基本过程能力指数的分析与应用问题研究

介绍了几个基本过程能力指数的定义、概念,对其特性和应用范围作了较为全面的分析和解释,并针对实际应用中的几个主要问题进行了论述,旨在为建立计算机系统数据模型提供清晰的指数定义支持,为质量管理人员进行过程能力分析和评价提供专业指导。     

过程能力分析在压缩机密封圈加工质量控制中的应用

为了保证大批量零件加工的产品质量合格率满足客户的要求,通过Ppk （过程性能指数）计算来评估初始加工过程能力,结果表明初始工序的过程能力不足。经因果分析,采取了相应的整改措施。落实改进措施后,在稳定状态下,取样所加工的统计数据,运用MINITAB软件,绘制了控制图、过程能力图,并进行了过程能力指数Cp ,Cpk （短期）与过程性能指数Pp ,Ppk （长期）计算和分析。最后根据客户反馈的质量数据确定了加工过程的工序能力水平与状态,使其工序能力满足客户的要求。     

过程能力分析中的过程稳定性及指数估计

在过程能力分析中通常采用子样级差或样本总体标准差来估计总体标准差。实际生产中的一些过程由于刀具磨损等系统原因导致周期性变化,很难处于统计过程控制。定义此类过程是长期稳定过程,通过建立数学模型,比较两种过程能力指数的估计方法,分析产生的原因并进行仿真研究。     

过程稳定性与过程能力指数的估计

过程能力分析(PCA)是质量统计技术的重要组成部分,也是六西格玛管理的标准工具.过程能力指数(PCI)是过程能力分析的结果,我国工业企业常称其为工序能力指数Cp.     

过程能力指数Cpk与过程性能指数Ppk

对汽车零部件制造行业而言, 进入WTO就意味着全球化采购时代的到来, 产品制造过程的控制越来越重要, 从而引起了对过程能力研究的高度重视。QS 9000五大技术手册之一的《产品质量先期策划及控制计划(APQP&CP)》要求在APQP的第三阶段(过程设计和开发) 制定初始过程能力研究计划, 在第四阶段 (产品过程确认) 予以实施。我们过去经常接触的是过程能力指数Cpk, 对QS 9000中提出的初始过程能力指数Ppk (也称过程性能指数 ) 这个概念, 还比较模糊, 有必要做认真的探讨。要了解过程能力指数Cpk和过程性能指数Ppk的差异, 首先应了解过…     

过程能力指数的评价与改进策略

通过对过程能力指数的简单介绍,阐明了对过程能力指数的评价原则及过程能力指数对产品合格率的影响,并制定了改进策略,从而保证产品质量。     

正交实验及过程能力指数在偏光片磨边机中的应用

文章介绍了正交实验法和过程能力指数(CPK)的实际应用,用正交实验法试验出了设备的切削参数;在设备的验证上,采用过程能力指数CPK进行了考验,提高了设备工作的稳定性.     

多变量过程能力分析在射孔弹头加工中的应用

零件加工过程的过程能力分析是明确过程改进方向和目标的重要环节,过程能力指数是进行过程能力分析的量化工具。目前对于单质量特性的过程能力指数研究较多,而对于多质量特性的过程能力指数相对较少。射孔弹头精加工过程的各工序会形成多个质量特性,因此本文以Boyles提出的与成品率对应的为基础,建立多质量特性过程能力指数和分析图,通过实例分析指出改进方向。     

几种典型过程能力指数的比较

针对实际生产过程质量评价中过程能力指数选用问题，基于所依据的质量损失函数，分析比较了Taguchi过程能力指数和传统过程能力指数的特性和异同，提出了指数选用与组织的长期和短期质量目标的关系。并建立了不同过程能力指数与合格率的函数对应关系。     

