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“智能制造模型”系列之四:可追溯性应用程序支持

“智能制造模型”系列之四:可追溯性应用程序支持 CIMETRIX矽美科
2020-09-08
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导读:随着集成电路越来越多地应用到对人类和环境安全至关重要的应用中,与产品可追溯性相关的法规要求变得越来越严格。
先有鸡,先有蛋,你知道鸡和蛋从哪里来吗?

例如,汽车行业已经要求设备制造商在收到特定类型产品的请求后48小时内提供完整的制造过程历史记录,但这只是触及了自动驾驶汽车及其配套公共基础设施、飞机零部件、医疗植入物和诊断系统等新兴市场的表面。

好消息是,最新的半导体制造设备接口标准包含了关于正在制造的产品和过程中每一步使用的工艺的足够信息,可以直接支持这些可追溯性要求,几乎或根本不需要定制软件。具体来说, 半导体设备数据采集(EDA)这套标准(也称为“Interface A”)定义了一个显式的设备的组件模型,可以表示这些信息,并且SEMI E164 EDA(通用元数据标准)甚至指定了所需组件的实际结构和命名约定。。
在深入讨论细节之前,让我们先后退一步,定义下这个背景下的“可跟踪性”。根据iso9000(质量管理体系-基础和词汇),这个术语的意思是“通过记录标识来追溯一个实体的历史、应用或位置的能力”。
在晶圆制造设备中,这一定义覆盖了很大范围内的能力。最基本的解释是,只要在晶圆在晶圆厂三个月的生产过程中,提供一份这片晶圆到过的所有生产设备的有序清单就可以了。只要制造商能够记录每个被组装的芯片来自于哪个基板(大多数来自哪个基板),就可以从MES(制造执行系统)及其相关的计划/调度系统中的信息生成所需的文档。


然而,另一方面,可追溯性的要求可能不仅包括设备访问列表,还会有在每个设备里使用的配方,晶片运动的精确的时间和设备内访问的工艺处理模块,任何可调的能够影响工艺处理行为的配方参数值和/或设备常数,工艺处理中使用的任何耗材的批号和状态信息,任何参与其中,操作设备的使用次数,操作人员的相互左右(如果有的话),等等。之所以有这么详细是为了使故障分析工程师能够确定任何现场故障的潜在的根本原因,然后确定现场的哪些设备可能容易出现类似的故障情况,以便进行产品召回。
可以肯定的是,大多数现代晶圆厂的设备、工艺工程和成品率管理系统所维护的各种数据库可以在事后汇集这些信息,但是这个过程可能很复杂、耗时,而且容易出错。更好的办法是直接从设备中可获得的信息即时生成最常用的可追溯性记录……这就是最新的EDA标准发挥作用的地方
通过类比,让我们看一个直观的例子:一个商业蛋糕烘焙企业。即使是相对简单(与半导体制造相比)的生产过程,完整的可追溯性也需要从原材料供应商到生产过程到包装和成品仓储的信息。在下面的图片中,你可以看到材料、配方和设备设置信息都包含在生产记录中。

在具有E164兼容接口的半导体制造设备单元中,这些类型的信息出现在设备元数据模型的各个部分中。具体来说,在“材料管理器”逻辑组件中捕获与材料相关的信息,如下面的扩展视图*所示,以突出显示每个晶圆(基片)在设备中传输和处理期间的状态转换事件和可用的参数数据。 


如SEMIE157(模块处理跟踪)中规定和E164中所要求的,配方的相关的信息在负责晶圆(基片)处理的物理模块的“E1570710:模块进程”状态机中可以找到(如下面的例子中的“ProcessingChamber1”和“ProcessingChamber2”)。请注意下面的扩展模型摘录中,每个配方步骤中可用的上下文信息的丰富列表,包括RecipeParameters数组。 


总的来说,来自设备模型的这两个部分的时间和参数数据提供了完整晶圆厂可追溯性所需的大部分信息。此外,由于SEMI E164实际上对模型中的事件和参数名进行了标准化,因此可以为符合E164的所有设备以编程方式生成和激活收集这些信息的DCPs(数据收集计划)。这意味着与用于识别、收集和管理这些信息的传统方法相比,大大降低了工程成本。下图是这样一个DCP的可视化图。 


当从单个设备扩展到电路板、模块和完成的部件(参见下面的汽车速度计示例)时,这些需求甚至需要更多的记录工作……但这是以后的主题! 


这篇文章是最近发布的智能制造模型系列的第四篇,请务必关注后续的帖子,它们会扩展这个主题。我们期待您的反馈,并与您分享智能制造之旅。
*设备元数据模型片段和DCP内容的可视化是由CimetrixECCE Plus产品(EDA客户端连接模拟器)生成的。



Traceability Application Support: Episode 4 in the

“Models in Smart Manufacturing” Series

 

…never mind which came first… do you know where the chicken and the egg came from?


