CN1720490B - 用于控制具有多变量输入参数的制造工艺的方法和系统 - Google Patents
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Abstract
本发明公开了一种建模和/或控制制造工艺的方法、系统和介质。特别地,一种根据本发明实施例的方法包括识别一个或多个输入参数的步骤。每个输入参数造成至少两个输出改变。所述方法还包括存储所识别的输入的值和对应的经验输出值以及预测输出值的步骤。所述预测输出值是部分地基于所识别的输入值计算的。所述方法还包括通过最小化一个评分方程(score equation)来计算一组变换系数的步骤,该评分方程是一个或多个经验输出值与其对应的预测输出值之间的差值的函数。所述方法还包括以下步骤:接收所识别的输入的一组新值,使用该组系数对所识别的输入的那组新值进行变换,并使用所变换的输入值来计算一组预测输出值。
Description
相关申请
本发明要求2002年11月15日提交的60/426393号美国临时申请的优先权,在此以引用方式将其内容并入本文。
技术领域
本发明涉及对工艺进行建模和控制的方法、系统和介质。更具体地,本发明涉及对具有多变量输入参数的半导体处理设备进行建模和控制。
背景技术
在制造包括精确的分立部件的产品(例如硅衬底上的微电子芯片)时,控制制造工艺扮演着重要的角色。控制这样的工艺可要求,尤其是要监视所制造部件(例如被处理的晶片,此后被称为输出)的特征并据此调整输入参数。通过调整输入参数的值,可以产生不同类型的输出,并且可控制输出的特征。
为了使制造工艺的控制自动化,可以使用处理设备的数学模型。这种模型的一个例子被称为预测模型。这个模型被用于基于历史信息(例如输入参数值和对应的输出质量)来预测未来的输出值(例如产品的特征)。
一个这样的预测模型是偏移技术,如图1中所示。特别地,大量输入参数101的值被输入/输出依赖模型103接收,输入/输出依赖模型103基于输入值计算预测输出值105。然后校正算子109比较输入参数的给定值的预测值和实际输出值如果预测输出值和实际输出值在确定的范围内相互类似,那么就不改变输入/输出依赖模型103。如果预测的和实际输出值相互不同(例如在范围之外),那么就通过基于差值的大小调整偏移值(O1)111来修改预测器输入/输出依赖模型103。
在具有超过一个输出的设备中,至少某些输出可包括共有的(共享的)输入。这意味着设备的输出值彼此不完全独立(例如改变一个输入来调整指定的输出可能会无意地改变其他输出的特征)。在传统的建模技术中,每个输出具有其自己的校正系统,就好像输出值是彼此独立的。由于传统技术不考虑不同输出之间的依赖性,所以它并不总是导致正确的预测。此外,调整一个输出的一个偏移量能影响其他输出。
发明内容
本发明的实施例有利地克服了以上提到的技术的上述缺点。更具体地,本发明的实施例提供了一种控制具有多变量输入参数和输出的半导体处理设备的系统、方法和介质。
本发明的实施例最小化了输出彼此相互依赖的影响。这是通过提供具有变换系数的输入参数变换实现的。随后这使得可获得准确的模型。使用这些模型,可实现制造设备的高度精确的控制。
特别地,一种根据本发明实施例的示例性方法包括以下步骤:识别至少一个输入,该输入导致多个输出中的至少两个输出发生改变;存储所识别的输入的值以及对应的经验输出值;和部分地基于所识别的输入计算和存储预测输出值。该示例性方法可进一步包括以下步骤:通过最小化一个评分方程来计算一组变换系数,该评分方程部分地是一个或多个经验输出值与其对应的预测输出值之间的差值的函数;并且部分地基于所计算的这组变换系数来为一个或多个期望输出值计算一个或多个输入值。
附图说明
当结合附图阅读详细描述时,可最佳地理解本发明的详细描述显示的各种特定特征,其中:
图1示出了传统偏移模型;
图2示出了处理设备;
图3根据本发明的实施例示出了图2中所示的处理设备的模型;
图4是说明本发明实施例的各种组件的方块图;
