非正态过程能力指数估计及抽样方案设计

在实际生产中许多稳定的加工过程不一定满足正态性假设，使得传统的过程能力指数度量失准。为此介绍总结了若干种数据转换方式，将质量特性的分布映射为正态形式，在此基础上再计算过程能力指数。讨论了过程能力指数置信下限与抽样容量、批量产品不合格率之间的对应关系，并给出了非正态分布条件下加工过程抽样方案的设计流程。以某曲轴加工过程为例给出案例分析。     

质量和成本约束下CSP-T和Spk集成过程控制方案

多水平连续抽样检验方案(CSP-T)是在线过程质量控制工具，但该方案的第一类风险和第二类风险都较高，且不能满足成本约束。提出了CSP-T和过程良率指数(S_pk)集成过程控制方案，该集成方案在满足质量约束的同时，以最小成本运行，并将两类风险控制在既定水平。建立了极限检验能力下的最优CSP-T方案，依据数据的计数特征驱动质量控制方案运行。基于S_pk估计的精确分布建立了风险控制方案，依据数据的计量特征驱动风险控制方案运行。质量控制方案和风险控制方案是独立互补关系。相比于CSP-T方案，检验工作量没有增加。企业案例验证了集成控制方案的可行性和有效性。     

基于成本控制的小批量生产工序能力指数研究

传统的工序能力指数分析方法仅仅从统计质量管理的角度对过程能力进行分析,而忽略了所加工产品的不同批量、不同价值、不同加工工序成本的影响。对国内外多品种、小批量的工序能力指数研究现状进行了回顾,在对工序能力指数的点估计及置信区间进行分析的基础上,提出了基于成本控制的多品种、小批量生产方式下确定工序能力指数的方法,从而达到降低生产加工过程成本的目的。     

计数型抽样方案在成品检验中的应用

本文详述了计数型抽样方案在直柄麻花钻成品检验中的应用情况，通过使用一个由接收质量限（AQL）确定的系统抽样方案，可将通过产品的平均不合格品率控制在事先规定的接收质量限（AQL）值下，达到控制产品质量的目的。     

产品质量抽样检验的两种风险分析

本文阐述了产品质量抽样检验中两种风险意义、数值计算方法及抽样方案中3个参数变化对它们的影响规律,对制定产品质量抽样检验方案有理论指导意义。     

工序能力分析与评价中的几个问题

在工序质量分析与控制中,计算与评价工序能力指数是一项非常重要的工作,也是计算机辅助质量系统的一个重要模块。文章针对目前在工序能力计算与分析中出现的问题,提出了如何合理地进行抽样、样本数据的正态性检验以及对非正态性数据的处理、Ｃｐ的置信区间以及与样本含量的关系,旨在为实际生产过程中质量工程师进行工序能力分析和评价提供指导。     

自制压孔心轴解决零件超差问题

轴承成品工作表面一般应尽可能不切削加工。因内孔精度高,压装后的零件受到基孔尺寸和铜套尺寸的影响,铜套尺寸检测麻烦,且为破坏性检验,只能做一定比例的抽样检验,对最终尺寸超差的零件目前没有较好的控制方法。压孔心轴的制作在工艺上增加压孔工序,解决了成品零件超差（内孔尺寸小）的问题,同时弥补了铜套的抽样风险,较好地保证了产品质量。     

基于不完美检验的验收抽样方案经济设计

为降低抽样方案造成的风险及损失，利用误检概率和批产品不合格品率的先验分布，计算了生产方和使用方风险的后验概率。在综合考虑抽检成本、复检成本、误判损失的基础上，构建了一个基于不完美检验的整数非线性规划经济模型，提出了最佳抽样方案，并与无检验错误的抽样方案进行了比较。最后，讨论了模型参数对抽样方案和两类风险的影响。结果表明，在不合格品率较小时，有检验错误的平均检验量相对较大；两者的平均检出质量非常接近，但平均检出质量上限相较无检验错误时略低。     

