Industry News, Trends and Technology, and Standards Updates

Resources Round-up: White Papers

Posted by Kimberly Daich; Director of Marketing on Mar 26, 2019 11:15:00 AM

Resource Center-1The Cimetrix Resource Center is a great tool for anyone who wants to learn more about industry standards including GEM (SECS/GEM), GEM300, EDA/Interface A, and more. These standards are among the key enabling technologies for the Smart Manufacturing and Industry 4.0 global initiatives that are having a major impact on many industries. Manufacturers and their equipment suppliers must be able to connect equipment and other data sources, gather and analyze data in real time, and optimize production through a wide variety of applications. The free white papers listed below provide in-depth coverage of the most broadly used equipment connectivity standards. They have been written by technical experts who have participated in and led the standards development process for more than two decades.

Be sure to stop by our Resource Center any time or download the white papers directly from the links in this posting.


Topics: Industry Highlights, SECS/GEM, EDA/Interface A, Doing Business with Cimetrix, Programming Tools, Photovoltaic/PV Standards, Smart Manufacturing/Industry 4.0

EDA Implementation Insights: What Data Should I Publish?

Posted by Derek Lindsey: Product Manager on Mar 19, 2019 11:30:00 AM

Previous blog posts have discussed the merits of choosing a commercial software platform for implementing the equipment side of EDA (Equipment Data Acquisition) and how you would use that package to differentiate your equipment data collection capabilities from your competitors.

In this post, we discuss how to design the equipment model to contain enough information to make it useful without publishing so much data that it becomes cumbersome for your factory customers to find the data that is most important to them.

Data to Publish

The automation requirements for the most advanced fabs call for the latest versions (Freeze II) of all the standards in the EDA suite, including the EDA Common Metadata (SEMI E164) standard. In addition to providing an excellent foundation for a new equipment model, E164 enables consistent implementation of GEM300, commonality across equipment types, automation of many data collection processes, less work to interpret collected data, and true plug-and-play client applications—all of which contribute to major increases in engineering efficiency. These capabilities benefit both the equipment suppliers and their factory customers alike. Therefore, equipment models should make all E164-compliant data available.

To summarize, those who remember the complexity of implementing SECS-II before GEM came along (pre-1992) will understand this analogy: E164 is to EDA what GEM was to SECS-II.

  • Fab-specified Data

The second blog post made the following statement:

“In effect, the metadata model IS the data collection 'contract' between the equipment supplier and the fab customer."

“This is why the most advanced fabs have been far more explicit in their automation purchase specifications with respect to equipment model content, going so far as to specify the level of detailed information they want to collect about process performance, equipment behavior, internal control parameters, setpoints and real-time response of common mechanisms.”

You only have to read the latest requirements specs for these fabs to get more specifics. Pick the one from your customer base that sets the bar highest and let that be your target.

Data to Avoid in the Model

It is easy to fall into the mindset that if publishing some data through the EDA interface is desirable, the more data we can publish, the better. This is not always the case. In his fascinating book, The Paradox of Choice, Barry Schwartz makes the case that freedom is defined by one’s ability to choose, but more choice doesn’t mean more freedom. In fact, too many choices actually cripple one’s ability to choose. The same can be said of data published in an EDA interface. Making too much data available actually hinders the creation of EDA client applications.information-overload-1-1

We were recently working with a fab to perform a proof-of-concept where we connected an EDA client to a piece of equipment with an EDA interface. We were able to connect to the equipment in a matter of minutes, but finding suitable data to collect for our proof-of-concept took almost an hour because there was so much superfluous data published from the equipment.

Publishing everything including the kitchen sink reduces the ability to create an efficient EDA client application.

Some examples of data to avoid publishing in the model include:

  • Parameters that have no value – If a parameter is available in the model, but the value is not published by the equipment control application, that parameter is just extra noise in the interface. Consider not adding it to the model.
  • Parameters with values that do not change – If a parameter value does not change during the life of the application, it does not make sense to collect that parameter’s data. For example, if an application uses an equipment constant, it may not be necessary to publish that constant through the EDA model.
  • Irrelevant data – If a parameter contains data that is irrelevant to data publication, it should not be added to the model. For example, having parameters in the model that contain the IP address or port number for connection are not very useful in the equipment model. This information is necessary in connecting with an EDA client, but is not relevant for data collection in the model.

The takeaway: Publish data required by E164 and additional fab-specified data, but carefully evaluate other data to be published to make sure it is relevant and useful for data collection.

If you have questions about Equipment Data Acquisition or would like a demo of the functionality described above, please contact Cimetrix to schedule a discussion

You can download an introduction to EDA White Paper any time.

Read the White Paper

Topics: Industry Highlights, EDA/Interface A, Smart Manufacturing/Industry 4.0

EDA Implementation Insights: Competitive Differentiation

Posted by Alan Weber: Vice President, New Product Innovations on Feb 13, 2019 11:50:00 AM

people arrowIn the first blog of this series, Clare Liu of Cimetrix China made the compelling case for choosing a commercial software platform for implementing the equipment side of the EDA (Equipment Data Acquisition) standards interface rather than developing the entire solution in-house. 