As integrated circuits increasingly find their way into applications for which human and environmental safety are paramount, the regulatory requirements related to product traceability become ever more stringent. For example, the automotive industry already requires that a device maker be able to provide a full manufacturing process history within 48 hours of a request for certain kinds of products, but this only scratches the surface of what’s to come in the growing markets for autonomous vehicles and their supporting public infrastructure, aircraft components, medical implants and diagnostic systems, and the like.

  

The good news in all this is that the latest semiconductor manufacturing equipment interface standards include enough information about the product being built and the processes used at each step along the way to directly support these traceability requirements with little or no custom software. Specifically, the SEMI Equipment Data Acquisition (EDA) suite of standards (also known as“Interface A”) defines the components of an explicit equipment model that can represent this information, and the SEMI E164 (EDA Common Metadata) standard goes so far as to specify the actual structure and naming conventions for the required components.

Before getting deeper into the specifics, let’s step back and define “traceability” in this context. According to ISO 9000 (Quality management systems – Fundamentals and vocabulary), the term means “the ability to trace the history, application or location of an entity by means of recorded identifications.”

In a wafer fabrication facility, this definition covers a broad range of capabilities. The most basic interpretation could be satisfied by simply having an ordered list of the manufacturing equipment visited by each wafer (substrate) during its 3-month journey through the fab. As long as the manufacturer keeps a record of which substrate each assembled die came from (which most do), the required documentation could be generated from information contained in the MES(Manufacturing Execution System) and its associated scheduling/dispatching system.


However, at the other end of the spectrum, the traceability requirement may include not only the list of equipment visited, but also the recipe used at each equipment, the precise timing of wafer movement and process modules visited within the equipment, values of any adjustable recipe parameters and/or equipment constants that affect process behavior, batch identification and status information for any consumables used during the process, usage counts for any fixtures involved, operator interactions (if any), and so on. The reason for this level of detailis to enable the failure analysis engineers to identify the potential root causes for any field failures, and then determine what other devices in the field may be susceptible to similar failure conditions for product recall purposes.


To be sure, much of this information could be assembled after-the -fact from the various data bases maintained by the equipment and process engineering and yield management systems present in most modern wafer fabs, but this process can be complex, time-consuming, and error-prone. A better approach would be to generate the most commonly needed traceability records on-the fly directly from information available in the equipment... and this is where the newest EDA standards enter the picture.


By analogy, let’s look at an intuitive example: a commercial cake baking enterprise. Even for a relatively simple (compared to semiconductor manufacturing) production process, full traceability requires information from the raw materials suppliers through the manufacturing process to packaging and finished goods warehousing. You can see in the picture below that material, recipe, and equipment setup information is included in the records produced.

In a unit of semiconductor manufacturing equipment with an E164-compliant interface, these types of information appearin various sections of the equipment metadata model. Specifically, material-related information is captured in the “Material Manager” logical component, shown in expanded view below* to highlight the state transition events and parameter data available for each substrate during its transportation and processing in the equipment.

Recipe-related information is found in the physical modules responsible for substrate processing

("ProcessingChamber1" and "ProcessingChamber2" in the example below), within the “E1570710:ModuleProcess” state machine, dictated by the SEMI E157 (Module Process Tracking) standard and required by E164. Note the rich list of context information available at every recipe step, including the RecipeParameters array, in the expanded model excerpt below.

Taken together, the timing and parameter data from these two sections of the equipment model supply most of the information required for full wafer fab traceability. Moreover, since SEMI E164 actually standardizes the event and parameter names in the model, the DCPs (data collection plans) that collect this information can be programmatically generated and activated for all the equipment that is E164-compliant. This represents a significant engineering cost reduction over the conventional methods used to identify, collect, and manage this information. The figure below is one visualization of such a DCP.

When extended beyond individual devices to circuit boards, modules, and completed parts (see the example below for an automobile speedometer), these requirements require even more bookkeeping… but that’s a topic for another day!

This article is the fourth in the series recently announced in the Models in SmartManufacturing Series - Introduction, be sure to watch for subsequent postings that will expand on this theme.


We look forward to your feedback and to sharing the Smart Manufacturing journey with you.


*The visualizations of equipment metadata model fragments and DCP contents are those produced by the CimetrixECCE Plus product (EDA Client Connection Emulator).


Topics: EDA/Interface A, Models in Smart Manufacturing series, Smart Manufacturing/Industry 4.0


Posted by Alan Weber: Vice President, New Product Innovationson Aug 1, 2017 11:15:00 AM


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