正态过程质量控制CSP-V检验方案的重新设计

正态过程已成为加工制造业生产和装配工序加工数据的主要分布形式。放宽连续抽样检验方案(CSP-V)在方案的制定和选择阶段,都没有考虑正态过程的稳定性特征,导致单一过程输出质量不稳定和多个并行过程输出质量不一致。提出一种面向正态过程重新设计CSP-V检验方案的新方法,称为最优CSP-V边界方案(OCSP-V)。OCSP-V根据过程合格品率估计建立检验方案,利用过程合格品率估计的置信下限调整检验方案,保障单一过程和多个并行过程输出质量稳定一致。建立了边界恒等式和等值面恒等式求解方案参数。分析了OCSP-V方案的优势。为方便应用,给出三种不同质量需求下各类正态过程的OCSP-V方案。企业案例有效验证了新方案的优势。     

基于采购产品抽样检验方案选用的研究

根据某企业采购产品进货检验使用抽样检验的情况,来阐述批量产品采购时可选用的抽样检验方案以及方案的科学性和经济性,以降低使用方质量风险,提高检验效率。     

Designing two mixed quick switching sampling plans for linear profiles

This study compares two proposed mixed quick switching sampling (QSS) plans for linear profiles as the quality characteristic. For the QSS plans, we recommend a binomial attribute plan for normal inspection and then a variable sampling plan for tightened inspection based on capability index C_puA of linear profiles with one-sided specifications. The difference between the two proposed QSS plans is in the tightened inspection. Tightened inspection of the first proposed plan is a single sampling using C_puA index, but tightened inspection of the second plan is a multiple dependent state repetitive (MDSR) plan based on C_puA index. The optimal parameters are obtained by nonlinear optimization. Simulation study for selecting parameters is conducted with various combinations of specified acceptable quality level (AQL), limited quality level (LQL), producer's risk, and consumer's risk. Simulation results confirm that the second proposed QSS plan which applies variable MDSR at tightened inspection performs better than another proposed plan. Hence, the approach of the second proposed plan is demonstrated in an illustrative example.     

A resubmitted sampling scheme by variables inspection for controlling lot fraction nonconforming

The paper attempts to develop a resubmitted sampling scheme by variables inspection for controlling lot fraction nonconforming when the quality characteristic follows a normal distribution and has two-sided specification limits. In this paper, the plan parameters are determined by the classical two-point condition on the operating characteristic curve, which will satisfy the quality requirements and allowable risks by the producer and the consumer simultaneously. The behaviour of the proposed sampling plan is discussed and compared with the conventional single sampling plan by variables. The proposed plan requires smaller sample size for inspection with the same protection to the producer and the consumer especially when the quality of the submitted lot is good enough. Tables of the plan parameters under several selected quality requirements and risks are provided for practical applications, and the operating procedure is also presented and illustrated with an example.     

A quick switching sampling system by variables for controlling lot fraction nonconforming

This article develops a new sampling scheme by variables inspection, namely a quick switching sampling (QSS) system based on the process yield index for lot determination when the quality characteristic is normally distributed with two specification limits. The QSS system can provide a flexible sampling procedure by switching decision policies, normal inspection and tightened inspection. The operating characteristic curve of the proposed QSS system is derived and required to pass through two designed points, acceptable quality level and limiting quality level for satisfying risks simultaneously suffered by the producer and the consumer. The proposed sampling system’s performance is investigated and a comparison with the conventional variables single sampling (VSS) plan is also examined. The results indicate that the proposed system outperforms the VSS plan by requiring a smaller sample size for inspection while retaining the same protection. For practical purposes, the plan parameters’ tables are provided on the basis of various selected quality requirements and risks. Finally, we demonstrate the proposed sampling system using an example taken from a silicone LED lens industry.     

A lots-dependent variables sampling plan considering supplier’s process loss and buyer’s stipulated specifications requirement

A well-established scheme and mechanism for deciding product acceptance is perceived as a win-win situation for the long-term supplier–buyer relationship. In this paper, we develop a lots-dependent variables sampling scheme for product acceptance determination. The dependent state is based on the sample information of the process capability index that incorporates the supplier’s process loss and the buyer’s demanded specifications requirement. This main scheme is implemented by a three-rule process that accepts or rejects a related lot conditional on the sample results of past lots. The plan-operational parameters satisfying the desired quality levels and constraining the supplier–buyer risks are determined by a non-linear optimisation model. In performance comparisons, our proposed plan demonstrated higher cost effectiveness and discriminatory power than the traditional variables single sampling plan. Finally, industrial applicability of our recommended sampling plans was investigated in a case study.     