Whenever this “make vs. buy” decision is discussed, however, the following question inevitably arises: “If we choose a standard product for this, how can we differentiate the capabilities of our equipment and its data collection capability from our competitors?” It’s a great question which deserves a well-reasoned answer.

Platform Choice and System Architecture

Most advanced fabs use EDA to feed their on-line FDC (Fault Detection and Classification) applications, which are now considered “mission-critical.” This means if the FDC application is down for any reason, the equipment is considered down as well. It is therefore important to choose a computing platform for the EDA interface that is highly reliable and has enough processing “headroom” to support the high bandwidth requirements of these demanding, on-line production applications. Moreover, this platform should not be shared by other equipment communications, control, or support functions, since these may adversely impact the processing power available for the EDA interface. 

Surprisingly, this approach is not universally adopted, and has been a source of problems for some suppliers, so it is an area of potential differentiation. 

Adherence to Latest Standards 

gold-thumbs-upThe automation requirements for the most advanced fabs call for the latest versions (Freeze II) of all the standards in the EDA suite, including the EDA Common Metadata (E164) standard. Dealing with older versions of the standard in the factory systems creates unnecessary work and complexity for the fab’s automation staff, so it is best to implement the latest versions from the outset. The Cimetrix CIMPortal Plus product makes this a straightforward process using the model development and configuration tools in its SDK (Software Development Kit), so there is absolutely no cost penalty for providing the latest generation of standards in your interface.

It takes time and effort for equipment suppliers with older versions of the standards to upgrade their existing implementations, so this, too, is an opportunity for differentiation.

Equipment Metadata Model Content

This is probably the area with the largest potential for competitive differentiation, because it dictates what a factory customer will ultimately be able to do with the interface. If an equipment component, parameter, event, or exception condition is not represented in the equipment model as implemented in the E120 (Common Equipment Model) and E125 (Equipment Self-Description), and E164 (EDA Common Metadata) standards, the data related to that element cannot be collected. In effect, the metadata model IS the data collection “contract” between the equipment supplier and the fab customer.

eye-with-maglassThis is why the most advanced fabs have been far more explicit in their automation purchase specifications with respect to equipment model content, going so far as to specify the level of detailed information they want to collect about process performance, equipment behavior, internal control parameters, setpoints and real-time response of common mechanisms like material handling, vacuum system performance, power generation, consumables usage, and the like. This level of visibility into equipment operation is becoming increasingly important to achieve the required yield and productivity KPIs (Key Performance Indicators) for fab at all technology nodes.

The argument about “who owns this level of information about equipment behavior” notwithstanding, providing the detailed information the fabs want in a structure that makes it easy to find and access is a true source of differentiation.

Self-Monitoring Capability

If you really want to set your equipment apart from your competitors, consider going well beyond simply providing access to the level of information needed to monitor equipment and process behavior and include “built-in” Data Collection Plans (DCPs) that save your customers the effort of figuring out what data should be collected and analyzed to accomplish this. Your product and reliability engineering teams probably already know what the most prevalent failure mechanisms are and how to catch them before they cause a problem… why not provide this knowledge in a form that makes it easy to deploy?

A few visionary suppliers are starting to talk about “self-diagnosing” and “self-healing" equipment… but it will be a small and exclusive group for a while – join them.

Readiness for Factory Acceptance

checklistBefore the fab’s automation team can fully integrate a new piece of equipment, it must follow a rigorous acceptance process that includes a comprehensive set of interface tests for standards compliance, performance, and reliability. This process is vital because solid data collection capability is fundamental for rapid process qualification and yield ramp that shorten a new factory’s “time to money.” If you know what acceptance tests and related software tools the fab will use (which is now explicit in the latest EDA purchase specifications), you can purchase the same software tools, perform and document the results of these same tests before shipping the equipment. 

This will undoubtedly speed up the acceptance process, and your customers will thank you for the effort you took to put yourself in their shoes. Incidentally, this usually means the final invoice for the equipment will be paid sooner, which is always a good thing.Red_smart_factory-TW

In Conclusion

In this posting, we have only scratched the surface regarding the sources of competitive differentiation. As you can see, choosing a commercial platform enables this far more readily than the in-house alternative, because it allows your development team to focus on the topics above rather than worrying about compliance to the standards. If you’d like to know more, please give us a call or click below to talk schedule a meeting. 

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Topics: Industry Highlights, EDA/Interface A, Doing Business with Cimetrix, Smart Manufacturing/Industry 4.0, Cimetrix Products

Why choose a commercial product for the EDA (Equipment Data Acquisition) interface solution for your equipment? 为什么要为您的设备选择商用EDA解决方案?

Posted by Clare Liu (刘波); Solutions Engineer on Nov 20, 2018 11:10:00 AM

Clare Liu, a Cimetrix Solutions Engineer, goes over the pros and cons of choosing a commercial product for EDA/Interface A vs. building a solution from scratch. Read it now in Chinese, or below in English. 



