基于质量损失的过程网络及其关键质量链分析

针对传统的过程能力分析仅以生产线中某一单一的生产工序(过程)为对象这一问题,将影响产品质量的所有生产过程视为一个过程网络,根据Taguchi田口方法,阐述了过程能力指数与质量损失的关系,给出了生产制造过程网络过程能力指数的计算方法.进一步应用PERT/CPM的基本思想,建立了生产制造过程网络关键质量链的规划模型,将质量损失最大的路径视为关键质量链.通过实例分析表明,以上方法改进了传统的统计质量控制和分析方法,能够有效地实现过程网络的质量管理.     

现代质量管理与6σ流程控制

本文以作者在GE和MOTOROLA服务的体会简要介绍近年来6σ质量管理在全球的应用发展情况。随后对Kσ原则下的过程能力指数及不合格品率作了计算和比较,并对有漂移情况下6σ流程控制作了讨论和评价。     

合格品链长控制图

在生产过程中不合格品率(p)很低的情况下,利用两个连续不合格品之间的合格品数(合格品链长)控制图来监督过程不合格品率能克服传统的p图所遇到的困难,为生产者提供产品质量改良的信息。本文研究两种合格品链长(CRL)控制图的制定方法,对这些控制图的效率进行了比较,并说明其实际应用。所研究的CRL控制图特别适用于自动化生产过程的100%检验的质量控制。     

多工序制造过程加工误差的传播分析和控制

多工序制造过程在加工产品质量特征时出现的加工误差存在相互影响,因此为了保障产品的加工质量,定义了误差自修正能力指数来评价多工序制造过程对产品质量特征加工误差的补偿能力,并提出一种偏最小二乘回归方法应用于确定最后一道工序的加工误差与上游工序加工误差之间的关系,从而采取相应的调整措施来减少误差、保证最终的加工质量.     

以AQL和AOQL及以LQL和AOQL为索引的计量一次抽样方案

对拒收批可100%挑选的情况下,使用方用AOQL(平均检出质量上限)作为验收指标制定抽样方案是顺理成章的.但从生产方来说,更喜欢用AQL(可接收质量水平)制定抽样方案,因为如果生产方的交验质量处在AQL,他的产品将以高概率接收.这样,可从AQL和AOQL两个指标设计抽样方案,同时满足生产方与使用方的要求.这种类型的抽样方案,经抽检最后被接收的各批,其不合格品率不是P(交验批的不合格品率)就是0,是不均匀的,但其平均质量最坏也不会超过规定的AOQL.如果要求每批质量不超过某个不合格品率(极限质量水平,LQL),同时要求被最后接收的各批平均质…     

基于差异系数的多元过程能力指数

过程能力指数表示过程能力满足产品质量标准的程度的评价指标，最普遍使用的过程能力指数有Cp、Cpk、Cpm、Cpkm等，它们已在各大工业部门得到了广泛的应用，但是多元质量特性的过程能力指数尚未得到很好的解决。许多学试图以不同的方式、方法计算多元质量特性的过程能力指数，但存在局限性。本以多元正态分布为基础，比较分析了每个质量特征的差异系数，给出了多元过程能力指数的计算公式。最后的一个算例表明，该方法是有效且符合实际的。     

过程能力指数评价过程能力的可靠性影响因素分析

利用过程能力指数评价过程能力,其可靠性程度会受到抽样误差、测量误差以及数据自相关性的影响,分析了观测数据受各种因素影响下过程能力指数估计的统计性质,给出了通过添加纠偏系数获得过程能力指数无偏估计或无偏估计近似值的方法。     

根据子样本的过程能力指数及其置信区间的估计

自1980年以来,分析过程能力的统计方法有显著的进展,已在实践中得到大量应用.过程能力指数是衡量生产过程中的产品尺寸适合规格限和接近目标值的能力.最普遍使用的能力指数是cp和cpk,这些指数曾被广泛地应用于日本、美国和英国的各工业公司和企业.文中对这些指数提出根据子样本估计标准差、能力指数及其置信区间的简单近似方法.     