Developing a variables multiple dependent state sampling plan with simultaneous consideration of process yield and quality loss

Acceptance sampling plans have been utilised predominantly for the inspection of outgoing and incoming lots; these plans provide effective rules to vendors and buyers for making decisions on product acceptance or rejection. Multiple dependent state (MDS) sampling plans have been developed for lot sentencing and are shown to be more efficient than traditional single sampling plans. The decision criteria of MDS sampling plans are based on sample information not only from the current lot but also from preceding lots. In this study, we develop a variables MDS sampling plan for lot sentencing based on the advanced process capability index, which was developed by combining the merits of the yield-based index and loss-based index. The operating characteristic function of the developed plan is derived based on the exact sampling distribution. The determination of plan parameters is formulated as an optimisation model with non-linear constraints, where the objective is to minimise the sample size required for inspection and the constraints are set by the vendor and the buyer to satisfy the desired quality levels and allowable risks. The performance of the developed plan is examined and compared with traditional sampling plans. A step-by-step procedure is provided, and the parameters of the plan under various conditions are tabulated for practical applications.     

Developing a variables repetitive group sampling scheme by considering process yield and quality loss

Acceptance sampling is a useful tool for determining whether submitted lots should be accepted or rejected. With the current increase in outsourcing production processes and the high-quality levels required, it is very desirable to have an efficient and economic sampling scheme. This paper develops a variables repetitive group sampling (RGS) plan that accounts for the process yield (meeting the manufacturing specifications) and the quality loss (variation from the target). The plan parameters are determined by solving a nonlinear optimisation problem. This implies that the plan parameters minimise the average sample number required for inspection and fulfil the classical two-point conditions on the operating characteristic (OC) curve. Besides, this paper investigates the efficiency of the proposed plan and compares it with the existing variables single sampling plan. Tables of the plan parameters for the proposed variables RGS plan are provided and an application example is presented for illustration.     

Variables Sampling Plan for Resubmitted Lots in a Process with Linear Profiles

Acceptance sampling plans include a sampling scheme and a set of rules for determining whether an inspection lot from a supplier should be accepted or rejected. In some circumstances, the supplier is allowed to resubmit lots for further inspection when the original inspection result is unacceptable. In this study, two variables sampling plans based on the process‐yield index for a process with linear profiles are proposed to deal with lot sentencing. The single sampling plan is a special case of the resubmitted lots sampling plan. The plan parameters are determined using a nonlinear optimization method under the given values of producer's risk, consumer's risk, acceptable quality level, and lot tolerance percent defective. Numerous tables are provided to determine the plan parameters. One real example is used to illustrate our proposed method. Copyright © 2015 John Wiley & Sons, Ltd.     

浅议抽检产品平均检出质量的测算与控制

文章提出了所发现的多例企业使用抽样检验控制出厂产品返次率中存在的问题,通过对抽样方案的平均检出质量的测算分析,指出了所确定的抽样计划及其相关参数的不合理性,并给出解决的建议.     

Effect of process parameters in face milling operation and analysis of cutting force using indirect method

Amelioration of demand for quality in machining-related products has resulted in the manufacturing industries as cornerstone for enhancement in quality control measures of the machining process. Milling, like any metal cutting operation, is used with an objective of optimizing surface roughness. Meticulous prediction of surface quality of a particular material during face milling operation is highly important for the purpose of controlling product quality and production rate. The machining characteristics of AA6061 using face milling were investigated. To calculate the cutting force through indirect approach, during machining the data acquisition was performed using a FANUC LAN cable. The data related to the current drawn by each axis were captured under two varying cases, one “With Cut” and another “Without Cut.” The experimental plan was executed by adopting the Taguchi approach to minimize experimental cost. The results attained through analysis of variance signify that the projected mathematical model can efficiently illustrate the performance in the boundary limit of the premeditated factors.     

测量不确定度引起的批量产品检验误判风险评估

为在产品检验前合理预估测量不确定度对批量产品检验结果的影响,分别面向全数检验和抽样检验方法,以误判率为指标,量化表示产品供求双方风险;基于绝对概率和条件概率,建立全数检验误判风险模型,在此基础上,推导抽样检验误判率计算公式。实例分析结果表明,提出模型可综合反映测量不确定度引起的误判风险;基于绝对概率模型的误判率计算结果,可作为产品检验测量方案选择的依据;基于条件概率模型的误判率计算结果,可更直观地反映产品供求双方风险,促使检验人员更为慎重地进行合格性判定。