1. 经验

在半导体制造设备上实现EDA要求软件开发人员具有半导体行业标准(SEMI)和半导体设备的经验。这对大多数设备供应商来说是非常困难的。即使他们已经拥有良好的软件开发人员,经验丰富的工厂自动化工程师和一个完整的硬件设计团队,他们还是需要有效的共同协作,找出如何设计一个结构良好的设备模型(SEMIE120 CEM 通用设备模型规范)并将设备所有的变量、时间和报警映射到设备模型的各个节点上(SEMI E125 EqSD设备自我描述规范)。 一个商业的EDA解决方案能够同时为OEM提供这些知识,并且可以基于该设备,提供EDA开发过程的指导方针。

2. 验收

checkmark简单地实现EDA接口功能和正确有效地实现的结果是不一样的。我从中得到的教训之一是,我们花了几乎整整一年的时间来实现EDA Freeze I的各种功能,并为测试的需要开发了客户端软件。然而,当我们将我们的EDA解决方案发布给客户工厂时,他们使用权威的第三方测试软件产品对所有设备的EDA解决方案进行了验证。我们的实现最初没有通过验收,因为我们对EDA标准的理解与客户的理解有些差异。为此我们花了很长时间来逐一解决验收中遇到的问题。商业的EDA解决方案通常已经在许多工厂得到了验证,因此更加标准化。

gantt-chart-cimetrix3. 时机




5. 知识更新

由于很多改进得到认同,还有很多新的技术在关键产品中的使用变得可行,半导体行业的EDA标准每年都在发生变化,在写这篇文章的时候,一个新的EDA标准冻结版本Freeze III正在投票中。商业EDA解决方案通常会紧紧追随标准的发展,同时会不断根据其他工厂用户的请求增加新的功能。这使得OEM能够快速、可靠地响应客户的最新需求。








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View Presentation: Raising the Bar
View Video: Importance of Process Module Tracking
View Video: E164 EDA Common Metadata
View Video: Equipment Modeling - E120/E125
Learn about CIMPortal 

Lessons-Learned-smallThe focus of this blog posting is the decision that many semiconductor manufacturing equipment suppliers face when deciding how to address the automation requirements of their most advanced customers, namely, whether or not to buy a commercial software package that supports the SEMI Equipment Data Acquisition (EDA / Interface A) Standards, or to develop this capability in-house.

I am especially qualified to explain the pros and cons of choosing a commercial solution, having worked as the EDA standards implementation lead developer in an equipment supplier before joining the Cimetrix team earlier this year.

  • Pros

1. Experience

Implementing EDA on a single unit of semiconductor manufacturing equipment requires that the software developers have experience with both SEMI Standards and the equipment. This is very difficult for most equipment suppliers. Even if they have good software developers, experienced factory automation engineers and a complete hardware design team, they must still work together efficiently to figure out how to design a well-structured equipment model (SEMI E120 CEM) and map all the equipment variables, events and alarm to the CEM nodes (SEMI E125 Equipment Self-Description).  A commercial EDA package provides all this knowledge for the OEM and guidelines explaining the EDA development process for their systems.

2. Qualifications

checkmarkSimply being able to implement the EDA interface functions is not the same as implementing them in a robust fashion. One of my lessons learned is that we spent almost an entire year to implement the EDA Freeze I version of the standards and the client software required to test these functions. However, when we released the EDA interface to the factory customer, they qualified the EDA solution for all equipment modules with an authoritative third-party compliance testing software product. Our implementation failed at first because our understanding of the SEMI Standards specifications was different from the customer’s understanding. So we struggled for a long time to fix all the problems.  A commercial EDA package will necessarily have been proven in many sites and is therefore far more standardized.

3. Timing


A commercial EDA product can help the OEM develop a qualified EDA interface in a short time. Developing EDA in house adds time pressure to already tight delivery schedules, and if the requirements are coming from a new customer, the first equipment supplier supporting EDA standards may have an advantage. On the business side, EDA might be the key feature to get the order. On the technical side, the first usage may determine the approach used across the entire fab, thereby dictating operational requirements that the other equipment must meet in the production environment.

4. Service

Using a commercial EDA package normally includes good technical support from the software supplier; this may be covered in the initial license fee or as a separate support contract. This means the OEM company does not have to dedicate a large software team for maintenance and troubleshooting of software issues. Instead, they can rely on a professional support team, and not worry about what happens if any of the in-house developers leave the company.

5. Knowledge update

The SEMI EDA standards are changing every year as improvements are identified and new technologies become viable for mission-critical production usage. At this writing, a new Freeze III version is being balloted. A commercial EDA package will closely follow the standards as they evolve and provide new features according to the requests from other factory users. This enables OEMs to respond quickly and reliably to the latest feature requests from their customers.

  • Cons

1. Cost

OEM must pay for the commercial package licenses and possibly for the annual support.

2. Intellectual Property (IP)

Some OEM companies want to have full control of the EDA interface source code, so they choose to develop and own the software by themselves. Most commercial packages don’t provide source code with a basic license.

3. Bug fixing lead time

If bugs are found in the commercial package, the equipment engineers and perhaps even the factory customers may need to help the software supplier find the root cause. And they must also wait for the supplier to fix and release a new version of the software. This can be quite inconvenient.

If this is a decision your company is facing, get in touch with us – we’re happy to share our expertise and market knowledge and help you make a well-informed decision.

