Industry News, Trends and Technology, and Standards Updates

The Interface A / EDA standards define powerful methods for collecting data from an equipment control application. The data collection can be as simple as querying values of a parameter or two, or as complex as gathering thousands of parameter values across multiple reports. EDA specifies the use of internet standard messaging protocols like HTTP, XML and SOAP messages for collecting this data.

It is possible to define so many data collection plans gathering so much data that the sheer amount of data causes network performance to degrade. To remedy this situation, the EDA standards provide ways of sending the data in “chunks,” which dramatically improves the performance of XML over HTTP.

Two methods for sending data in chunks are grouping and buffering.

Grouping

Grouping only applies to individual Trace Requests within a Data Collection Plan (DCP).  If I have a trace request with an interval of one second, a group size of 1 would generate a report every second and send it across the wire. If I change my group size to 10, a report would still be generated every second, but the report would not be sent across the wire until 10 reports have accumulated. Each report has its own timestamp and they are arranged in the order they occur. The following diagram shows a trace data collection report with a group size of 3.

Buffering

Buffering is different from grouping in that the buffer interval (in minutes) applies to an entire DCP rather than individual trace requests within that plan. For example, if I have a DCP with three trace requests and two event requests defined with a buffer interval of 1 (meaning one minute), the trace reports would still be generated at the specified trace interval. Event reports would be generated as the events are triggered. The reports are not sent to the EDA client until the buffer interval expires. At that point, all the data reports that were generated within that buffer interval time are packaged and sent to the EDA client.

Combining Grouping and Buffering

Grouping and buffering can be combined as well. Groups are still defined on a per trace basis. If a group size has not been met when the buffer interval expires, the group report will be in the next buffer report that is sent.

Summary

With the provision for transmitting data in blocks, using grouping for trace data reports and/or buffering for all data reports, EDA is well suited for collecting large amounts of data without having a negative effect on network performance.  

Over the past several months, we have posted a number of blogs dealing with the testing of SEMI’s Equipment Data Acquisition (EDA / aka Interface A) standards suite. The first of these posts connected the importance of this topic to the increased adoption of the EDA standards across the industry, and broke the overall problem domain into its three major components. 

Subsequent postings provided additional detail in each of these areas:

• Compliance testing – does the equipment adhere to the specifications described in the SEMI Standards? 

• Performance and stability testing– does the equipment meet the end users’ performance and availability specifications? 

• Equipment metadata model conformance testing – does the equipment model delivered with the interface represent the tool structure and content anticipated by the end customer? 

To bring this series to a close, this post addresses the “as-is” state of EDA testing as it is practiced today by the advanced semiconductor manufacturers who are requiring EDA interfaces on new equipment purchases and the suppliers who provide that equipment. 

For compliance testing, the three options in general use include: 

1. ECCE Plus product- this software tool was originally developed under contract with the International Sematech Manufacturing Initiative (ISMI) to validate the fidelity, usability, and interoperability of early versions of the standard; it can used to manually execute a set of procedures documented in the “ISMI Equipment Data Acquisition (EDA) Evaluation Method for the July 2010 Standards Freeze Level: Version 1.0” document (see title page below) to exercise most of the capabilities called for in the standard; note that this is the only commercially available solution among the three.

1. Company-specific test suites – one major chip manufacturer (and early adopter of EDA) maintains its own partially-automated set of compliance tests, and provides this system to its equipment suppliers as a pre-shipment test vehicle. This set of tests is then used in the fab as part of the tool acceptance process; however, this system also includes a number of company-specific automation scenarios, which are not available for outside use. This highlights the need to support custom extensions in an industry-validated tester if it is to be commercially viable.

2. In-house custom test clients – this is a variation of #2 that some of the major OEMs have chosen as their economies of scale dictate; the problems with this approach are that a) the test clients must be kept current with the EDA standards, which are themselves a moving target, and b) unless thoroughly validated by the eventual customers of the equipment, there is no guarantee that passing these tests will satisfy the final acceptance criteria for a given factory. 

For performance and stability testing, there are no automated solutions currently available. The ISMI EDA Evaluation Method does describe some rudimentary performance evaluation procedures, but these no longer reflect the expectations of the customers with many years of accumulated EDA production experience. Clearly a better solution is needed.

Finally, for metadata model conformance testing, the only available solution is the Metadata Conformance Analyzer (MCA) that was commissioned by Sematech and implemented by NIST (National Institute of Standards and Technology). It has not been updated in almost five years, and exhibits a number of known issues when applied to a SEMI E164-compliant equipment model (E164 = Specification for EDA Common Metadata), so it will be increasingly insufficient as more companies require full Freeze II / E164 specification compliance. 

The good news in all this is that Cimetrix has recognized and anticipated this emerging need, and is actively addressing it on our product roadmap. If you want to know more about EDA testing and/or discuss your specific needs, please contact Cimetrix for a demonstration of this exciting new capability!