图5是说明本发明实施例的处理步骤的流程图;
图6示出了CMP工艺;
图7是被配置来执行本发明实施例的计算机的一个示例性实施例的方块图;
图8示出了一个存储介质的例子,其可用于存储本发明实施例的计算机程序。
具体实施方式
本发明的实施例一般地提供系统、方法和介质,用于生成一个或多个自适应工艺模型来数学表示多变量输入参数系统。本发明尤其适用于制造工艺,比如制造和/或处理半导体晶片。特别是,本发明涉及由与半导体晶片制造有关的设备所使用的建模技术。以下提供了本发明实施例的全面概述。随后是本发明的一个特定的示例性实施方式。
在讨论本发明的实施例之前,图2显示了具有输入参数201和输出203的处理设备205的简化图形表示。处理设备的例子包括蚀刻器工具、沉积工具、化学机械平坦化(CMP)工具等等。处理设备205能够包括一个或多个工具。根据输入参数201的值,可实现不同的工艺。例如,在沉积工具中,不同类型的层可沉积在晶片上和/或层的厚度可变化。
如图3中本发明实施例的总览,处理设备205具有一组输入参数301、一组预测输出303和其之间的预测模型305(取代图2中的处理设备)。预测模型的总目标是使预测输出值和经验收集的输出值(也就是实际输出值)之间的差值最小化。一旦预测模型被优化(例如预测输出值和实际输出值之间的差值已经被最小化),那么该模型能够被用于基于期望输出值设置输入参数。换句话说,对于一组指定的期望输出值,可以以相反的方式使用该模型来计算可导致输出值接近期望输出值的输入参数值。计算的输入参数值通称为配方(recipe)。
在本发明的实施例中,获得预测模型的步骤可分成两步。第一是把输入参数301的值变换成变换输入值307。第二是使用变换输入值307计算预测输出值303。
(在这个例子中P11、P12、P21、P22和Pcross能够具有不同的值。)
系数值是通过以下步骤计算的:a.收集关于输入参数值和实际输出值的历史信息;b.基于所收集的信息生成评分函数;和c.寻找最小化评分函数SP的系数值。
以上步骤是通过参考半导体处理工具描述的。同样地,收集历史信息的步骤需要一组数据点用于处理大量的晶片。特别是,应收集已经被处理设备处理的大量晶片的输入参数值和实际输出值。然后这个收集被用于最小化评分函数的下一步。
这里评分函数SP是:
其中:
i——晶片数量;
k——输出数量;
yactual——实际输出值;
ypredicted——预测输出值,是按照基于特定晶片i的变换输入来计算的;
和
上述步骤计算最优的(也就是输入变换函数的系数向量),使得本发明的预测模型提供最接近实际输出的可能的预测输出。在具有多变量输入参数的处理模型中,当所述评分最小化时,输出值之间的相互依赖性对于模型准确性的负面影响也被最小化。
现在转到描述上述实施例的示例实现,如图4所述,该示例实现包括大量的组件:输入变换器401、输入一输出依赖模型403、校正算子405和存储设备407。所有这些组件可以在硬件、固件、软件和/或这些的任意组合中实现。
参考图5进一步解释这些组件。特别是,历史信息(也就是 )存储在存储设备407中。校正算子405然后从存储设备407检索历史信息(步骤501)。由于检索的历史信息包含原始的输入参数值,所以该信息连同系数被发送到输入变换器401(步骤503)。系数可存储在存储设备407或者校正算子405中。
在接收到来自输入变换器401的变换的输入参数值时,校正算子405就把变换的输入参数值发送给输入/输出依赖模型403。输入/输出依赖模型403然后计算预测输出参数值ypred(步骤507)。校正算子405然后计算评分SP,并设置新的(输入变换函数的参数向量)以最小化评分SP(步骤509)。可以重复这些步骤直到获得产生最小评分SP的最优并返回每次获得新的数据,就生成来自新数据的新评分并计算最优值。这个新计算的向量可被用于变换输入值,意思是
在本发明的实施例中,最优系数可以和最近的向量结合,以至于其中K<1。
当一组新的数据点到达时,可重新计算新的最优