Schedule a Meeting

You also might be interested in the following information:

View Presentation: Raising the Bar
View Video: Importance of Process Module Tracking
View Video: E164 EDA Common Metadata
View Video: Equipment Modeling - E120/E125
Learn about CIMPortal 

Topics: EDA/Interface A, Customer Support, Doing Business with Cimetrix, Smart Manufacturing/Industry 4.0, EDA Best Practices

EDA Applications and Benefits for Smart Manufacturing Episode 6: Trace Data Analysis

Posted by Alan Weber: Vice President, New Product Innovations on Oct 25, 2018 11:20:00 AM

In this final article of the “EDA Application and Benefits” series we discuss an application that is one of the most basic and intuitive, but also provides the foundation for the many of the emerging capabilities in the machine learning and artificial intelligence (AI) domain—trace data analysis. Moreover, of all the applications we’ve introduced over the past 6 months, trace data analysis is the one that most directly leverages the capabilities of the SEMI Equipment Data Acquisition (EDA) standards

Problem Statement

When we ask fab process engineers and their supporting automation teams why they are now requiring the latest SEMI EDA/Interface A standards on their new equipment, the answer we hear most often is “To better understand equipment and process behavior.” And when asked why this cannot be achieved using the SECS/GEM interfaces, the answers are equally consistent: “The detailed information we need is either unavailable or cannot be collected at the frequencies we need to accurately see and characterize the behaviors we are interested in. And even if this were possible, we don’t have the operational freedom to change our data collection systems as quickly as our needs change, so we must have a more flexible approach.” 

What these engineers are looking for as a starting point is a way to easily specify a list of potentially related equipment parameters and collect their values at a rate that is fast enough to see how they are changing in relationship to one another. Human beings are wonderful at pattern recognition, and simply being able to juxtapose a set of signals on a “strip chart” display (see first figure below) can yield important insights into the underlying process. Of course, this capability is most useful when the engineer can precisely specify the timeframe of interest for this visual analysis. This is sometimes called data “framing” and can be accomplished by using equipment events to bracket the period of interest (see second figure below).



While humans may be good at pattern recognition, they quickly get overwhelmed when the number of parameters to view grows and/or the timespan to consider expands… which is where trace data analysis software enters the picture.

Solution Components

In addition to very flexible time-series data visualization tools, trace data analysis software packages must be able to “slice and dice” subsets of large data sets to compare every imaginable combination of equipment instance, process chamber, product, layer, recipe, fixture, consumable batch, shift, operator, … (you get the picture) to look for correlations between important factory metrics and the behavior of the equipment involved. Moreover, they must be able to identify and flag “abnormal” (which must be flexibly defined) situations for further analysis, since these may hold clues about incipient failures that traditional multivariate FDC (fault detection and classification) applications may not catch.

In fact, there is an emerging school of thought for fault detection that states “most of the time, the equipment is making good wafers, so unless there’s something very different about the tool behavior between the most recent lots and the current lot (as determined through trace data analysis), it’s very likely that the current lot is good as well.” This simplified approach has also been called “model-less FDC” because it mostly compares trace data signals rather than passing tool parameters into highly context-specific multivariate statistics-based models.

Of course, any trace data analysis application is only as good as the data that feeds it… which is where the EDA standards and the related equipment purchase specifications come into the picture.

EDA (Equipment Data Acquisition) Standards Leverage

Previous postings such as Episode 4 on Fault Detection and Classification and Precision Data Framing during Process Execution – Tricks of the Trade have highlighted the capabilities of the Freeze II EDA standards related to Data Collection Plans (DCPs) and the Trace Requests, Event Requests, and Exception Requests that comprise them. We have also highlighted the need for broad stakeholder involvement when creating the EDA section of an equipment purchase specification and described the process we’ve crafted to accomplish this.

However, to fully support a world-class trace data analysis application, it’s important to understand what to ask of the equipment suppliers. To this end, we’ve excerpted some key sample requirements from a typical purchase specification below.

  • Equipment Model Content (SEMI E120, E125, E164)

    • The hierarchical depth of the metadata model should include at least the “field replaceable unit” (FRU) level, and one of two levels below this for complex sub-systems.
    • The metadata model must contain command and status information for all equipment components that affect material movement. This includes not only material transfer elements such as robot arms, but also devices that may inhibit/enable material movement, such as gate valves, interlocks, etc.
    • The metadata model must include control parameters for all significant operating mechanisms and subsystems in the equipment. The control parameters may include but are not limited to: process variable setpoints and status values; control variable status values; PID tuning parameters, control limits, and calibration constants.
    • The metadata model must include whatever additional usage counters, timers, and other parameters that may be useful in time-based, usage-based, and condition-based maintenance scheduling algorithms.
    • The metadata model must contain parameters the describe consumption rates and levels for key process resources such as electricity, process gases, and other consumables. These are used in some of the FDC models to detect potentially abnormal process conditions.
    • Suppliers must provide a written description of the update rates, recommended sampling intervals, normal operating ranges and behaviors, and high/low/rate-of-change limits for all key process parameters.
    • Etc.

