多品种小批量生产模式下基于相似元的工序能力分析

随着社会的发展和科技的进步,消费者对于产品的需求呈现多样化,因此多品种小批量生产模式成为制造业的一大主流趋势,但由此带来的加工数据量少的问题给企业生产过程的质量控制及工序能力分析带来了困难。为了解决这个问题,利用相似元理论,根据影响工序的各种因素,将与目标工序相似的其他工序合并成组,通过数据转换扩大样本容量,进而利用大样本加工数据对目标工序进行质量控制和工序能力分析。以某生产车间车削工序为例,计算出该工序的工序能力指数,所得结果与实际情况相符。结果表明,该方法可以给多品种小批量生产模式下企业的质量控制和工序能力分析工作带来许多便捷。     

面向多品种小批量生产的工序能力指数计算

在概述一般的工序能力指数计算方法的基础上，提出应用成组技术把工艺过程相似、结构相同而公差要求不同的零件归类，通过数据变换转化为服从同一分布的数据，由此计算工序能力指数，旨在解决多品种小批量生产方式下计算工序能力指数中数据不足和工序能力指数繁杂的问题。     

基于熵权和模糊物元的改进多元过程能力分析

为解决多品种小批量产品数据采集困难及各指标间存在交互影响致使传统方法难以奏效的现状,基于主成分分析法的多元过程能力指数会造成信息量缺损。该方法将工序能力影响因素采用模糊物元方法构造工序相似条件,选出相似工序将小批量问题变成大批量处理,应用公差系数法将原始数据转化为相对数据。提出基于熵权理论和模糊物元的改良多元过程能力指数。该论文结合某产品进行实例分析,验证了该方法的实用性和有效性。     

孔定位装置在汽车零件折弯加工中的应用

本文提出了重型汽车零件——支撑板、角板等折弯加工问题,介绍了孔定位装置的主要结构,分析了其在多品种小批量汽车零件折弯工序加工中所体现的工艺先进、加工成本低、经济实用、方便快捷等特点,并对其解决这一问题所起的作用做出评价。     

基于改进田口方法的轮毂装配过程质量控制研究

针对风力机轮毂装配工序的质量控制问题，结合多品种小批量生产模式的特点，提出了一种面向定位布置的轮毂装配关键工序识别与监控的方法。综合考虑轮毂装配生产中的成本因素及相对质量损失，制定装配工序的质量特性损失标准，采用改进的质量损失函数识别轮毂装配关键工序；为解决统计过程控制（SPC）方法应用于小批量生产模式的瓶颈，引入基于直觉模糊集的工序相似性分析与评定方法，通过分析工序相似性的影响因素，构建轮毂装配成组工序相似性评判指标体系及评定模型，完成工序相似性的测度。最终使用SPC方法监控管理轮毂装配关键工序，确保轮毂的装配质量。该研究为小批量生产模式中运用SPC方法管理过程质量提供了理论依据。     

基于工序成本的多元过程能力指数分析

单一的多元过程能力指数在反映企业制造多元质量特性产品能力时存在缺陷,无法反映由于各工序成本的差异而造成的工序能力重要性的差别.基于此,从企业工序质量控制和工序成本关系的角度来分析,构建了基于工序成本修正的多元过程能力指数,反映企业的成本控制能力和产品竞争能力.最后,通过修正得到的多元过程能力指数,一方面优选企业的质量改进或控制方案,另一方面判定企业在同类产品制造中的实际质量控制能力和过程成本损失差异.     

基于过程能力指数的抽样风险研究

如果将生产过程中上一道工序的加工过程（设备）视为生产者,而紧邻的下一道工序的加工过程（设备）视为使用者,则上道工序加工的零部件在通过质量抽样检验进入下道工序的过程中．就将产生抽样风险。而由抽样风险确定的抽样方案直接关系到加工过程质量控制和检验成本控制等加工效率问题。考虑到许多大批量自动生产线的检验设备已经具备在线计算过程能力指数的能力．提出了一个基于过程能力指数的抽样风险分析方法,通过计算过程能力指数,得到相应的抽样风险．进而确定合理的抽样检验方案,从而将加工过程的重要指标——过程能力指数与抽样检验方案之间建立了联系。最后,以某汽车发动机曲轴生产线加工过程为例进行了抽样风险分析。     