基于主成分分析的改进多元质量特性过程能力指数

目前多元质量特性的过程能力指数主要通过过程产出的不合格品率、基于一元过程能力指数的概念推广、基于质量损失函数和各种综合评价技术来进行研究,但多元问题的复杂性增加了多元过程能力指数计算的困难度,难以为实践提供便利和参考。提出一种基于主成分分析的改进多元过程能力指数,以评价涉及多元质量特性产品的生产过程能力,该方法将最初的质量特性变量转化为标准正态分布变量,基于Taam指数和主成分分析方法,构建了改进的多元过程能力指数,并给出了其统计特性,比如置信区间和最低置信限,以帮助工程师更好地了解其统计意义。采用一个制造过程案例和仿真案例证明所提出过程能力指数的有效性,并给出在制造过程中使用该方法的具体实施流程。实例证明该方法计算更加简单,有效可行,有利于在生产实际中应用。所做研究为多元过程能力指数计算提供了一种新方法。     

The study of cost-tolerance model by incorporating process capability index into product lifecycle cost

To reduce the cost of manufacturing systems, many studies of cost minimization have been performed. Since tolerance design significantly affects the manufacturers’ cost, the optimization of cost-tolerance allocation will be an important issue for reducing these costs. Costs incurred in a product life-cycle include manufacturing cost and quality loss. However, most cost-tolerance optimization models frequently ignore the concept of quality loss and may not lead to an accurate analysis of the tolerance. Until now, process capability analysis has been the tool used to evaluate the adequacy of a production tool in meeting a quality target. Hence, the concept of process capability analysis should be included into the cost-tolerance optimization model. In this study, a flexible cost-tolerance optimization model will be constructed by integrating the process capability index into the product life-cycle cost function. The constructed cost-tolerance optimization model simultaneously considers the manufacturing cost of the components, the process capability of the manufacturing operations, and the quality loss of products. The decision-maker can apply the proposed cost-tolerance optimization model to determine a reasonable tolerance with minimum total cost including consideration of the process capability .     

Measuring process yield based on the capability index Cpm

Process capability indices C_p, C_a, C_pk and C_pm have been proposed to the manufacturing industry as capability measures based on various criteria including variation, departure, yield, and loss. It has been noted in recent quality research and capability analysis literature that both the C_pk and C_pm indices provide the same lower bounds on process yield, that is, Yield2(3C_pk)-1=2(3C_pm)-1. In this paper, we investigate the behaviour of the actual process yield in terms of the number of nonconformities (in ppm) for processes with a fixed index value of C_pk=C_pm, but with different degrees of process centring, which can be expressed as a function of the capability index C_a. The results illustrate that it is advantageous to use the index C_pm over the index C_pk when measuring process capability, since C_pm provides better customer protection. This revised version was published online in October 2004 with a correction to the issue number.     

A process capability index for simple linear profile

In some cases, the quality of a process or a product is characterized by a linear regression model which is also called a linear profile. Process capability index is an important concept in statistical quality control and measures the ability of a process to manufacture products that meet certain specifications. There has been little attempt to study the process capability in linear profiles. In this paper, two methods are proposed for measuring the process capability in simple linear profiles. The first method uses the percentage of nonconforming parts produced at each level of the independent variable to introduce a process capability index. The second method is a multivariate process capability approach where a vector of three components is introduced. The components of the vector assess the process dispersion, its centrality, and its location within the upper and the lower specification limits. In comparison to the only existing method, numerical analysis based on simulation studies indicates that the suggested process capability measurements perform more accurately in evaluating the capability of a process generating a simple linear profile. When the error term variance is 1 and the actual percentage of nonconformities is 0.11 %, the proposed method estimates 0.11 % nonconforming percentage and a capability index of 1.06. While the existing method results in 0.27 % nonconforming percentage and a capability index of 0.9, the existing method underestimates the process capability.     

Incorporating process capability index and quality loss function into analyzing the process capability for qualitative data

Process capability analysis (PCA) is frequently employed to evaluate a product or a process if it can meet the customer’s requirement. In general, process capability analysis can be represented by using the process capability index (PCI). Until now, the PCI was frequently used for processes with quantitative characteristics. However, for process quality with the qualitative characteristic, the data’s type and single specification caused limitations of using the PCI. When the product can not meet the target, even if it lies in the specified range, it should lead to the corresponding quality loss. Taguchi developed a quadratic quality loss function (QLF) to address such issues. In this study, we intend to construct a measurable index which incorporates the PCI philosophy and QLF concept to analyze the process capability with the consideration of the qualitative response data. The manufacturers can not only employ the proposed index to self-assess the process capability, but they also can make comparisons with the other competitors .     