  • Data Collection Capability (SEMI E134)

    • Equipment must include built-in DCPs to support common equipment performance monitoring, diagnostic, and maintenance processes that are well known to the supplier. Documentation for these DCPs must define their purpose, activation conditions, interface bandwidth consumed, and the types of analysis the collected data enables.
    • Equipment parameters provided through the EDA interface must exhibit a number of data quality characteristics, including, but not limited to: an internal sampling/update rate sufficient to represent the underlying signal accurately; timing of trace reports that is consistent with the sampling interval within +/- 1.0%; values in adjacent trace reports must contain then-current values at the specified sampling interval; and rejection of obvious outliers.

  • Performance Requirements

    • Performance requirements will be expressed as combinations of sampling interval, # parameters per DCP, # of simultaneously active DCPs, group size, buffering interval, response time for ad hoc “one-shot” DCPs, maximum latency of event generation after the related equipment condition occurred, consistency of timestamps in trace reports with the specified sampling interval, and perhaps others.
    • Example: The EDA interface must be capable of reporting at least 5000 parameters at a sampling interval of 0.1 seconds (10Hz) with a Group Size of 1, for a total data collection capacity (bandwidth) of 50,000 parameters per second. It must also support simultaneous data collection from at least 5 clients while still achieving a total bandwidth of 50,000 parameters per second; Group Sizes greater than 1 may be used to achieve this level of performance.
    • Some equipment types may have more stringent performance requirements than others, depending on the criticality of timely and high-density data for the consuming applications.

apc2017_5KPIs Affected

Trace data analysis will undoubtedly take its place among the other “mission-critical” applications in today’s fabs because of the increasing process complexity and the need to maintain the traditional “time to yield” production ramp. This is especially true for the industry pioneers now using the latest EUV scanners, as there will be much to learn about this new technology in the coming years.

Let Us Hear from You!


If you want to understand how the latest EDA standards and trace data analysis can support your future manufacturing objectives, or how to make this a reality in your Smart Manufacturing roadmap, please schedule a meeting!

Schedule a Meeting

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

EDA Applications and Benefits for Smart Manufacturing Episode 5: Fleet Matching and Management

Posted by Alan Weber: Vice President, New Product Innovations on Sep 5, 2018 10:30:00 AM

In the fourth article of this series, Fault Detection and Classification, we highlighted the application that has been the principal driver for the adoption of EDA (Equipment Data Acquisition) standards across the industry thus far, namely Fault Detection and Classification (FDC). In this posting, we’ll discuss another important application that effectively leverages the capabilities of the EDA standard: Fleet Matching and Management. 

Problem Statement

The problem that fleet matching (which also covers chamber and tool matching) addresses is maintaining large sets of similar equipment types at the same operating point in order to maximize lot scheduling flexibility by the real-time scheduling and dispatching systems that run modern wafer fabs. This avoids the situation where specific equipment instances are dedicated to (and therefore reserved for) critical layers of certain products, processes or recipes, which can reduce the effective capacity of the affected process area. This situation can arise because tools naturally “drift” apart over time, especially when manual adjustments are made to the equipment, or other factors (maintenance actions, consumable material changes, key sub-system replacements, etc.) affect the equipment’s operating envelope. eda5.1

Of course, part of the problem is choosing which equipment should be the one matched to—the so-called “golden tool.” And depending on the breadth of the fab’s product/process mix, there may be multiple targets to choose from, further complicating the task. 

Solution Components

The solutions for many of today’s complex manufacturing problems require lots of high-quality equipment data, and fleet matching is no exception. Like FDC, choosing the golden tool(s) also requires some information about which recent lots exhibited the highest yields, which must be correlated with the equipment used throughout the process. Unlike FDC, however, it is NOT necessary to build hundreds (if not thousands) of multivariate fault models specific to the various context combinations, because the underlying principle of chamber/tool/fleet matching is that “if all the fundamental operating mechanisms of a set of equipment are working consistently, then the behavior of the equipment in aggregate should likewise be consistent.” This means that the matching process can be largely recipe independent, which is a major simplification over other statistically based applications.

This is not as simple as it may first appear, because a complex equipment may have scores of these mechanisms (pressure/flow control, multi-zone temperature control, motion control, power/phase generation, etc.) for which thousands of parameters must be collected to characterize and monitor equipment behavior accurately. Static and dynamic equipment configuration information also comes into play, since similar (but not identical) tools may be interchangeable for certain processes. 

This is where the EDA standards enter the picture.

EDA Standards Leverage

Although not explicitly required by the SEMI EDA standards, the intent and expectation of its designers was to support a far richer (read “more detailed”) equipment metadata model than is practical in most SECS/GEM implementations. With respect to fleet matching and management, this would include not just the high-level status variables for key equipment mechanisms (listed above), but also the setpoints, internal control parameters, and detailed status of their underlying components. 

The metadata model must also include the complete set of equipment constants that govern tool operation, since these “constants” are sometimes changed “on the fly” by an operator within some allowable range. While this may be an acceptable production practice, it nevertheless affects the tool’s operating window, and must be accounted for in the matching algorithms.EDA5.2-667640-edited 

Moreover, the communications interface should support sampling and data collection of these detailed parameters at a frequency sufficient to observe the complete real-time operation of these mechanisms so the process and equipment engineers can more deeply understand how the equipment actually works. Support for this level of equipment visibility was also a stated requirement for the EDA standards.

