【作者】 顾铠；

【导师】 庄奕琪； 贾新章；

【作者基本信息】 西安电子科技大学 ， 微电子学与固体电子学， 2014， 博士

【摘要】 如今，在半导体和集成电路制造领域，随着工艺过程、技术和设备的日益复杂，电子元器件产品自身功能的不断完善，以及客户对工艺水平及产品质量要求的不断提高，使得生产过程质量控制和评价技术显得日益重要。同时，越来越多的国内企业为了向国际型企业标准迈进，开始重视质量控制与工艺评价技术。因此，全面实施工艺质量控制与评价技术具有重要意义。本论文以半导体生产过程中多品种小批量生产过程及多变量生产工艺为主要研究对象，以理论分析及计算机模拟仿真为手段，利用self-starting技术、多元数值积分与极大似然估计等，研究了多品种小批量生产过程中，工艺参数均值和标准偏差的监控，以及如何对多变量生产过程的产品质量和工艺进行评价。本论文同时介绍了基于截尾样本分析供应商所提供的产品质量的方法。本文的研究成果有助于提高产品质量，减少质量缺陷，对提高企业的市场竞争力具有深远的意义。本论文的主要研究内容包括：1).分析了在多品种小批量生产模式下，实施质量过程控制技术所面对的困难。创新性地提出了多品种生产模式下的质量控制方法——T-K控制图技术，用于检测工艺参数母体均值及标准偏差的波动。该控制图采用一种对样本量要求不高的方法，基于采集的每批样本数据，计算T、K统计量，使得T、K统计量各自相互独立且服从相同分布。该技术具有self-starting特点，无需经历分析用控制图阶段估计母体的分布参数，尤其是T控制图的建立过程与母体标准偏差无关。即便在母体分布参数未知的情况下，只要样本数据达到2批，T-K控制图即可对多品种小批量生产过程实施质量控制。2).从SPC技术的基本原理出发点，讨论了控制图性能的衡量方法。对平均运行长度的概念、意义及计算方法做出简单介绍。其次对T控制图及K控制图的ARL性能进行了分析。而后分析了self-starting控制图的缺陷，并提出了一种优化方法用于改进具有自启动特点的控制图的ARL性能。结果表明，改进后的Q控制图以及T-K控制图的ARL性能均有明显提升。3).以单变量工艺为核心简要介绍单变量工序能力指数与工艺成品率的关系，并结合6σ设计评价思路对常规Cpk计算方式进行了改进，提出了一种与成品率具有一一对应关系的等效工序能力指数ECpk。之后沿用这一思想引出基于成品率的多变量工序能力指数MECpk的概念及计算方法，并分析了协方差矩阵对多变量工艺成品率的影响，提出了一种提升工艺成品率的解决思路。最后通过实例详述了多变量工序能力指数的计算过程，通过与其他多变量工序能力指数评价结果对比，验证了MECpk指数的有效性。4).成品率反映了产品的内在质量和可靠性。从购买者的角度出发，介绍了如何利用产品特性参数的截尾样本数据来评价供应商所提供产品的质量；提出了利用服从截尾正态分布的样本数据推测产品成品率的方法，该方法同时适用于单侧及双侧截尾情况；定量分析了成品率计算结果的置信区间，进而给出了该方法对样本容量的要求。同时，结合半导体产品的实际测试数据介绍了基于截尾数据推测成品率的步骤，并验证了算法有效性。5).此外，在本课题的研究基础上，开发了质量控制与评价软件系统。该软件包含了质量过程控制与工艺评价功能，涵盖了多种控制图技术和工序能力指数计算方法，而且具有本文所提出的多变量工序能力指数计算模块。更多还原

【Abstract】 In the field of modern semiconductor and integrated circuit manufacturing, asprocess, technology and equipments are becoming more and more complicated, thefunction of electronic devices is becoming more perfect and users bring morerequirements to process level and product quality.Then, it isnecessary thatthe techniquesof quality control and process evaluation should be paied more attention. At the sametime, in order to keep abreast of time and compete with international companies, domesticcompanies begin to implement techniques of quality management and process evaluation.So, their implement is of important significance.This dissertation studies some problems of process control and evaluation inmultivariate process and multi-variety and small batch manufacturing system using self-starting technique, multivariate numerical integration and maximum likelihoodestimation and so on through theory and computer simulation analysis. The problemsinclude monitoring process mean and standard deviation of multi-variety and small batchproduction run, and the evaluation of the process and product quality of multivariateprocess. In the meanwhile, the method of evaluation on the quality of product providedby suppliers based on truncated sample is also introduced. These researches can improveprocess products quality and reduce quality defects. It is meaningful to up-grate marketcompetitiveness of enterprise. The main contents are summarized as follows:1). Fistly, the existing problem of implementing quality control and evaluation inmulti-variety and small batch production runs to monitor process mean and standarddeviation is analyzed. A quality control technique in multi-variety and small batchmanufacturing system, T-K control chart, is proposed constructively. Using this method,the quality manager needn’t collect samples as many as traditional chart. The T or Kstatistics are calculated based on each subgroup, and the statistics of each subgroup areindependent with each other and have an identical distribution. This method adopts self-startingtechnique, and does notrequire PhaseI sample aimingat estimating processmean.Especially, the T-chart does not need the estimation of variance. Even the distributionparameters are unknown, the T-K chart can be used to monitor multi-variety and smallbatch production run as long as there are no less than2subgroups.2). In the light of the theory of statistical process control, some methods to evaluatethe performance of control chart are discussed. Then, the concept, the significance andthe calculation steps of average run length are introduced. The ARL performance of Tchart and K chart is analyzed. In addition, the shortcoming of self-starting control chart is studied, and a strategy for optimizing theARLperformance of self-staring control chartis proposed. The result reveals that the ARL performance is improved dramatically afterthe optimization.3). The relationship between the index Cpkand process yield for the case with singlecharacteristic is analyzed. Then an equivalent process capability index ECpkis proposedbased on the idea of six sigma design strategy. ECpkindex has a one-to-onecorrespondence relationship with process yield. Following this idea we develop amultivariate PCI MECpkwhich can be used to evaluate process capability for processeswith multiple characteristics and we also discuss the impact of covariance matrix onprocess yield, fromwhich the authors propose a solution to improve overall process yield.Some illustrative examples are presented to verify the validity of the suggested index invarious cases.4). It is known that product yield reflects the potential product quality and reliability,which means that high yield corresponds to good quality and high reliability. From theview of consumers, the method of judging the quality of products supplied bymanufacturers based on truncated samples is introduced. This dissertation proposes analgorithm for calculating the parameters of full Gaussian distribution before truncationbased on truncated dataand estimating product yield.The algorithmis proper to both one-side and two-side truncation. The confidence interval of the yield result is derived, andthe effect of sample size on the precision of the calculation result is also analyzed. Finally,the steps for calculating the product yield are offered and the effectiveness of thisalgorithm is verified by an actual instance.5). In addition, based on the models and algorithms discussed above, the computer-aid quality control and process evaluation software is developed. The software systemincludes the function for statistical process control and process capability evaluation. Thesoftware offers many control charts,process capability indicesand especially the functionfor computing multivariate process capability index proposed in this dissertation.更多还原