一旦计算了一组系数,就可获得一组期望输出值的一组输入值(例如一个配方)。更具体地,根据一组期望值,通过反转所述预测模型(例如输入/输出依赖模型403)可获得一组变换的输入值变换的输入值然后可使用系数被逆变换,以获得输入值来产生期望输出值。
在上述实施例中,使用计算的系数变换了原始输入值。这种变换要求考虑输入参数之间的依赖性,如图6所示的。更具体的,一个晶片的表面被CMP工艺抛光,该晶片具有5个粗糙度不同的区域。目标是获得由图6中的虚线表示的平坦表面。在传统的技术中,可抛光一个区域而不考虑其他区域。但是,抛光一个区域能影响另一个区域的抛光(例如,当在区域1中应用偏移以把区域1的高度下降到虚线时,区域2的高度也被区域1的变化所影响)。使用本发明的实施例,说明了这些依赖性。
以下结合图7-8描述本发明的实施例在其中操作的计算机的示例实施例(例如在图4中描述的各种组件)。图7示例说明了被配置执行本发明实施例的计算机的内部硬件713的一个例子的方块图。总线756作为主要的信息高速路互连其中的各种组件。CPU 758是内部硬件713的中央处理单元,执行计算和逻辑运算,而这些是执行本发明的实施例以及其他程序所需的。只读存储器(ROM)760和随机存储器(RAM)762组成主存储器。磁盘控制器764连接一个或多个磁盘驱动器到系统总线756。这些磁盘驱动器是,例如软盘驱动器770、CD ROM或DVD(数字视频磁盘)驱动器766、或者内部或外部硬盘驱动器768。这些各种磁盘驱动器和磁盘控制器是可选的设备。
显示接口772和显示器748相连,并允许来自总线756的信息显示在显示器748上。与外部设备比如上述系统的其他组件的通信是利用,例如通信端口774进行的。光纤和/或电缆和/或导体和/或光通信(红外等等)和/或无线通信(例如射频RF等等)能够被用作外部设备和通信端口774之间的传输介质。外围接口754连接键盘750和鼠标752,允许输入数据传送到总线756。除了这些组件,内部硬件713还可选地包括红外发射器和/或红外接收器。当计算机系统与经由红外信号传输发送/接收数据的一个或多个处理组件/站/模块一起使用时,红外发射器被可选地使用。不使用红外发射器或红外接收器,计算机系统也可可选地使用低功率无线电发射器780和/或低功率无线电接收器782。低功率无线电发射器发送被生产工艺的组件接收的信号,并经由低功率无线电接收器接收来自这些组件的信号。低功率无线电发射器和/或接收器是工业标准设备。
虽然图7中的计算机被示例性地表示为具有单个处理器,单个硬盘驱动器和单个本地存储器,但是分析器可选地适合配备任何多的处理器或存储设备或者其组合。例如,计算机可被根据本发明实施例的任何合适的可操作处理系统替代或者与其组合,包括复杂的计算器、手持设备、笔记本电脑、微型计算机、大型机和超级计算机,以及相同的处理系统网络组合。
图8是示例性的计算机可读存储器介质884,其用于存储计算机可读代码或指令。作为一个例子,介质884可与图7所示的磁盘驱动器一起使用。典型地,存储介质比如软磁盘、CD ROM或数字视频磁盘将包含,例如用于单字节语言的多字节地区和用于控制建模器使得计算机能够执行上述功能的程序信息。替代地,图7所示的ROM 760和/或RAM 762也可被用于存储程序信息,该程序信息被用于指示中央处理单元758执行与本发明的各种自动处理相关联的操作。用于存储信息的合适的计算机可读介质的其他例子包括磁存储、电存储或者光存储(包括全息存储)、其某些组合等等。
通常,应该强调的是本发明实施例的各种组件可在硬件、软件或者其组合中实现。在这种实施例中,各种组件和步骤可在硬件/或软件中实现以执行本发明实施例的功能。可在本发明的这种实施例使用任何现在可用的或者未来开发的计算机软件语言和/或硬件组件。例如,至少上述某些功能能够使用Visual Basic、C、C++或者考虑到使用的处理器适合的任何汇编语言实现。它应该在解释性环境比如Java中编写,并传送到多个目的地给不同用户。