根据子样本的过程能力指数及其置信区间的估计

自1980年以来, 分析过程能力的统计方法有显著的进展, 已在实践中得到大量应用\bd 过程能力指数是衡量生产过程中的产品尺寸适合规格限和接近目标值的能力. 最普遍使用的能力指数是$c_p$和$c_{pk}$,这些指数曾被广泛地应用于日本、美国和英国的各工业公司和企业. 本文对这些指数提出根据子样本估计标准差、能力指数及其置信区间的简单近似方法     

产品设计与质量控制的动态因素模型(上)

本文介绍产品设计与质量控制的新思想,从产品的设计、生产和使用的角度来研究影响产品质量的所有因素,把它们看成是一个随机过程,提出了动态因素产品设计与质量控制的数学模型。文中把过程能力指数的要领推广到了特性能力指数函数,用于统一地来衡量产品的设计质量、生产质量和使用质量;给出了以特性能力指数函数为变量的产品动态质量损失和产品技术损失的概念,并为组成产品的原材料或零部件达到一致寿命的最经济设计提供了一种理论和方法。     

Decision-making in testing process performance with fuzzy data

Over the years, numerous process capability indices (PCIs) have been proposed to the manufacturing industry to provide numerical measures of process performance. Most research efforts have focused on developing and investigating PCIs that assess process capability by precise measurements of output quality. However, real observations of continuous quantities are not precise numbers; in practice, they are more or less imprecise. Since observations of continuous random variables are imprecise the values of related test statistics become imprecise. Therefore, decision rules for statistical tests have to be adapted to this situation. This article presents a set of confidence intervals that produces triangular fuzzy numbers for the estimation of C_pk index using Buckley’s approach with some modification. Additionally, a three-decision testing rule and step-by-step procedure are developed to assess process performance based on fuzzy critical values and fuzzy p-values. This concept is also illustrated with an example for testing process performance.     

Lot sizing and testing for items with uncertain quality

We consider the problem where items are produced in lots and sold with warranty. Due to manufacturing variability, some items do not conform to the design specifications and their performance is inferior (for example, have higher failure rate). The warranty servicing cost for these is much higher than for those which conform. Two approaches have been advocated for reducing the warranty cost per item released and in both it is achieved at the expense of increased manufacturing cost. The first involves life testing to weed out nonconforming items and the second involves strategies to reduce nonconforming items being produced. In this paper, the authors develop a model which combines both approaches and quality control decisions are made optimally to minimize the total (manufacturing and warranty) cost. It extends the earlier models of the authors which deals with quality decisions based solely on either the first or the second approach.     

Assessing process capability based on Bayesian approach with subsamples

Process capability indices (PCIs) have been widely used to measure the actual process information with respect to the manufacturing specifications, and become the common language for process quality between the customer and the supplier. Most of existing research works for capability testing are based on the traditional frequentist point of view and statistical properties of the estimated PCIs are derived based on the assumption of one single sample. In this paper, we consider the problem of estimating and testing process capability using Bayesian approach based on subsamples collected over time from an in-control process. The posterior probability and the credible interval for the most popular index _Cpk$C_{\mathit{pk}}$ under a non-informative prior are derived. The manufacturers can use the presented approach to perform capability testing and determine whether their processes are capable of reproducing product items satisfying customers’ stringent quality requirements when a daily-based or weekly-based production control plan is implemented for monitoring process stability.     

A compound control chart for monitoring and controlling high quality processes

In the present article, we propose a new control chart for monitoring high quality processes. More specifically, we suggest declaring the monitored process out of control, by exploiting a compound rule couching on the number of conforming units observed between the (i − 1)th and the ith nonconforming item and the number of conforming items observed between the (i − 2)th and the ith nonconforming item. Our numerical experimentation demonstrates that the proposed control chart, in most of the cases, exhibits a better (or at least equivalent) performance than its competitors.     

