Industry News, Trends and Technology, and Standards Updates

Feature by Ranjan Chatterjee, CIMETRIX
and Daniel Gamota, JABIL

Abstract

The vertical segments of the electronic products manufacturing industry (semiconductor, outsourced system assembly, and test, and PCB assembly) are converging, and service offerings are consolidating due to advanced technology adoption and market dynamics. The convergence will cause shifts in the flow of materials across the supply chain, as well as the introduction of equipment and processes across the segments. The ability to develop smart manufacturing and Industry 4.0 enabling technologies (e.g., big data analytics, artificial intelligence (AI), cloud/edge computing, robotics, automation, IoT) that can be deployed within and between the vertical segments is critical. The International Electronics Manufacturing Initiative (iNEMI) formed a Smart Manufacturing Technology Working Group (TWG) that included thought leaders from across the electronic products manufacturing industry. The TWG published a roadmap that included the situation analysis, critical gaps, and key needs to realize smart manufacturing.Article First Posted by SMT007 Magazine

Introduction

The future of manufacturing in the electronics industry is dependent on the ability to develop and deploy suites of technology platforms to realize smart manufacturing and Industry 4.0. Smart manufacturing technologies will improve efficiency, safety, and productivity by incorporating more data collection and analysis systems to create a virtual business model covering all aspects from supply chain to manufacturing to customer experience. The increased use of big data analytics and AI enables the collection of large volumes of data and the subsequent analysis more efficient. By integrating a portfolio of technologies, it has become possible to transition the complete product life cycle from supplier to customer into a virtual business model or cyber-physical model. Several industry reports project manufacturers will realize tens of billions of dollars in gains by 2022 after deploying smart manufacturing solutions. In an effort to facilitate the development and commercialization of the critical smart manufacturing building blocks (e.g., automation, machine learning, or ML, data communications, digital thread), several countries established innovation institutes and large R&D programs. These collaborative activities seek to develop technologies that will improve traceability and visualization, to enable realtime analytics for predictive process and machine control, and to build flexible, modular manufacturing equipment platforms for highmix, low-volume product assembly.

The vertical segments of the electronic products manufacturing industry (semiconductor (SEMI), outsourced system assembly, and test (OSAT), and printed circuit board assembly (PCBA) are converging, and service offerings are being consolidated. This occurrence is due to the acceleration of technology development and the market dynamics, providing industry members in specific vertical segments an opportunity to capture a greater percentage of the electronics industry’s total profit pool.

The convergence of the SEMI, OSAT, and PCBA segments will cause shifts in the flow of materials across the supply chain, as well as the introduction of equipment and processes across the segments (e.g., back-end OSAT services offered by PCBA segment). OSAT services providers are using equipment and platforms typically found in semiconductor back-end manufacturing, and PCBA services providers are installing equipment and developing processes similar to those used by OSAT.

The ability to develop smart manufacturing technologies (e.g., big data analytics, AI, cloud/ edge computing, robotics, automation, IoT) that can be deployed within the vertical segments as well as between the vertical segments is critical. In addition, the ability to enable the technologies to evolve unhindered is imperative to establish a robust integrated digital thread.

As the electronic products manufacturing supply chain continues to evolve and experience consolidation, shifts in the traditional flow of materials (e.g., sand to systems) will drive the need to adopt technologies that seamlessly interconnect all facets of manufacturing operations. The iNEMI Smart Manufacturing TWG published a roadmap that would provide insight into the situation analysis and key needs for the vertical segments and horizontal topics (Figure 1) ^[1].

In this roadmap, the enabling smart manufacturing technologies are referred to as horizontal topics that span across the electronics industry manufacturing segments: security, data flow architecture, and digital building blocks (AI, ML, and digital twin).