本发明实施例的许多特征和优点在详细的说明书中是明显的,因此,由所附的权利要求来覆盖本发明的所有这些特征和优点,其属于本发明的真正精神和范围。此外,由于对于本领域的技术人员来说,大量修改和变化是容易进行的,所以不希望把本发明限制在所述的确切构造和操作,据此,可采用所有合适的属于本发明范围的修改和等同物。例如,输出值可进行和输入参数上实施的变换类似的变换,且可对所变换的输出值上实施类似那些在所变换的输入参数上实施的变换。
Claims (14)
1.一种用于控制制造设备的计算机实现的方法,所述方法包括以下步骤:
(a)识别通到所述制造设备的至少一个输入,所述至少一个输入导致所述制造设备的多个输出中的至少两个输出发生改变;
(b)存储所识别的输入的值和对应的实际输出值;
(c)基于所述所识别的输入的值确定和存储预测输出值;
(d)通过最小化一个评分方程来确定一组变换系数,所述评分方程使用一个或多个所述实际输出值与其对应的预测输出值之间的差值的函数来表示;
(e)基于所计算的这组变换系数来确定对应于一个或多个期望输出值的一个或多个输入参数;和
(f)利用步骤(e)中所确定的一个或多个输入参数来设置制造设备输入参数。
4.根据权利要求1所述的方法,进一步包括步骤:
收集来自所述制造设备的新的实际输出数据和所述制造设备的对应的输入值;和
基于所述新的实际输出数据计算一组新的系数。
6.一种用于控制制造设备的系统,所述系统包括:
(a)用于识别通到所述制造设备的至少一个输入的装置,所述至少一个输入导致所述制造设备的多个输出中的至少两个输出发生改变;
(b)一个存储器设备,其被配置成存储所识别的输入的值和对应的实际输出值以及预测输出值,其中所述预测输出值是基于所述所识别的输入的值计算的;
(c)通过最小化一个评分方程来确定一组变换系数的装置,所述评分方程使用一个或多个所述实际输出值与其对应的预测输出值之间的差值的函数来表示;
(d)基于所计算的这组变换系数来确定对应于一个或多个期望输出值的一个或多个输入参数的装置;和
(e)利用(d)中所确定的一个或多个输入参数来设置制造设备输入参数的装置。
9.根据权利要求6所述的系统,进一步包括:
收集来自所述制造设备的新的实际输出数据和所述制造设备的对应的输入值的装置;和
基于所述新的实际输出数据确定一组新的系数的装置。
11.一种用于控制半导体处理设备的计算机实现的方法,其中所述半导体处理设备有多个输入参数和多个输出,所述方法包括以下步骤:
(a)识别通到所述半导体处理设备的至少一个输入,所述至少一个输入导致所述半导体处理设备的多个输出中的至少两个输出发生改变;
(b)找到所识别的输入的值和对应的实际输出值;
(c)基于所述所识别的输入的值确定预测输出值;
(d)通过最小化一个评分方程来确定一组变换系数,所述评分方程使用一个或多个所述实际输出值与其对应的预测输出值之间的差值的函数来表示;
(e)基于所确定的这组变换系数来确定对应于一个或多个期望输出值的一个或多个输入参数;和
(f)利用步骤(e)中所确定的输入参数来设置半导体处理设备输入参数。
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US7966087B2 (en) | 2011-06-21 |
US20080021571A1 (en) | 2008-01-24 |
US20040225377A1 (en) | 2004-11-11 |
CN1720490A (zh) | 2006-01-11 |
US7272459B2 (en) | 2007-09-18 |
AU2003290932A1 (en) | 2004-06-15 |
WO2004046835A2 (en) | 2004-06-03 |
WO2004046835A3 (en) | 2005-01-06 |
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