The focus of the most recent SYSTEMA Expert Day, held during a snowy week in Dresden in late January 2016 in conjunction with the 13^th annual innovationsforum, was “200mm Fab Enhancement” and featured a number of presentations from Systema GmbH customers and partner companies.

By way of background, there are a number of reasons for the emphasis on 200mm fab enhancement, most notably that many of these factories are enjoying a renaissance of business to meet the growing demands for IoT (Internet of Things) devices. Moreover, since the drivers for this market segment include cost, variety, and volume, the automation and operations people in these factories are faced with a new combination of challenges not seen in earlier markets.

Cimetrix’ contribution to the event was a presentation titled “Equipment Data-Driven Continuous Improvement for 200mm Fabs,” which outlined a model-based, ROI-driven approach for adding equipment data collection capabilities to existing factories. Our basic premise is that such an approach helps meet some of the automation challenges in an incremental, cost-effective way without requiring major redesign of the factory or equipment control systems.

Since the term “model” is used in many different contexts, we first clarified what this term means in the context of SEMI equipment communications standards, and how this evolved over the past three decades. This was accomplished using a natural language analogy, which is shown in the figure below. Note that the culmination of this process to date is the EDA (Equipment Data Acquisition) metadata model called for in the latest generation of standards, which is very prescriptive in terms of structure, content, and naming conventions for the elements of a semiconductor manufacturing equipment. And even thought the specifics of this model were designed with 300mm wafer fab equipment in mind, the principles well apply to all substrate sizes, and even to the types of material, processes, and equipment found in back end assembly and test factories.

After establishing the value of explicit models for representing equipment, sensors, and other key items in a manufacturing environment, we next introduced concept of an ROI-driven strategy for evaluating the relative benefit of various data collection projects. This strategy first identifies and ranks the key manufacturing objectives that must be addressed, then poses the questions that must be answered to meet those objectives. It then identifies the data sources for the information required to answer those questions, and the data collection techniques (including software) applicable to those sources. Finally, since the original objectives can change with time and additional knowledge, they should be re-examined periodically, giving the strategy an iterative aspect as well.

In order provide specific examples for the uses of equipment data in a continuous improvement program, the presentation listed a number of application use cases that have been successfully deployed in 200mm facilities. These included (in general increasing order of complexity) substrate tracking, process execution tracking, product time measurement (aka wait time waste analysis), external sensor integration, component fingerprinting, and product traceability.

A couple of these were then explained in more detail, showing how a basic tracking application could start by using a small subset of the equipment data, and then evolve over time to provide more advanced functions (and benefit!) as more detailed information was made available.

For those who want to understand this process in more depth, you are welcome to download the entire presentation using the link below, or call us to discuss how we can apply these ideas to your company!♦

“Equipment Data-Driven Continuous Improvement for 200mm Fabs"

December 16-18 in Tokyo, SEMI played host to SEMICON Japan that was co-located with the WORLD OF IOT, a special “show-within-a-show” dedicated to the Internet of Things usages that are propelling the next generation of microelectronic advances. SEMICON Japan is of note as Japan has the world’s largest installed fab capacity with more than 4.1 million 200mm equivalent wafers per month representing a high product mix.

Over 60,000 visitors attended the three-day event who met with nearly 800 exhibitors; attended forums, technical sessions, and networking events; and had the opportunity to see new innovations and technologies within the industry.

One highlight of the show was the Sustainable Manufacturing Pavilion. The pavilion focused on 200mm fab capacity where increased demand from IoT devices is anticipated. Revamping of the existing capacity and building cost-conscious capacity will be key to the sustainable growth of the industry. Sustainability in microelectronics manufacturing is quickly moving from a minor area of focus to a major consideration in business planning. Forward-thinking device makers, materials suppliers, and equipment manufacturers are all beginning to understand sustainable manufacturing makes economic sense for the future.

The pavilion offered many related sessions throughout SEMICON including the SEMI Technology Symposium Test Technologies for Automotive Semiconductors; the SEMI Technology Symposium on DFM in the Trends towards Fabless/Foundry Manufacturing and Alliances; the SEMI Technology Symposium on The Dreams and Reality of TSV/2.5D/3D Packaging; and a Sustainable Manufacturing and High Tech Facility Forum.

This year’s SEMICON Japan also featured a Manufacturing Innovation Pavilion that showcased inventive processes, equipment, manufacturing, components, and materials technologies that enable smarter and faster—yet cheaper—semiconductor devices to create our advancing society, industry, and life. The pavilion demonstrated that developing microelectronics technologies that will make the IoT possible requires continued innovation in semiconductor manufacturing equipment, materials, and components.

In conjunction with the Manufacturing Innovation Pavilion, SEMICON conducted a Semiconductor Executive Forum, a Lithography Business Forum, and a Manufacturing Innovation Forum to exchange ideas and share knowledge about the topics featured in the pavilion.