The three electronics manufacturing industry segments SEMI, OSAT, and PCBA share some common challenges:•

• Responding to rapidly changing, complex business requirements
• Managing increasing factory complexity
• Achieving financial growth targets while margins are declining
• Meeting factory and equipment reliability, capability, productivity, and cost requirements
• Leveraging factory integration technologies across industry segment boundaries
• Meeting the flexibility, extendibility, and scalability needs of a leading-edge factory
• Increasing global restrictions on environmental issues

These challenges are increasing the demand to deploy, enabling smart manufacturing solutions that can be leveraged across the verticals.

Enabling Smart Manufacturing Technologies (Horizontal Topics): Situation Analysis

Many of the challenges may be addressed by several enabling smart manufacturing technologies (horizontal topics) that span across the electronics industry manufacturing segments: security, data flow, and digital building blocks. The key needs for these are discussed as related to the different vertical segments (SEMI, OSAT, and PCBA) and the intersection between the vertical segments.

Members of the smart manufacturing TWG presented the attribute needs for the following: security, data flow, digital building blocks, and digital twin. Common across the vertical segments is the ability to develop and deploy the appropriate solutions that allow the ability to manufacture products at low cost and high volume. Smart manufacturing is considered a journey that will require hyper-focus to ensure the appropriate technology foundation is established. The enabling horizontal topics are the ones that are considered the most important to build a strong, agile, and scalable foundation.

Security Security is discussed in terms of two classes: physical and digital. The tools and protocols deployed for security is an increasingly important topic that spans across many industries and is not specific only to the electronics manufacturing industry. Security is meant to protect a number of important assets and system attributes that may vary according to the process (novel and strong competitive advantage) and perceived intrinsic value of the intellectual property (IP).

In some instances, it directly addresses the safety of workers, equipment, and the manufacturing process. In other cases, it transitions toward the protection of electronic asset forms, such as design documents, bill of materials, process, business data, and others. A few key considerations for security are access control [2], data control [3], input validation, process confidentiality, and system integrity [2].

At the moment in manufacturing, in general, IT security issues are often only raised reactively once the development process is over and specific security-related problems have already occurred. However, such belated implementation of security solutions is both costly and also often fails to deliver a reliable solution to the relevant problem. Consequently, it is deemed necessary to take a comprehensive approach as a process, including implementation of security threat identification and risk analysis and mitigation cycles on security challenges.

Data Flow

General factory operations and manufacturing technologies (i.e., process, test, and inspection) and the supporting hardware and software are evolving quickly; the ability to transmit and store increasing volume of data for analytics (AI, ML, predictive) is accelerating. Also, the advent and subsequent growth of big data are occurring faster than originally anticipated. This trend will continue highlighting existing challenges and introducing new gaps that were not considered previously (Figure 2).

As an example, data retention practices must quickly evolve; it has been determined that limitations on data transmission volume and length of data storage archives will disappear (e.g., historical data retention of “all” will become standard practice). Examples of data flow key considerations are data pipes, machine-tomachine (M2M) communication, and synchronous/ asynchronous data transmission.

A flexible, secure, and redundant architecture for data flow and the option considerations (e.g., cloud, fog, versus edge) must be articulated. The benefits and risks must be identified and discussed. Data flow and its ability to accelerate the evolution of big data technologies will enable the deployment of solutions to realize benefits from increases in data generation, storage, and usage. These capabilities delivering higher data volumes at real-time and nearreal- time rates will increase the availability of equipment parameter data to positively impact yield and quality. There are several challenges and potential solutions associated with the increases in data generation, storage, and usage; capabilities for higher data rates; and additional equipment parameter data availability.

The primary topics to address are data quality and incorporating subject-matter expertise in analytics to realizing effective on-line manufacturing solutions. The emergence of big data in electronics manufacturing operations should be discussed in terms of the “5 Vs Framework”:

1. Volume
2. Velocity
3. Variety (or data merging)
4. Veracity (or data quality)
5. Value (or application of analytics)

The “5 Vs” are foundational to appreciate the widespread adoption of big data analytics in the electronics industry. It is critical to address the identified gaps—such as accuracy, completeness, context richness, availability, and archival length—to improve data quality to support the electronics manufacturing industry advanced analytics ^[4].