Modified multivariate process capability index using principal component analysis

The existing research of process capability indices of multiple quality characteristics mainly focuses on nonconforming of process output, the concept development of tmivariate process capability indices, quality loss function and various comprehensive evaluation methods. The multivariate complexity increases the computation difficulty of multivariate process capability indices（MPCI）, which makes them hard to be used in practice. In this paper, a new PCA-based MPCI approach is proposed to assess the production capability of the processes that involve multiple product quality characteristics. This approach first transforms the original quality variables into standardized normal variables. MPCI measures are then provided based on the Taam index. Moreover, the statistical properties of these MPCIs, such as confidence intervals and lower confidence bound, are given to let the practitioners understand the capability indices as random variables instead of deterministic variables. A real manufacturing data set and a synthetic data set are used to demonstrate the effectiveness of the proposed method. An implementation procedure is also provided for quality engineers to apply our MPCI approach in their manufacturing processes. The case studies demonstrate the effectiveness and feasibility of this new kind of MPCI, which is easier to be used in production practice. The proposed research provides a novel approach of MPCI calculation.     

西格玛水平与过程能力指数关系模型探讨

通过对质量特性过程的波动和概率分布的研究,结合对不合格品率的系统分析,给出西格玛水平和过程能力指数的详细计算方法,建立西格玛水平、过程能力指数及不合格品率之间的联系,拓展六西格玛管理的研究内容,给企业管理层提供了质量评价决策依据.     

车间级产品加工质量控制的研究

质量控制一直是企业追求的目标,车间产品加工质量的控制又是企业质量控制的关键。在分析影响车间产品加工质量的因素的基础上,根据车间产品加工质量控制的内容,提出了控制车间产品加工质量的途径。     

Robust design of railway vehicle suspension using a process capability index

Robust design for the primary suspension of a railway vehicle was performed according to the optimization of 10 dynamic responses representing driving safety and ride comfort, in which response surface models (RSMs) from the design of experiments (DOEs) were applied. To evaluate the probabilistic feasibility of robustness, an intensive computational process is mandatory. In the present study, the authors utilized the first-order Taylor series expansion to reduce the computational burden associated with a probabilistic feasibility evaluation, thus easily obtaining both an individual mean and variance of constraints. To overcome the difficulty of optimizing the mean and probabilistic variances for the 10 dynamic responses, a process capability index (C_pk) was introduced, which shows the mean value and scattering of the product quality to a certain extent and normalizes the objective functions irrespective of varying dimensions. Consequently, the robust design to optimize the 10 dynamic responses minimized the C_pk subjected to the constraint of C_pk ≥ 2, which satisfied 6σ. The proposed method improved the C_pk that violated the constraints obtained by the RSMs from DOEs and minimized the variance of the C_pk.     

Variable sampling plan for resubmitted lots based on process capability index and Bayesian approach

Acceptance sampling plans are applied for quality inspection of products. Among the design approaches of sampling plan, the most important one is to use process capability indices in order to improve the quality of manufacturing processes and the quality inspection of products. But, selection of estimators of process capability index and their sampling distribution is very important. Bayesian statistical technique can be used to obtain the sampling distribution. In this paper, a variable sampling plan is developed for resubmitted lots based on process capability index and Bayesian approach. In the proposed sampling plan, lots are inspected several times depending on the quality level of the process. In addition, this paper presents an optimization model for determining the decision parameters of developed sampling plan with regards to the constraints related to the risk of consumer and producer. Two comparison studied have been done including: First, the methods of double sapling plan (DSP), multiple dependent state (MDS) sampling plan, and repetitive group sampling (RGS) plan are elaborated, and also in order to comparing developed sampling plans, an expected number of products as average sample number (ASN) is used for different developed plans; second, a comparison study between Bayesian approach and exact probability distribution is carried out and their results are analyzed. It is observed that the ASN values of MDS sampling plan is less than ASN values of other methods, and also the ASN values of different variable sampling plans based on Bayesian approach is less than ASN values obtained using exact approach.