什么是SPC

SPC即统计过程控制（Statistical Process Control）。 SPC主要是指应用统计分析技术对生产过程进行实时监控，科学的区分出生产过程中产品质量的随机波动与异常波动，从而对生产过程的异常趋势提出预警，以便生产管理人员及时采取措施，消除异常，恢复过程的稳定，从而达到提高和控制质量的目的。[第一段]     

用统计过程控制技术监控孵化机箱板生产质量

本文介绍了统计过程控制(SPC)技术,重点阐述了应用SPC技术对孵化机箱板生产质量实际进行监控的过程与方法.     

SPC技术在电子元器件生产中的应用

对统计过程控制（SPC）技术做了简要介绍；对我国电子元器件制造方在应用SPC过程中出现的一些问题和解决方案进行了讨论。     

SPC在电缆外护套挤出工艺中的应用

统计过程控制(statistic process control,SPC)与传统的产品控制方法不同,具有诸多优点,是一种科学有效的方法。以某电缆外护套挤出工艺为例,阐述了如何应用SPC技术来分析产品质量数据,实施SPC的工作程序及实施SPC之后的效果。以定量的数理统计方法评估工艺的控制能力,最后通过对生产过程连续监控保证产品质量的稳定性。     

统计过程控制在产品质量管理中的应用

统计过程控制(SPC)作为质量管理的重要工具对生产过程起预防与预测作用：介绍统计过程控制的概念和基本运用方法。     

运用统计分析工具解决生产质量问题

运用统计分析工具,结合生产过程中的统计过程控制（SPC）和专业分析,能够比较准确、快捷地找到质量问题的根源。     

成组技术在微波仪器零件生产中的应用

文章分析了成组技术在微波仪器零件生产中的应用,阐述了相似质量特性为主的成组方法在质量控制上如何解决SPC（统计过程控制）中样本量不足的问题。     

SPC技术在键合工艺中的应用

采用统计过程控制(SPC)技术,提高微电路产品的质量和可靠性,监控键合工序的生产过程状态。通过连续采集的25批键合强度数据,绘制了标准-偏差控制图,并对控制图处于非受控状态的批次进行了具体分析。根据分析结果,改进工艺方法,使生产过程处于受控状态。     

SPC在小批量生产中的应用

统计过程控制(SPC)是获得合格产品质量的有效工具,它是过程性能监视和过程故障诊断的基础,控制图是SPC的核心工具。文中通过选取正确的SPC模型、数据采集、绘制控制图和数据分析,实现了对小批量生产过程的有效监控。     

开展SPC诊断提高C_(PL)

无锡华芝半导体有限公司在集成电路后道生产过程中,确定对键合关键工序的破断强度和剥离强度两个质量特性应用统计过程控制（SPC）实施过程监控。在实施中发现某规格金丝破断强度的工序能力指数（C(PL)）偏低,经过诊断能获得预防性改进。笔者以此为例探讨SPC诊断（SPCD）过程及其操作。一、原因调查SPC诊断首先从原因调查开始,检查“病状”,判定“病症”。1．现状调查。门）键合采用的金丝有。25pm、巾30pm和中32卜m三种规格。前两种金丝的C;。。分别为1．72和1．75,工序能力等级达到特级水平,即工序能力过高。后一种金丝的C…     

Prioritizing processes in initial implementation of statisticalprocess control

A production process composed of tens or even hundreds of subprocesses is a common phenomenon in industry. Each of the subprocesses contributes to various aspects of product quality. Ideally, a control chart can be set up on every subprocess to guarantee the quality of the final product. This is not practical however, because of limited human and economic resources, and the management has to decide which subprocesses are to be given higher priorities. In this paper, for the purpose of prioritizing processes in complicated production systems for implementing statistical process control (SPC) schemes, preliminary selection based on statistical and technical criticality of processes is discussed. An analytic hierarchy process approach based on pair-wise comparisons between several factors in deciding the relative criticality of the processes in a hierarchy structure is then studied. The approach can be used in management decision making in planning for SPC implementation. A case study is presented to illustrate the methodology     