Digital Building Blocks

The advancements in the development of digital building blocks (interconnected digital technologies) are providing digitization, integration, and automation opportunities to realize smart manufacturing benefits. These technologies will enable electronics manufacturing companies to stay relevant as the era of the digitally- connected smart infrastructure is developed and deployed. Several technologies considered fundamental digital building blocks are receiving increased attention in the electronics manufacturing industry (e.g., AI, ML, augmented reality, virtual reality, and digital twin).

AI and ML

AI and ML tools and algorithms can provide improvements in production yields and quality. These tools and algorithms will enable the transformation of traditional processes and manufacturing platforms (processes, equipment, and tools). The situation analysis for AI and ML, as well as their enablers, typically consider the following features and operational specifications: communications at fixed frequency, commonality analysis, material and shipment history and traceability, models for predicting yield and performance, predefined image processing algorithms, secure gateway, warehouse management systems.

AI and ML present several opportunities to aggregate data for the purpose of generating actionable insights into standard processes. These include, but are not limited to, the following:

1. Preventive maintenance: Collecting historical data on machine performance to develop a baseline set of characteristics on optimal machine performance, and to identify anomalies as they occur.
2. Production forecasting: Leveraging trends over time on production output versus customer demand, to more accurately plan production cycles.
3. Quality control: Inspection applications can leverage many variants of ML to fine-tune ideal inspection criteria. Leveraging deep learning, convolutional neural networks, and other methods can generate reliable inspection results, with little to no human intervention.
4. Communication: It is important for members of the electronics manufacturing industry to adopt open communication protocols and standards ^[5–8].

Digital Twin Technology

The concept of real-time simulation is often referred to as the digital twin. Its full implementation is expected to become a requirement to remain cost-competitive in legacy and new facility types. Digital twin will initially be used to enable prediction capabilities for tools and process platforms that historically cause the largest and most impactful bottlenecks. The ultimate value of the digital twin will depend on its ability to continue to evolve by ingesting data and the availability of data with the “5 Vs”: veracity, variety, volume, velocity, and value. The situation analysis of the digital twin within and between electronics industry manufacturing segments highlight the following data considerations: historical, periodic, and reactive.

The concept of a digital twin lends itself to on-demand access, monitoring and end-toend visualization of production, and the product lifecycle. By simulating production floors, a factory will be able to assess attainable projected KPIs (and what changes are required to attain them), forecast production outputs, and throughputs through a mix of cyber-physical realities (the physical world to the virtual world, and back to the physical world), and expedite the deployment of personnel and equipment to manufacturing floors worldwide.

Enabling Smart Manufacturing Technologies (Horizontal Topics): Key Attribute Needs

Security

Security will continue to be a primary concern as the electronics manufacturing industry adopts technologies and tools that rely on ingested data to improve manufacturing quality and yield and offer differentiated products at a lower cost and higher performance. SEMI members generated a survey to appreciate the needs, challenges, and potential solutions for security in the industry and its supply chain and gather more comprehensive input from the industry in terms of users, equipment and system suppliers, security experts, and security solution providers ^[9]. It is a topic that permeates many facets of manufacturing: equipment, tools, designs, process guidelines, materials, etc. Processes continue to demand a significant level of security to minimize valuable know-how IP loss; this requirement will generate the greatest amount of discussion such as data partitioning, production recipes, equipment, and tool layout. A few key attribute needs for security are network segmentation ^[10], physical access, and vulnerability mitigation.

These security issues are not unique to microelectronics manufacturing, and many of the issues go beyond manufacturing in general. The topic of security should reference the challenges and potential solutions across the manufacturing space. As an example, the IEC established an Advisory Committee on Information Security and Data Privacy ^{[11figuredfdafdfd}. It is suggested to collaborate with other standards and industry organizations that are developing general manufacturing security roadmaps by delineating specific microelectronics manufacturing issues and focusing on common needs.