多品种小批量生产的SPC应用研究

综述了多品种小批量生产方式的特点以及该生产方式下SPC(统计过程控制)的应用现状,指出常规控制图不适用于多品种小批量生产的问题,提出结合通用控制图、累积和(Cumulative-Sum,CUSUM)控制图和指数加权移动平均(Exponentially Weighted Moving-Averages,EWMA)控制图的解决方法,并总结出该SPC方法用于处理多品种小批量生产中微小偏差的步骤。     

成组单元的作业排序

多品种小批量生产中为提高生产率和经济效益采用成组技术。作业排序是成组技术管理工作中的一个重要问题。本文从多工序成组作业排序的基本方法中着重介绍了一种方法,并结合生产实际应用分析如何进行修正的方法。文中还结合分析对比其他几种方法,指出了本文介绍方法的优点。     

多批次小批量生产过程能力指数的贝叶斯估计

针对过程能力指数(PCIs)的传统计算方法应用于多批次小批量生产过程出现的失真问题,以多批次小批量生产过程的总体均值和总体方差分别服从共轭正态分布和共轭逆伽马分布,利用共轭贝叶斯估计理论提出了多批次小批量生产过程分布参数估计方法、过程能力指数计算方法及其通用表达式,这种贝叶斯估计方法减小仅用当前批小样本容量估计过程参数...     

A run-to-run control algorithm based on timely and delayed mixed-resolution information

In certain run-to-run (R2R) processes, timely accurate measurements are difficult to obtain due to slow laboratory measurement operations. Instead, only low-resolution categorical observations are observed online for important quality variables; continuous measurements for the same variables are provided after a specific amount of delay. Currently, most conventional R2R controllers cannot be applied if no continuous observations are available. It is therefore important to develop online algorithms for R2R process control based on mixed-resolution information that is partially timely and partially delayed. In this study, we take the lapping process in semiconductor manufacturing as an example and propose parameter estimation models with these mixed-resolution data for processes with the first-order autoregressive, AR(1), disturbance series. We also derive control strategies to generate recipes between production runs for better process control. The computational results of a performance evaluation show that the control performance of the proposed method is competitive compared to existing methods that are based on accurate measurements.     

Using economically designed Shewhart and adaptive ―X charts for monitoring the quality of tiles

This paper presents the economic design of ―X control charts for monitoring a critical stage of the main production process at a tile manufacturer in Greece. Two types of ―X charts were developed: a Shewhart‐type chart with fixed parameters and adaptive charts with variable sampling intervals and/or sample size. Our prime motivation was to improve the statistical control scheme employed for monitoring an important quality characteristic of the process with the objective of minimizing the relevant costs. At the same time we tested and confirmed the applicability of the theoretical models supporting the economic design of control charts with fixed and variable parameters in a practical situation. We also evaluated the economic benefits of moving from the broadly used static charts to the application of the more flexible and effective adaptive control charts. The main result of our study is that, by redesigning the currently employed Shewhart chart using economic criteria, the quality‐related cost is expected to decrease by approximately 50% without increasing the implementation complexity. Monitoring the process by means of an adaptive ―X chart with variable sampling intervals will increase the expected cost savings by about 10% compared with the economically designed Shewhart chart at the expense of some implementation difficulty. Copyright © 2006 John Wiley & Sons, Ltd.     

基于神经网络的SPC/EPC整合过程监测方法研究

为解决统计过程控制(SPC)/工程过程调整(EPC)整合引起的传统SPC控制图监测异常扰动效率低的问题,提出了采用神经网络技术监测SPC/EPC整合过程的策略,并对神经网络模型结构和参数设置进行分析,构建过程输入、过程输出及两者的协方差为输入参数,异常扰动发生与否为输出参数的3层神经网络模型。为验证该方法的性能,进行了大量的比较实验:即对相同的样本,分别采用Shewhar图、CUSUM图和上述神经网络模型进行监测。实验结果表明:神经网络模型能准确监测幅度大于2的阶跃扰动和大于2的过程漂移,平均运行步长(ARL)为1;传统SPC监测技术只能较准确地(监测率大于90%)监测幅度大于5的阶跃扰动和大于2的过程漂移,ARL大于2。与传统监测方法相比,该方法能快速有效地监测异常扰动的发生。     