Statistical process control in semiconductor manufacturing

The author presents a brief survey of standard SPC (statistical process control) schemes, and illustrates them through examples taken from the semiconductor industry. These methods range from contamination control to the monitoring of continuous process parameters. It is noted that, even as SPC is transforming IC production, the peculiarities of semiconductor manufacturing technology are transforming SPC. Therefore, the author describes novel SPC applications which are now emerging in semiconductor production. These methods are being developed to monitor the short production runs that are characteristic of flexible manufacturing. Additional SPC techniques suitable for in situ multivariate sensor readings are also discussed     

制造业过程控制中的测试保证方法研究

制造市场的激烈竞争要求制造业开发一种保证产品质量的过程控制 ,而不是依靠常规检测来找出造成重大经济损失的废品。在产品生产过程的研究中 ,文中采用连续校准的方法 ,给出确定和控制测量误差的过程测试保证方法。这个方法的应用和产品统计过程控制 (SPC)共同确定了产品的结果 ,即当在过程控制的测量中确定了有关测量误差后 ,相应的产品测试结果误差也就确定了 ,从而极大地减少或免去进一步的检测     

BiCMOS工艺中纵向晶体管β和广义SPC

采用 SPC获得影响 Bi CMOS工艺中纵向晶体管电流放大系数 β值波动的因素仅和基区方块电阻相关。进一步采用 SUPREM3工艺模拟得到影响 β波动的重要因素是扩散炉温度。试验结果定量证明温度的影响 ,由此说明批量生产时测试基区方块电阻而无需测试结深就能预测其 β值。最后建议采用广义的 SPC使 β值受控达到设计规范     

SPC在多品种小批量生产线的应用研究

统计过程控制(SPC)是一种有效的质量管理工具,但由于半导体制造工艺过程的复杂性,常规的SPC模型已经不能对工艺过程状态进行有效的监控。着重论述了SPC在多品种、小批量半导体生产线上的实际应用;根据工艺特点,选取正确的SPC模型,通过采集数据、绘制控制图和数据分析,对图中异常点采用5M1E进行分析,既可及时发现工艺异常并进行纠正,又可排除非工艺原因造成的异常。该方法对提高工艺稳定性和产品质量有着非常重要的意义。     

The mathematics of success and failure [SPC]

The use of statistical process control (SPC) to improve quality is discussed. Mathematical tools and techniques for SPC are reviewed. How to decide when a change in an indicator is statistically significant is addressed. An approach to SPC in which one attempts to reduce process sensitivity to external variations rather than control these variations more tightly is discussed     

接近零不合格过程的质量分析及控制探讨

该文对提高接近零不合格过程的质量分析和控制的准确性及效率进行探讨,提出对接近零不合格过程的质量分析首先应根据产品质量要求和过程能力要求选择合适的aσ,且要与接近零不合格过程的控制的程度相适应,然后利用传统的统计过程控翩(SPC)的方法对过程进行质量分析和控制,使过程处于受控状态或良好的受控状态,同时利用该状态时的不合格...     

Run by run process control: combining SPC and feedback control

The run by run controller provides a framework for controlling a process which is subject to disturbances such as shifts and drifts as a normal part of its operation. The run by run controller combines the advantages of both statistical process control (SPC) and feedback control. It has three components: rapid mode, gradual mode, and generalized SPC. Rapid mode adapts to sudden shifts in the process such as those caused by maintenance operations. Gradual mode adapts to gradual drifts in the process such as those caused by build-up of deposition inside a reactor. The choice between the two modes is determined by the outcome from generalized SPC which allows SPC to be applied to a process while it is being tuned. The run by run controller has been applied to the control of a silicon epitaxy process in a barrel reactor. Rapid mode recovered the process within 3 runs after a disturbance. Gradual mode reduced the variation of the process by a factor of 2.7 as compared to historical data