Data Flow

The development of a scalable architecture that provides flexibility to expand; connect across the edge, the fog, and the cloud; and integrate a variety of devices and systems generating data flow streams is critical. A smart factory architecture may, for example, accommodate the different verticals in the electronics manufacturing industry as well as companies in non-electronics manufacturing industries.

As mentioned previously, different industries seeking to deploy smart manufacturing technologies should leverage architectures thatprovide the desired attributes; data flow architecture is considered a prime candidate for leveraging and cross-industry collaboration to identify optimum solutions (i.e., data synchronizers, execution clients).

The development and deployment of technologies for data flow are accelerating. Focus on data analytics, and data retention protocols are increasing at a faster rate than first anticipated. It is imperative to collect the critical data as well as to establish guidelines to perform intelligent analysis and to exercise the appropriate algorithms to specify data-driven decisions. Several topics related to data are under consideration, such as general protocols:

• “All” versus “anomaly” data retention practices
• Optimization of data storage volumes
• Data format guidelines for analytics to drive reactive and predictive technologies
• Data quality protocols enabling improvements in time synchronization, compression/uncompression, and blending/merging
• Guidelines to optimize data collecting, transferring, storing, and analyzing

Data considerations for equipment are:

• Defining context data sets for equipment visibility
• Improving data accessibility to support functions
• Data-enabled transition from reactive to redictive functionality
• Data visibility of equipment information (state, health, etc.)

Digital Building Blocks

The ability to deploy the necessary digital building blocks to realize smart manufacturing is at different stages of maturity.

AI and ML

A few key attribute needs for AI and ML are data communication standards, data formatting standards, and 3PL tracking solutions. Technologies, such as AI and ML, are seen as enablers to transition to a predictive mode of operation: predictive maintenance, equipment health monitoring, fault prediction, predictive scheduling, and yield prediction and feedback. This paradigm in AI-enhanced control systems architectures will enable the systems to “learn” from their environment by ingesting and analyzing large data sets. Advanced learning techniques will be developed that improve adaptive model- based control systems and predictive control systems. The continued development and assessment of AI and ML technologies is critical to establish the most robust and well-tuned prediction engines that are required to support emerging production equipment.

Digital Twin Technology

Advances in digital twin technologies are accelerating as the potential benefits are communicated to end-users. Also, the costs for enabling technologies (hardware and software platforms) are becoming less expensive. The following are considered key attribute needs that will increase adoption and broad-based deployment of the digital twin (product design, product manufacturing, and product performance: digital thread, predictive, prescriptive, and systemwide continuous data access.

Digital twin is a long-term vision that will depend on the implementation of discrete prediction capabilities (devices, tools, and algorithms) that are subsequently integrated on a common prediction platform. It is generally considered that the digital twin will provide a real-time simulation of facility operations as an extension of the facility operations system.

The successful deployment of digital twin in a facility environment will require high-quality data (e.g., accuracy, velocity, dynamic updating) to ensure the digital twin is an accurate representation of the real-time state of the fab. Also, the realization of this vision will depend on the ability to design an architecture that provides the key technologies to operate collaboratively by sharing data and capabilities. Ultimately, the success of the digital twin will depend on the ability to develop a path for implementation that provides redundancy and several risk assessment gates.

Prioritized Research, Development, and Implementation Needs

The topic of collaboration is often mentioned in industry-led initiatives as a key element to realize the benefits attributed to smart manufacturing. There is a strong drive by members of the electronics manufacturing industry to engage in activities that foster collaboration. Participants in these activities recognize that solutions must be consensus-based and adopted by many vendors. Equipment suppliers appreciate that deep domain knowledge combined with data analysis contributes to only a fraction of the potential value that can be captured. The optimal value will be realized when data is shared across manufacturing lines in facilities, with vertical segment industry supply chain members and across vertical segments.