Inventory models for imperfect quality items with shortages and learning in inspection

The classical economic order quantity model, although well known and useful; assumes that all items received conform to quality characteristics. However, in practice, items may be damaged due to transportation and/or production conditions. This requires a buyer to screen each lot it receives from its vendor to separate the good from the nonconforming (due to imperfect quality) items. While screening is usually a manual task performed by inspectors, it may improve with learning. Besides, it was observed in some studies that coordinating activities (e.g., quality) between a buyer and a vendor may be subject to learning effects and results in improving the quality of each lot (as it contains less nonconforming items) delivered or produced.     

最优过程均值和生产运行长度的确定

实际生产中,过程均值由于受到随机振荡的影响,经常从受控状态逐渐漂移到失控状态,从而导致大量不合格品的出现.针对这种情况,本文假定随机振荡次数服从泊松过程,每次振荡引起过程均值漂移相互独立且服从同一指数分布,结合不对称田口质量损失函数,建立了最佳初始过程均值的经济模型,并讨论了最优生产运行长度的确定.通过与初始过程均值设置在目标值处的情形比较,说明本文模型对降低生产成本的有效性。灵敏度分析表明了各参数对最优过程均值和生产运行长度的影响.     

基于合格品率及返工有效率的计划投产量决策

在订单式生产人工作业系统(MTO/MOS)中,产品的质量和工人技能水平、工作态度、工作状态及激励、惩罚机制等密切相关.当遇到紧急插单、设备故障、工人流失等扰动时,产品的质量易受影响,使得产品合格率变动程度较大.为了满足订单需求,控制成本,须对不合格品进行返工.由于生产系统人员或设备的随机扰动性,使得返工有效率也有一定的变动范围.考虑当合格品率服从连续随机分布及返工有效率服从离散随机分布时,如何进行计划投产量建模及优化决策.应用上述模型于企业实践,验证了该模型的有效性,通过数据分析,得出了具有应用价值的有关规律,并对有关参数的变化进行敏感性分析.结论表明,为了使成本损失尽可能小,须加强有关成本控制,尽可能减少生产过程和返工过程的随机扰动性,提高合格品率及返工有效率.     

Economic lot scheduling problem with imperfect production processes

In this paper, we model the effects of imperfect production processes on the economic lot scheduling problem (ELSP). It is assumed that the production facility starts in the in-control state producing items of high or perfect quality. However the facility may deteriorate with time and shifts at a random time to an out of control state and begins to produce nonconforming items. A mathematical model is developed for ELSP taking into account the effect of imperfect quality and process restoration. Numerical examples are presented to illustrate important issues related to the developed model.     

高质量过程控制技术的比较研究与分析

随着质量改进活动的不断开展,现代制造过程中的不合格项在逐渐降低。在这种情况下,常规的休哈特型计数控制图往往是失效的。为了监控高质量的过程运行,一种方法是采用累计合格品计数(CCC)图;另一种方法是采用几何Q图,本文首先分析了这两种控制图的基本原理;进而以平均链长(ARL)和探测过程发生漂移的概率为准则,系统分析和比较了这两种控制图的性能,仿真结果表明,在大多数情况下,这两种控制图具有相似的性能;最后,通过实例说明了这两种控制图的应用,并给出了若干建议。     

基于非协调元的区域分解法──强重迭情形

基于非协调元的区域分解法──强重迭情形黄建国（上海交通大学应用数学系）ＡＤＯＭＡＩＮＤＥＣＯＭＰＯＳＩＴＩＯＮＭＥＴＨＯＤＦＯＲＮＯＮＣＯＮＦＯＲＭＩＮＧＦＩＮＩＴＥＥＬＥＭＥＮＴ──ＴＨＥＣＡＳＥＯＦＳＴＲＯＮＧＯＶＥＲＬＡＰ￥ＨｕａｎｇＪｉａｎ...