Once this data is collected, a variety of analysis tools can look for similarities and anomalies in the equipment parameters to identify the factors that matter most in achieving consistent process performance. At this writing, a number of companies are looking at this domain as an ideal application for Artificial Intelligence and Machine Learning technology. Stay tuned for exciting developments in this area. 

KPIs Affected

The KPI (Key Performance Indicators) most impacted by the fleet matching and management application is overall factory cycle time, since the scheduling systems can make optimal use of all available equipment to move material through the fab.Accelerate gains, reduce costs

Equipment uptime is also improved, because the continuous equipment mechanism “fingerprinting” process which is fundamental to fleet matching also catches potential problems before they cause the entire tool to fail. Finally, when more equipment instances are available for running experimental lots (rather than having dedicated tools for this), the yield ramp for new processes can be shortened as well.

If keeping a large set of supposedly identical equipment operating consistently is a challenge you currently face, give us a call. We can help you understand the approaches for building a standards-based Smart Manufacturing data collection infrastructure to support the machine learning algorithms that are increasingly prevalent in this latest generation of manufacturing applications… including fleet matching and management. Smart Factory

To Learn more about the EDA/Interface A Standard for automation requirements, download the EDA/Interface A white paper today.



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

한국에서의 EDA 연착륙을 위한 3 차 세미나 개최; Hosting the third seminar for soft landing of EDA in Korea

Posted by Hwal Song on Aug 15, 2018 11:04:00 AM

Hwal Song of Cimetrix Korea talks about EDA/Interface A and Korean Equipment Makers. Read now in Korean or below in English.


Cimetrix Korea와 국내 파트너사인 링크제니시스는 EDA에 대한 세미나를 7 월 19 일에 개최했습니다. 삼성, SK 하이닉스를 포함한 글로벌 반도체 제조사들이 공정 장비의 추가 통신 프로토콜로 EDA를 채택함에 따라 EDA가 더욱 각광을 받게 되면서 개최한 세번째 세미나였습니다. 지금까지 200 명이 넘는 엔지니어가 이들 세미나에 참석하였으면, 이에 따라 한국에서의 EDA 연착륙이 진행 중입니다. 이들 세미나의 목적은 EDA의 이해부족로 오는 시행착오를 줄이고 첫번째 EDA구현을 가장 빠른 시간에 구현하기 위함입니다.

반도체 제조사의 EDA 채택은 차세대 분석 기능을 구현하고 딥러닝 및 머신 러닝 등과 같은 빅 데이터 및 AI의 새로운 기술을 수용하기 위한 주요 노력의 일환입니다. 대부분의 공정장비들이Freeze II 및 E164가 포함된 EDA 기능의 장착이 요구되거나 요구될 예정이여서,  Cimetrix Korea는EDA의 일반적인 개념뿐만 아니라 심도 있는 구현 방법론에 대한 이해를 위한 도움이 각 장비 제조사의 소프트웨어 엔지니어들에게 필요함을 인지하였습니다. 이러한 요구를 충족시키기 위해 다음과 같이 내용으로 세미나가 준비되었습니다.

  • EDA관련 업계 동향 및 채택 현황 -  E164의 중요성 포함
  • 반도체 제조사가 EDA 사양을 어떤 과정을 거쳐 준비하는가?
  • 장비제조사의 소프트웨어팀 관점에서 EDA 구현의 모범 사례와 방법론
  • 여러 장비제조사의 소프트웨어팀을 코칭한 컨설팅 및 지원 팀의 관점에서 EDA 구현 모범 사례와 방법론
  • 구현중이거나 구현된 EDA 적합성 테스트의 모범 사례

활발한 토론과 Q&A를 통해서 한국의 장비 제조사들의 EDA에 대한 높은 관심을 엿볼 수있는 행사였습니다.

궁금한 점이 있으시면 언제든 연락주시기 바랍니다.

Hwal Song

Cimetrix Korea and our local partner, Linkgenesis, held a seminar about SEMI EDA on July 19, the third one since 2016. EDA continues to gain momentum as global chip makers like Samsung and SK hynix have adopted EDA as an additional communication protocol for process tools. So far, over 200 engineers have attended these seminars, promoting the soft landing of EDA in Korea. Their goals include minimizing trial and error due to the lack of understanding on EDA, and speeding up the first deployment of EDA.


Adoption of EDA by chip makers is one of the major efforts for factories to implement their next-generation analytic capabilities and also embrace new technologies from big data and AI such as deep learning and machine learning. As most process tools are or will be required to ship with EDA capability, with Freeze II and E164, Cimetrix Korea recognized that Korean software engineers employed at equipment makers were looking for help in understanding in-depth deployment methodologies as well as understanding the general concept of EDA. In order to accommodate these needs, our seminars have been put together with following agenda:

  • General industry trends of EDA and its adoption – the importance of E164
  • Koreablog-1How an EDA specification is put together by a chip maker
  • Best practices & methodologies for implementation of EDA – from the perspective of a software team at a tool maker
  • Best practices & methodologies for implementation of EDA – from the perspective of a consulting and support team who have coached many software teams in tool makers
  • Testing best practices during and after EDA implementation

Active discussions and Q&A showed the high level of interest in EDA among Korean equipment makers. 