Example prioritized research, development, and implementation needs topics are as follows:

• Define data flow standard interfaces and data formats for all equipment and tools
• Investigate if data flow continuity between vertical segments should be mandatory or optional
• Determine optimal operation window for the latency of data versus process flow and quantify permissible latency for data flow when used to determine process go/no-go
• Investigate data security and encryption requirements when sharing common process tools versus isolating process equipment between vertical segments
• Develop open and common cross-vertical-segments communication standards and protocols for equipment

Gaps and Showstoppers

There is universal agreement that digitization will drive huge growth in data volumes. Many predict that cloud and hybrid cloud solutions are critical to enable the storage and subsequent manipulation of data by AI algorithms to derive value. However, industry members must adopt consensus-based standards and guidelines for connectivity protocols and data structures (Figure 4). Smart manufacturing is a journey, and a robust and scalable connectivity architecture must be established on which to deploy digital building blocks (e.g., AI, ML to extract the optimal value from the data). 

Example critical gaps that could significantly impact the progress of the deployment and adoption of smart manufacturing are:

• Undefined data security between vertical segments
• Lack of machine interface standardization for data flow
• Undefined data formats for data flow
• Data vulnerability when security is breached
• Robust and scalable connectivity architecture across electronics vertical segments to enabling smart manufacturing functionality (event and alarm notification, data variable collection, recipe management, remote control, adjustment of settings, interfacing with operators, etc.)

Summary

The iNEMI Smart Manufacturing Roadmap Chapter provides the situation analysis and key attribute needs for the horizontal topics within the vertical segments as well as between the vertical segments. Also, the chapter identifies the primary gaps and needs for the horizontal topics that must be addressed to enable the realization of smart manufacturing:

• Definitions: Smart manufacturing, smart factory, Industry 4.0, AI, ML, etc.
• Audits for smart manufacturing readiness: Develop consensus-based documentation, leverage published documents (e.g., Singapore Readiness Index ^[12])
• Security: Best practices, physical, digital, local and remote access, etc.
• Equipment diversity and data flow communications: Old, new, and mixture
• Data attribute categorization and prioritization: Volume, velocity, variety, veracity, and value
• Cost versus risk profile versus ROI
• Talent pool (subject-matter experts): Data and computer scientists, manufacturing engineers, and automation
• Standards and guidelines: Data formats and structures, communication protocols, and data retention
• Open collaboration: SEMATECH 2.0

The gaps and needs that were identified for addressing require additional detail for the status of the different vertical segments to appropriately structure the initiatives. It was suggested to circulate surveys to gather the information to appreciate the issue. One survey format was suggested as an example template: Manufacturing Data Security Survey for IRDS FI Roadmap ^[13].

iNEMI, together with other organizations, such as SEMI, can organize workshops to facilitate collaboration between the electronics manufacturing industry stakeholders. In addition, iNEMI can establish cross-industry collaborative projects that can develop the enabling technologies to address the roadmap identified needs and gaps to realize smart manufacturing.

Further, organizations, such as iNEMI and SEMI, can collaborate to establish guidelines and standards (e.g., data flow interfaces and data formats) as well as lead groups to develop standards for equipment and tool hardware to reduce complexity during manufacturing. Also, iNEMI can engage other industry groups to foster the exchange of best practices and key knowledge from smart manufacturing initiatives.

The members of the roadmap TWG are committed to provide guidance during the smart manufacturing journey—people, processes, and technologies. Members of the TWG also suggested engaging microelectronics groups as well as non-microelectronics groups to assess opportunities to leverage existing smart manufacturing guidelines and standards.

Acknowledgments

Thank you to the members of the iNEMI Smart Manufacturing TWG. Their dedication, thought leadership, and deep appreciation for SMT enabling technologies was critical to preparing the roadmap chapter.