The WORLD OF IOT brought together leading global electronics and microelectronics companies whose innovations are driving the expansion of mobile technologies, cloud computing, and network-connected devices. Held in conjunction with SEMICON Japan, WORLD OF IOT was a "show-within-a-show". Exhibitors included such noteworthy companies as Tesla Motors, Toyota Motor Corporation, and Intel KK that demonstrated current projects and developing technologies. Executive forums and technical sessions were also offered everyday during the show.

Cimetrix was proud to be represented by our two distributors in Japan, Meidensha Corporation and Rorze Corporation, who both featured our SECS/GEM and EDA product lines. For Rorze, 2015 has been a significant year, the company celebrated its 30^th anniversary. Stay tuned for my upcoming blog about its amazing anniversary celebration.

SEMICON Japan 2015 made a great end cap to the year as it focused so heavily on where the semiconductor industry is headed. Hopefully all the SEMICONs in 2016 will continue to be forward-looking as we here at Cimetrix are and remain focused on seeing how managing big data is becoming an ever more important issue within manufacturing. For more information on how EDA/Interface A is equipped to manage data acquisition in fabs, click here.♦

In my October 27th blog, I wrote about the Equipment Automation topic shown in the figure below and stressed the importance of developing good equipment purchasing specifications from the outset to ensure the company’s manufacturing objectives can be met. Given the number of EDA pilot and production projects currently active across the industry, it’s likewise important to consider what kind of Factory System Infrastructure will be necessary to support a full-scale EDA deployment… so the purpose of this posting is to highlight this topic for the semiconductor manufacturing IT professionals who may face these challenges soon.

However, before diving into a detailed design process for an EDA factory system, you must decide what overall system architecture will govern that design. A number of factors go into this decision, including 1) the functional requirements that distinguish EDA-based data collection from other more traditional approaches, 2) technology constraints of the existing factory systems, 3) budget limitations, 4) schedule requirements, and especially 5) the non-functional requirements (scalability, performance, reliability, ease-of-use, etc.) that often make the difference between success and failure of a given system.

Each of these factors deserves a thorough treatment of its own, but since we were invited to address this topic at a recent seminar sponsored by SEMI Taiwan, we’ve assembled an overview presentation entitled “Factory Systems Architectures for EDA” that you can use as a starting point. It not only covers in more depth the requirements above which drive key architectural decisions, but also suggests what some of the major architectural components of a production system would need to be, based on the experience Cimetrix has gained working with the earliest adopters of EDA across the semiconductor device maker and equipment supplier communities. These include provisions for handling the scores of equipment metadata models that will exist in a production facility, for creating and managing the thousands of data collection plans that are resident at the equipment instances themselves, for monitoring and maintaining the overall performance of a system with such inherent flexibility, and for a number of other examples. Finally, the presentation describes some high-level examples of architectural “styles” that have been implemented in the industry thus far.  

We sincerely hope you will download this presentation and its companion “The Power of E164: EDA Common Metadata” that was also presented at the SEMI Taiwan event, and contact us when you want to know more about any of these topics.♦

Cimetrix participated in the recent Advanced Process Control (APC) Conference in Austin, Texas, along with more than 120 control professionals across the semiconductor manufacturing industry. This conference, now in its 27^th year, is one of only a few global events dedicated to the domain of semiconductor process control and directly supporting technologies, so it was encouraging to see its attendance and energy level rebound from its low water mark a few years ago. The calendar may have indicated it was fall, but nobody told the weather forecasters… Austin set temperature records that week, even hitting 99°F one day!

Given the importance of high quality equipment data for all types of equipment- and factory-level process control applications, it is vital that Cimetrix and its customers understand the current requirements and future direction of this industry segment. Many presentations addressed these topics indirectly, but perhaps the newest insights in this regard came not from the wafer fabrication processes, but rather from the Back End, OSAT (Outsourced Assembly and Test), and advanced packaging segments.

As evidence, a number of presenters mentioned the growing need for equipment data collection in these areas, and cited the following reasons: 1) increasing demands by the consumer product manufacturing customers of these facilities (especially smart phone providers, but others as well) for equipment data to support their product quality and supply chain optimization initiatives; 2) emphasis on the Overall Equipment Effectiveness (OEE) productivity metrics, and the event/status data needed to support their automated calculation; 3) broader deployment of multi-variate Fault Detection and Classification (FDC) applications, which require more equipment trace data parameters than have typically been collected from back end equipment; and finally, 4) actual feedback control based on back end metrology – the best example of this presented last week was an application on dicing equipment that showed how kerf data collection and analysis can be used to adjust saw process parameters

The takeaway for Cimetrix in all this is that the back end equipment suppliers will need to anticipate this demand and may need to upgrade their interface capabilities substantially.

Since some of Cimetrix’ customers have pioneered the application of the latest generation of SEMI EDA (Equipment Data Acquisition) / Interface A standards in plumbing data from external “add-on” sensors to fault detection applications, I presented a generalization of this approach during one of technical sessions. This presentation, “Data Fusion at the Source: Standards and Technologies for Seamless Sensor Integration” is available on the Cimetrix website for those who want to learn more about how this is done.

Check back next week to learn more about creating good EDA/Interface A purchasing specifications.