Please feel free to contact us whenever you have any questions.

Hwal Song

Topics: EDA/Interface A, Doing Business with Cimetrix, Smart Manufacturing/Industry 4.0

SEMICON West 2018 Standards Committee Meeting Updates

Posted by Brian Rubow: Director of Solutions Engineering on Jul 18, 2018 12:30:00 PM


During the SEMICON West exhibition in San Francisco this past week (July 9-10), the North American Information & Control Committee and its Task Forces met to continue SEMI standards development. Here is a brief summary of the proceedings.

The GEM 300 task force, in addition to reapproving E90, also approved minor title changes to the E39, E39.1, E40 and E40.1 standards. Each SEMI standard must be revised or reapproved to avoid becoming inactive. A few years ago, SEMI changed regulations that mandate that each standard declare its classification, such as a “guide” or “specification”. Since then the task force has been slowly correcting the titles. The E37.1 standard is in the middle of such classification, but has been riddled with reapproval complications due to minor concerns and some needed corrections in the standard. The ballot to make these corrections, 6349, failed for the second time at SEMICON West. The ballot will be slightly reworked and resubmitted for another round of voting. Another ballot, 6348 proposed to clean up the GEM E30 standard, to improve its readability and to bring the standard in conformance with current SEMI regulations and its current style guide. The forefront of the discussions was surrounding the confusing use of acronyms DVNAME, DVVAL, SVV and other such acronyms where the meaning and use of the acronyms was confusing to new readers. The 6348 ballot also failed, but hopefully the task force is progressing towards reaching an agreement. One major challenge is that ballot 6348 is a major revision ballot, where the entire specification is opened up for review and scrutiny, as opposed to line item ballots where only specific sections of a standard are modified.

Finally, and most exciting is ballot 6114B; a revision to the SECS-II E5 standard. The ballot proposed a set of new messages for transferring any large items between a host and equipment. Typically, one item in a message is limited to about 16.7 MB. The new messages are specifically targeting the transfer of equipment recipes, but the messages are written generic enough so that anything else can be transferred, too. The new messages support two styles of item transfer. Either the item can be transmitted in a single message, or broken into parts for transfer with the expectation to be concatenated by the recipient. Or the item can be transmitted in multiple messages, broken into parts with each part sent in a separate message and the same expectation to be concatenated by the recipient. An item is identified by its “type”, “id” and “version”. The messages are intended to resolve current issues with recipes where some equipment suppliers are using recipes that surpass 16.7 MB. And the messages open the door to be used by other SEMI standards and to be customized for specific applications. After passing this ballot, the task force intends to make the messages part of the GEM standard. Even though the ballot 6348 failed, the task force seems to have finally reached consensus on the message formats and continues to work out minor details.

The DDA Task Force continues to work on the next version of the Equipment Data Acquisition (EDA) standards. In the latest cycle of voting, changes were proposed to E138 (ballot 6336), E134 (ballot 6335) and E132 (ballot 6337). Although one part of E134 passed, most of E134 failed and the other ballots failed. All of the failed ballots will be reworked and resubmitted for voting. Additionally, during the task force meeting additional proposed changes were reviewed and discussed. The task force continues to make plans to move from HTTP 1.1 and SOAP/XML to HTTP 2.0 and Protocol Buffers. Specifically, the plan is to recommend using gRPC. Testing done to date indicated an 18 times performance improvement and significant bandwidth reduction. The task force also discussed changes to simplify the equipment model metadata handling. Finally, Cimetrix proposed the implementation of a new method of data sampling designed for higher data collection frequencies. The current trace data collection messages, while very effective for speeds up to maybe 80 Hz, become inefficient when trying to collect data at even faster rates. The concept is called a “cached data sample” where the equipment collects the data at a specified frequency and then reports the data in an array syntax. When using HTTP 2.0 and Protocol Buffers, this will be an especially efficient format expected to allow much higher frequencies.

The client specifies the data collection frequency as well as the reporting frequency. For example, a client might specify a frequency of 10 kHz and a reporting frequency of 1 s, where 10,000 data samples would be reported each second. Such proposal if accepted, combined with the faster Protocol Buffer, will open the door for a number of new data collection applications.

A lot of people are wondering when EDA freeze III will be done. Probably not until late next year. How soon this happens mostly depends on how efficiently task force members provide feedback on the ballot drafts.

Subscribe to our blog in the upper right corner of this page to be sure not to miss that or any of my future updates on the North American Information & Control Committee.

Topics: Industry Highlights, Semiconductor Industry, EDA/Interface A, Events

SEMICON West 2018 Pre-Show

Posted by Kimberly Daich; Director of Marketing on Jul 5, 2018 12:29:00 PM

SEMICON West 2018 Beyond SmartSEMICON West 2018 is fast approaching and the Cimetrix team is gearing up for a great show.  The show runs from July 10th – 12th at the Moscone Center in San Francisco and we’re looking forward to meeting with all our present and future clients.

This year SEMICON West is unveiling the new Smart Manufacturing Pavilion to showcase the entire manufacturing process from silicon to systems, including Front End, Back End and PCB Assembly. Cimetrix is excited to announce that we are a sponsor and will be participating in the Smart Manufacturing Pavilion showcase, both as part of the Front End segment as well as in the PCB Assembly area.

