寻求健康保险市场的长期发展.健康保险以发病率为依据而非以死亡率为依据,风险控制难度大,专业技术要求高,因此与人寿保险在定价上有不同之处,其费率厘定的原理与财产保险相似.本文对健康保险与财产保险的费率厘定方法进行比较分析.     

数字化转型、内部控制与股票流动性

文章基于2016—2020年我国沪深两市A股上市公司数据，采用文本分析技术，以股票流动性作为资本市场的考量指标，分析我国企业数字化转型对资本市场的影响，并以内部控制质量作为中介变量，检验其作用机理与路径机制。研究结果表明，企业数字化转型为资本市场释放了利好信息，能提高股票流动性，该结论经过稳健性检验后依然成立。路径分析结果显示，企业数字化转型通过提高内部控制质量提高了股票流动性。     

试论统计信息公开制度的完善

一、建立完善统计信息公开制度的必要性分析 国家机构由于职能与工作的需要,收集、积累、占有、控制着大量的信息资源,这些信息资源对国民经济的建设有着重要的作用.信息如同货币一样,流动性越强,其价值也就越能得到体现.如果这些信息资源能为社会充分利用,将会大大降低社会经济运作的风险与盲目性,提高社会经济运作的质量,产生巨大的经济效益.现代社会网络技术的发展,更为信息的流动提供了坚实的技术基础.     

基于网络技术的抽样调查设计与实施研究

文章分析了基于网络技术的抽样调查设计过程中应该注意的问题,以及基于网络技术的城镇居民收入调查方案的设计构想.文章讨论了网络调查设计中怎样选用具体的调查方式,怎样进行问卷设计,以及控制网络调查的质量和提高样本的代表性问题;分析了城镇居民收入调查实施过程中应该怎样选择网络调查方法,提出了一个网络调查的基本方案,认为调查实施过程中必须采用传统调查与网络调查相结合的方法.     

数据质量控制与评估办法

数据质量控制与评估办法数据质量是统计工作的生命，数据质量控制与评估应该说贯穿于整个统计工作过程。一、统计数据质量控制与评估的必要性和迫切性二、统计数据质量控制与评估的几种方法（一）比较分析法（二）调查验证法（三）专家论证法三、市县级统计部门关于数据质...     

工程投资审计的技术方法探讨

审计的技术方法是指收集审计证据时应用的技术手段。审计人员在审计过程中可以采用检查、监盘、观察、查询及函证、计算和分析性复核等技术方法，获取审计证据。检查是审计人员对会计记录和其他书面文件可靠程度的审阅与核对；监盘是审计人员现场监督被审计单位各种实物资产及现金、有价证券等的盘点，并进行适当的抽查；观察地审计人员对被审计单位的经营场所、实物资产和有业务活动及其内部控制的执行情况等所进行的实地察看。     

钢铁产业技术进步与产能过剩关系的实证分析

文章以2005-2015年45家钢铁上市公司的相关数据为基础,运用存货变动率来衡量企业产能过剩的状况,运用全要素生产率来衡量钢铁上市公司的技术进步情况,实证分析了我国钢铁产业技术进步与产能过剩的关系.研究发现:我国钢铁产业技术进步确实对降低产能过剩有相当程度的影响,加速技术进步是从根本上缓解我国钢铁产业产能过剩状况的一条途径;与此同时,各钢铁公司应将其固定资产扩张率与资产负债率控制在合理的范围内,因为企业的固定资产扩张率和资产负债率对我国钢铁产业的产能过剩状况也有较大影响.     

基于约束最优化理论的企业生产成本控制方法

在既定的市场供求结构下,控制自身的成本是厂商维持和扩大利润的主要方法.厂商对生产成本的控制受到技术条件和计划产量的限制.文章以数理经济学的角度,使用约束最优化工具,探讨成本控制问题.从动态和静态两个角度,分别分析静态条件下的要素投入量控制和投入参数控制的方法,以及动态条件下的要素组合调整时间节点选择方法.     

关于单变量统计过程控制图某些研究结果简介

文章仅对一元连续变量的静态与动态控制图研究现状进行了简单的总结和介绍,并给出了较详细的参考文献,希望为国内开展此方向的研究抛砖引玉。     

A binomial CUSUM chart for detecting large shifts in fraction nonconforming

This article studies a unique feature of the binomial CUSUM chart in which the difference (d _t ?d ₀) is replaced by (d _t ?d ₀)² in the formulation of the cumulative sum C _t (where d _t and d ₀ are the actual and in-control numbers of nonconforming units, respectively, in a sample). Performance studies are reported and the results reveal that this new feature is able to increase the detection effectiveness when fraction nonconforming p becomes three to four times as large as the in-control value p ₀. The design of the new binomial CUSUM chart is presented along with the calculation of the in-control and out-of-control Average Run Lengths (ARL₀ and ARL₁).     

The extended GWMA control chart

This study extends the generally weighted moving average (GWMA) control chart by imitating the double exponentially weighted moving average (DEWMA) technique. The proposed chart is called the double generally weighted moving average (DGWMA) control chart. Simulation is employed to evaluate the average run length characteristics of the GWMA, DEWMA and DGWMA control charts. An extensive comparison of these control charts reveals that the DGWMA control chart with time-varying control limits is more sensitive than the GWMA and the DEWMA control charts for detecting medium shifts in the mean of a process when the shifts are between 0.5 and 1.5 standard deviations. Additionally, the GWMA control chart performs better when the mean shifts are below the 0.5 standard deviation, and the DEWMA control performs better when the mean shifts are above the 1.5 standard deviation. The design of the DGWMA control chart is also discussed.     