In addition, we would like to thank the participants and facilitators of the SEMI Smart Manufacturing Workshop—Practical Implementations and Applications of Smart Manufacturing (Milpitas, California, on November 27, 2018). SMT007

References

1. 2019 iNEMI Roadmap.
2. U.S. National Institute Standard and Technology’s Special Publication 800-82.
3. U.S. National Institute Standard and Technology’s Special Publication 800-171.
4. IEEE International Roadmap for Devices and Systems, Factory Integration.
5. Japan Robot Association’s Standard No. 1014.
6. SEMI E30-0418, Generic Model for Communications and Control of Manufacturing Equipment (GEM); SEMI A1-0918 Horizontal Communication Between Equipment; SEMI E5-1217, Communications Standard 2 Message Content (SECS-II); SEMI E4-0418, Equipment Communications Standard 1 Message Transfer (SECS-I).
7. Hermes Standard.
8. IPC-CFX Standard.
9. J. Moyne, S. Mashiro, and D. Gross, “Determining a Security Roadmap for the Microelectronics Industry,” 29th Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC), pp. 291–294, 2018.
10. IEC 62443 3-2.
11. website: iec.ch/acsec.
12. EDB Singapore, “The Singapore Smart Industry Readiness Index,” October 22, 2019.
13. www.surveymonkey.com/r/ZXLS6LH.

Ranjan Chatterjee is vice president and general manager, smart factory business, at Cimetrix.

Dan Gamota is vice president, manufacturing technology and innovation, at Jabil.

Article First Posted by SMT007 Magazine

Feature by Ranjan Chatterjee, CIMETRIX
and Daniel Gamota, JABIL

Editor’s note: Originally titled, “The Convergence of Technologies and Standards Across the Electronic Products Manufacturing Industry (SEMI, OSAT, and PCBA) to Realize Smart Manufacturing ” this article was published as a paper in the Proceedings of the SMTA Pan Pacific Microelectronics Symposium and is pending publication in the IEEE Xplore Digital Library.

Cimetrix is proud to announce that Ranjan Chatterjee, Executive Vice President of Smart Factory Solutions at Cimetrix, has been newly elected to the iNEMI Board of Directors. 

iNEMI, The International Electronics Manufacturing Initiative is a not-for-profit, highly efficient R&D consortium of approximately 90 leading electronics manufacturers, suppliers, associations, government agencies and universities.

iNEMI roadmaps the future technology requirements of the global electronics industry, identifies and prioritizes technology and infrastructure gaps, and helps eliminate those gaps through timely, high-impact deployment projects. These projects support their members' businesses by accelerating deployment of new technologies, developing industry infrastructure, stimulating standards development, and disseminating efficient business practices. They also sponsor proactive forums on key industry issues and publish position papers to focus industry direction.

In the official press release from iNEMI, they explain “The iNEMI Board plays an integral role in the governance of our organization,” said Marc Benowitz, CEO. “They provide oversight for our operations, including decisions regarding policy, strategy and direction of the consortium. These recently elected individuals bring a high caliber of leadership, as well as supply chain diversity, to our Board. We welcome the new and returning Directors and look forward to working with them.”

In addition to being elected to the Board of Directors, Mr. Chatterjee has also had the opportunity to Co-Chair the Smart Manufacturing Roadmap with Dan Gamota from Jabil.

Cimetrix is excited to play a role in the ongoing mission of iNEMI.

Read now in Chinese or below in English

矽美科很高兴地宣布和欢迎刘立聪先生加入矽美科并担任中国区总经理。刘先生将领导一支由中国软件技术专家组成的团队，负责本地区市场销售和客户服务，确保我们在中国半导体设备制造和智能制造工厂领域里领先的并不断增长的客户群的成功，为矽美科在中国市场长期成功发展制定战略方向。

刘先生拥有工商管理硕士学位和机电一体化工程学士学位。他在半导体和电子行业拥有超过20年的经验，其中包括中国本土公司和国际公司的经历。他担任过销售管理、客户管理和渠道管理等多方面的职责。他深刻理解半导体行业面临的诸多挑战，他将通过矽美科产品的价值和定位给我们的客户带来贡献，帮助客户发展业务。

矽美科中国，即矽美科 软件（上海）有限公司，成立于2019年，是一家在中国本土注册的企业，目的是更方便地为中国企业提供智能制造软件产品，并提供行业内最强的技术支持。