Some Modifications of the Classical Pre‐control Technique

Pre‐control is a simple technique for the initial evaluations of the capability of a process. It can be seen as a tool to get the set‐up approval or fulfilment of the specifications of a production process. As the resultant information of pre‐control should be used to adjust the process, it can be understood as a form of feedback controller. It has sometimes been considered as an alternative to statistical control charts for monitoring processes, although these tools differ in a number of ways. In this work, we propose some new alternatives to the classical pre‐control, particularly in its initial phase that aim to qualify the process, that is, to certify that it is capable. We present a comparative analysis of the power of the different alternatives. Copyright © 2003 John Wiley & Sons, Ltd.     

机械球磨过程控制技术的研究进展

如何实现对机械球磨过程的控制，扬长避短，加快应用进程是当前发展机械球磨技术的研究热点之一。评述了机械球磨过程控制技术的研究进展，介绍了控制气-固反应的反应球磨技术，控制球磨中焊合-碎裂等基本过程的过程控制剂技术，及其在纳米粉体、氢化物、氮化物及复合材料等制备中的应用。     

Integrating statistical process monitoring with feedforward control

Feedforward control is a particular form of engineering process control. If a known input variable z_t can be measured and appropriate relationships built between the input variable, a compensatory variable x_t, and the desired output y_t, then a feedforward control system can be developed. Using feedforward control, we show under both sudden jump shifts and trends in the mean of the input and compensatory variables that the use of statistical process monitoring tools, such as the exponentially‐weighted moving average and the cumulative sum (CUSUM), significantly reduces variability in both the output variable and the controller relative to the use of feedforward control alone. Copyright © 2000 John Wiley & Sons, Ltd.     

Optimal Controllers for Nonsymmetric and Nonquadratic Loss Functions

Minimum-variance controllers provide an essential link for integrating concepts of statistical process control and engineering process control. These controllers are specifically designed to minimize a quadratic loss function. In some problems, however, other loss functions may be more appropriate. In this article, controllers that are optimal for nonsymmetric and nonquadratic loss functions are derived. In many cases, these controllers retain the basic simplicity of the minimum-variance controller. Additionally, for process disturbances driven by normal white noise, the minimum-variance controller is shown to be optimal for a broad class of objective functions.     

A conjugate Bayesian approach to control chart for multi-batch and low volume production

Control chart could effectively reflect whether a manufacturing process is currently under control or not. The calculation of control limits of the control chart has been focusing on traditional frequency approach, which requires a large sample size for an accurate estimation. A conjugate Bayesian approach is introduced to correct the calculation error of control limits with traditional frequency approach in multi-batch and low volume production. Bartlett’s test, analysis of variance test and standardisation treatment are used to construct a proper prior distribution in order to calculate the Bayes estimators of process distribution parameters for the control limits. The case study indicates that this conjugate Bayesian approach presents better performance than the traditional frequency approach when the sample size is small.     

制造过程的质量管理探讨（续）

生产过程控制是对“５ＭＩＥ”质量因素的探讨,其控制活动体现在每一个生产工序中。根据ＩＳＯ９００４标准,从生产过程控制的角度,探讨了制造过程的质量管理问题,并重点讨论了关健和特殊工序的控制。     

Adaptive ―X Control Charts with Sampling at Fixed Times

The idea of a variable sampling interval with sampling at fixed times (VSIFT) has been presented by Reynolds. This paper extends this idea to the other two adaptive ―X charts: the variable sampling rate with sampling at fixed times (VSRFT) ―X chart and the variable parameters with sampling at fixed times (VPFT) ―X chart. The VSIFT, VSRFT and VPFT ―X charts are inclusively called the adaptive with sampling at fixed times (AFT) ―X charts in this paper. The control scheme and the design issue are described and discussed for each of the AFT ―X charts. A comparative study shows that the AFT ―X charts have almost the same detection ability as the traditional adaptive ―X charts. However, from the practical viewpoint, the AFT ―X charts are considered to be more convenient to administer than the traditional adaptive ―X charts. Overall, this paper advances the application of ‘sampling at fixed times’ to the adaptive ―X control charts. Copyright © 2004 John Wiley & Sons, Ltd.