Maximum Chi-Square Generally Weighted Moving Average Control Chart for Monitoring Process Mean and Variability

In this article, we propose a new control chart called the maximum chi-square generally weighted moving average (MCSGWMA) control chart. This control chart can effectively combine two generally weighted moving average (GWMA) control charts into a single one and can detect both increases as well as decreases in the process mean and/or variability simultaneously. The average run length (ARL) characteristics of the MCSGWMA and maximum exponentially weighted moving average (MaxEWMA) charts are evaluated by performing computer simulations. The comparison of the ARLs shows that the MCSGWMA control chart performs better than the MaxEWMA control chart.     

An NP Control Chart Using Double Inspections

The np control chart is used widely in Statistical Process Control (SPC) for attributes. It is difficult to design an np chart that simultaneously satisfies a requirement on false alarm rate and has high detection effectiveness. This is mainly because one is often unable to make the in-control Average Run Length ARL₀ of an np chart close to a specified or desired value. This article proposes a new np control chart which is able to overcome the problems suffered by the conventional np chart. It is called the Double Inspection (DI) np chart, because it uses a double inspection scheme to decide the process status (in control or out of control). The first inspection decides the process status according to the number of non-conforming units found in a sample; and the second inspection makes a decision based on the location of a particular non-conforming unit in the sample. The double inspection scheme makes the in-control ARL₀ very close to a specified value and the out-of-control Average Run Length ARL₁ quite small. As a result, the requirement on a false alarm rate is satisfied and the detection effectiveness also achieves a high level. Moreover, the DI np chart retains the operational simplicity of the np chart to a large degree and achieves the performance improvement without requiring extra inspection (testing whether a unit is conforming or not).     

The RL2 chart versus the np chart for detecting upward shifts in fraction defective

The use of the np chart for monitoring fraction-defective is well-established, but there are a number of relatively simple alternatives based on run-lengths of conforming items. Here, the RL₂ chart, based on the moving sum of two successive conforming run-lengths, is investigated in order to provide SPC practitioners with clear-cut guidance on the comparative performance of these competing charts. Both sampling inspection and 100% inspection are considered here, and it is shown that the RL₂ chart can often be considerably more efficient than the np chart, but the comparative performance depends on the false-alarm rate used for the comparison. Graphs to aid parameter-choice for the RL₂ chart are also provided.     

The effect of autocorrelation on the retrospective X-chart

Quality control chart interpretation is usually based on the assumption that successive observations are independent over time. In this article we show the effect of autocorrelation on the retrospective Shewhart chart for individuals, often referred to as the X-chart, with the control limits based on moving ranges. It is shown that the presence of positive first lag autocorrelation results in an increased number of false alarms from the control chart. Negative first lag autocorrelation can result in unnecessarily wide control limits such that significant shifts in the process mean may go undetected. We use first-order autoregressive and first-order moving average models in our simulation of small samples of autocorrelated data.     

A combined control scheme for monitoring the frequency and size of an attribute event

A traffic accident can be considered as an example of the attribute events, and the number of the injured in each accident is called the event size. Some control charts have been developed for monitoring either the time interval (T) between the occurrences of an event or the event size (C) in each occurrence. This article studies the statistical monitoring of the attribute events in which T and C are monitored simultaneously and C is an integer. Essentially, it integrates a T chart and a C chart, and is therefore referred to as a T&C scheme. Our studies show that the new chart is more effective than an individual T chart or C chart for detecting the out-of-control status of the event, in particular for detecting downward shifts (sparse occurrence and/or small size). Another desirable feature of the T&C scheme is that its detection effectiveness is more invariable against different types of shifts (i.e. T shift, C shift and joint shift in T&C) compared with an individual T or C chart. The improvement in performance is achieved due to the simultaneous monitoring of T and C. The T&C scheme can be applied in manufacturing systems and especially in non-manufacturing sectors (e.g. supply chain management, health care industry, disaster management and security control).     

Grey Predictive Process Control Charts

The present article intends to develop some imputation methods to reduce the impact of non response at both the occasions in two-occasion successive (rotation) sampling. Utilizing the auxiliary information, which is only available at the current occasion, estimators have been proposed for estimating the population mean at the current occasion. Estimators for the current occasion are also derived as a particular case when there is non response either on the first occasion or second occasion. Behaviors of the proposed estimators are studied and their respective optimum replacement policies are also discussed. To study the effectiveness of the suggested imputation methods, performances of the proposed estimators are compared in two different situations, with and without non response. The results obtained are demonstrated with the help of empirical studies.     

Investigation of the diesel consumption for trucks at an overburden stripping area by SPC study

This study examined whether diesel consumption used by trucks at a stripping area is controlled or not. The factors affecting diesel consumption were also investigated and some necessary solutions were presented. Diesel consumption was observed with the aid of control graphs. Abnormal situations in the diesel consumption were explored by means of Shewhart control graphs. The factors which are out of control were also presented in a cause–effect diagram, and suggestions for improvement were proposed. It has been determined that the main effect of the diesel consumption is the daily run number of the trucks. The main factors affecting the daily run number were also investigated.