矽美科从五年前开始服务于中国市场和客户。最初，我们的中国市场策略侧重于与部分选择性的半导体300毫米设备制造商密切合作，通过为他们提供卓越的本地技术支持，确保他们成功使用矽美科产品。现在，这些最初阶段的客户已经向领先的中国半导体300毫米晶圆工厂批量提供设备，为矽美科赢得了高质量产品的声誉和证明。我们相信，现在是扩大本地团队，提高本地支持能力的正确的时机，可以让我们有能力更好地为规模庞大并不断增长的中国半导体界服务。刘先生将带领的核心技术团队是由经验丰富的软件工程师组成，他们是工厂自动化、设备控制和矽美科SEMI GEM、GEM300和设备数据采集（EDA）等方面产品的专家。我们过去一段时间一直在寻找一位高素质的国家总经理来补充我们的技术团队，也包括面试许多候选人。我们很高兴最终找到刘先生加入矽美科团队。”

Bob Reback，矽美科总裁兼首席执行官

矽美科在世界各地建立国际团队，为我们的客户提供在当地时区工作、讲本国语言和了解其独特文化的技术专家。在全球半导体和电子制造的主要地区，我们现在都有一位经验丰富的高级管理人员担任该地区的国家经理，能够帮助我们的客户获得最高质量的技术支持并取得成功。

欢迎刘立聪先生！

Cimetrix is pleased to announce and welcome Lewis Liu as its Country Manager for Cimetrix China. Mr. Liu will be responsible for ensuring the success of our growing customer base of leading semiconductor equipment manufacturers and smart manufacturing factories in China, providing strategic direction for Cimetrix China to have long-term success in the China market, overseeing local sales and account management, and leading an expert team of China-based software engineers.

Mr. Liu earned a Bachelor of Engineering in Mechatronics and a Master of Business Administration. He has over 20 years of experience in the semiconductor and electronics industries with both China local and international companies. He has held a variety of positions in sales management, account management and channel management. He deeply understands the many challenges of the semiconductor industry and will be an asset to our customers by demonstrating the value propositions of Cimetrix products for their businesses.

Cimetrix China (Cimetrix Software Shanghai Co., Ltd.) was formed last year as a local China company with the goal to empower China companies with smart manufacturing software, be easy to do business with and provide the strongest technical support in the industry.

“Cimetrix has been serving customers in China for the past five years. Initially, our China strategy focused on working closely with a few select manufacturers of semiconductor 300mm equipment to ensure their success using Cimetrix products by providing them with exceptional local technical support. Now that these initial customers are shipping equipment in high volume to leading China semiconductor 300mm wafer fabs and have earned Cimetrix a reputation for very high-quality products, we believe it is time to grow our local capabilities to better serve the large and growing China semiconductor community. Mr. Liu will lead our core technical staff of very experienced software engineers who are experts in factory automation, equipment control and the full portfolio of Cimetrix products for SEMI GEM, GEM300 and Equipment Data Acquisition (EDA) capabilities. We conducted an extensive search for a high-quality Country Manager to complement our technical team, which included interviewing many candidates. We were very pleased to find Mr. Liu and are excited to have him join the Cimetrix team.”

Bob Reback, President and CEO, Cimetrix

Cimetrix has been building international teams throughout the world to provide our clients with technical experts who work in their local time zones, speak their native languages, and understand their unique cultures. In all of the major regions for semiconductor and electronics manufacturing, we now have an experienced executive who serves as that region’s Country Manager and is able to help our customers be successful and receive the highest levels of technical support.

Welcome Lewis Liu!

You may be familiar with the brain teaser that starts, “As I was going to St. Ives, I met a man with seven wives.” As the poem continues, each wife has seven sacks, each sack has seven cats, etc. Eventually the question comes out, “How many were going to St. Ives?” The common misconception of this brain teaser is that to answer the question you must multiply all of the items together, resulting in a huge number.