The Smart Manufacturing Pavilion includes a “Meet the Experts Theater” featuring presentations from two of our own Cimetrix thought leaders.  Alan Weber will present “Making Smart Manufacturing Work: The Stakeholder-driven Requirements Development Process” on Wednesday, July 11th at 11:00 am. This process has already been used successfully to support the significant growth of SEMI EDA standards usage in Asia, but is equally relevant for a wide range of related Smart Manufacturing technologies.

Later on Wednesday afternoon at 3:00 pm, Ranjan Chatterjee and Dan Gamota of Jabil will present “Convergence of Technologies and Standards Across the Semiconductor, SMT and OSAT Segments.” 

Cimetrix will be exhibiting at booth #1122 in the South Hall, just a short walk from the Smart Manufacturing Pavilion. Stop by our booth or find us at the Pavilion to talk to our experts about your specific needs. We will have onsite product demonstrations as well as information about our company available.  You can also schedule in advance a time to meet with us at the show by filling out a quick form with your meeting request.  

Schedule a Meeting

See you at SEMICON!

Topics: Semiconductor Industry, EDA/Interface A, Events, Smart Manufacturing/Industry 4.0, SMT/PCB/PCBA

European Advanced Process Control and Manufacturing Conference XVIII: Retrospective and Takeaways

Posted by Alan Weber: Vice President, New Product Innovations on Jun 13, 2018 11:30:00 AM

apcm-2018-1Cimetrix participated in the recent European Advanced Process Control and Manufacturing (apc|m) Conference, along with over 160 control systems professionals across the European and global semiconductor manufacturing industry. The conference was held in Dresden, a beautiful city in the Saxony state of Germany which was the site of the original European conference in 2000 and host to this annual event many times since.


This conference, now in its 18th year and organized by Silicon Saxony, is one of only a few global events dedicated to the domain of semiconductor process control and directly supporting technologies. The participants represented all links in the semiconductor manufacturing value chain, from universities and research institutes to component, subsystem, and equipment suppliers to software product and services providers to semiconductor IDMs and foundries across a wide spectrum of device types to industry trade organizations – something for everyone. 

As usual, the conference was very well organized, and featured a wide range of high-quality presentations, keynote addresses, and tutorial sessions. 

Highlights of the conference included the following:

  • apcm-2018-4“FDC to the power of 2 – how it got us to the next level of manufacturing excellence“ by Jan Räbiger of GLOBALFOUNDRIES – one of a number of long-time thought leaders in the development and application of APC technology, Jan described the latest phase of FDC system evolution, which includes broad use of the EDA/Interface A standards to zero in on recipe step-specific anomalies that had previously escaped detection.
  • “Applying the Tenets of Industrie 4.0 / Smart Manufacturing to Microelectronics Next Generation Analytics and Applications“ by James Moyne (University of Michigan / Applied Materials) – James presented a very nice decomposition of the domain into 6 topic areas (Big Data Environment, Advanced Analytics and Applications, Supply Chain Integration, CPS/IIoT, Cloud Computing, Digital Twin) and explained our industry’s relative status and recommended actions in each. one of the conclusions from his very disciplined treatment of the topic is that “Smart Manufacturing is essentially a connectivity problem” – and we couldn’t agree more!
  • “Lithography Control is Data Hungry” by Tom Hoogenboom of ASML – his illustration of just how precise litho metrology has become was brilliant: controlling exposure and registration at the 5nm node on a 300mm substrate is like moving your chair in the conference meeting room by 1 mm and having an airborne observer of a 300km diameter region know it happened!apcm-2018-5

Finally, as in many prior years, Cimetrix was privileged to present at this conference, as Alan Weber delivered a talk entitled “EDA Applications and Benefits for Smarter Manufacturing.” This presentation described the potential use of SEMI EDA (Equipment Data Acquisition) standards to improve the performance and benefit of a range of manufacturing applications; it also included a specific ROI case study for the use of EDA in the all-important FDC (Fault Detection and Classification) application to reduce the false alarm rate and the severity of process excursions. If you want to know more, you can request to view a copy of the entire presentation.

However, it wasn’t all work and no play… The local sponsors, GLOBALFOUNDRIES, Infineon, and XFAB, hosted the conference banquet at the picturesque Adam’s Gasthof in the nearby city of Moritzburg.


In addition to all the food and libation one could possibly consume, the participants were feted with a torchlight walking tour of the town and its iconic Moritzburg Castle. All in all, German hospitality and history at its best.  


The insights gained from these and the other 30+ presentations are too numerous to list here, but in aggregate, they provided an excellent reminder of how relevant semiconductor technology has become for our comfort, sustenance, safety, and overall quality of life.

This (apc|m) conference and its sister conference in the US are excellent venues to understand what manufacturers do with all the data they collect, so if this topic piques your interest, be sure to put these events on your calendar in the future. In the meantime, if you have questions about any of the above, or want to know how equipment connectivity and control fit into the overall Smart Manufacturing landscape, please contact us!

Topics: EDA/Interface A, Events