Cimetrix has extensive experience in helping application developers integrate the Equipment Data Acquisition (EDA) / Interface A standards into their equipment control applications. Occasionally we encounter an equipment type that has a very large number of process modules and each process module has a very large number of exceptions. An exception in EDA Freeze II is represented by both an exception definition and an exception instance. What are the options for creating a model with a large number of exceptions?

Good

The most direct approach is to have one exception definition per exception instance as shown in the following EDA equipment model:However, with this approach, if each module has 5000 exceptions, 200 modules would result in 1 million exception instances with a corresponding 1 million exception definitions. The system resources required to deploy and maintain this model are very large.

Better

EDA allows multiple exception instances to refer to a single exception definition. The following model shows this approach:In this example, we can see that the process module has ten exception instances, but now there is only one set exception definition. Using this approach, if each module has 5000 exception instances, 200 modules would still result in 1 million exception instances, but we would now only have 200 exception definitions (one for each module). This is a significant reduction, but still quite large.

Best

The best approach for equipment with many process modules each with a large number of exceptions is to define only a few distinct exceptions per module, and then use a transient parameter (or data variable) to indicate the actual cause of the problem. The following model shows how this might look:The process module in the model above only has one exception. The transient parameter AlarmCode would contain the information about what caused the exception to be triggered. It is possible to have multiple exception parameters if additional information is necessary (sub error code, description, etc.)

The EDA standards reference four exception severity levels – Information, Warning, Error, and Fatal. If we create one exception definition for each of these severities and no more than four exception instances per module, we see that a model with 200 modules would have four exception definitions and an upper limit of 800 exception instances.

This approach to exception consolidation benefits equipment makers and factories alike by reducing model complexity and model size.

The answer to the brain teaser above is that only one person was going to St. Ives – me. You don’t have to spend a lot of time and effort trying to figure out how many people, cats, etc. were in the other party, because they were travelling in the opposite direction! Similarly, if you consolidate your exception handling in EDA, you don’t have to spend a lot of time and system resources trying to handle too many exceptions.

The COVID-19 pandemic is impacting businesses worldwide, and in many regions, working from home is now mandatory or at least strongly encouraged.

While this doesn’t pose a major disruption for many types of jobs, it can be problematic for people working with the automation features of advanced manufacturing equipment. The network connections to production equipment are normally part of a secure factory system infrastructure, which makes them almost impossible to reach from outside the company’s intranet. Luckily, for those responsible for testing and characterizing the SEMI EDA (Equipment Data Acquisition, also known as Interface A) interfaces on new 300mm equipment, this should only be a minor inconvenience. And why is that?

The choice of internet technologies (Web Services, SOAP/XML) as the foundation for the EDA standards makes it easy to connect to a piece of equipment over the internet as long as the user’s client computer can “reach” the connection URLs of the equipment (and vice versa). What this probably means in practice is setting up a VPN (Virtual Private Network) connection from your client computer (say, the laptop you normally use) to the company’s network. This is something that road warriors and remote employees must often do as a matter of course to access internal file systems, in-house applications, and other private information.

Once this is done, you can connect to the various service URLs for that equipment by including the remote computer name in the session connection strings. Note that you may have to modify the firewall settings of your client machine so the E134 NewData messages can find their way back to you. This is necessary because these are NOT request/reply messages like many of the EDA services; rather, they are initiated from the equipment, so your application has to be listening for them on the Consumer URL. This address is passed to the equipment when the connection session is first defined and established.

Using the Cimetrix ECCE Plus client product as an example, here is how I would set up a remote (from home!) session with an EDA-enabled 300mm equipment simulator running in our office on a machine named “edasimulator.” The first screenshot shows the choice of connections defined for my instance of the ECCE Plus; note that last one in the list that is highlighted.

Clicking on the “Edit Session Definition” button and then the “More >” checkbox yields the screen below. You can see that the equipment IP address is “edasimulator” (the remote computer name referenced above) and each of the Freeze II service URLs (E132 Location, E125 Location, and E134 Location) for the session are defined on that machine.

Note that the client ID (From/Client Name), which is “MyHomeTestClient,” must also be defined in the equipment’s Access Control List (ACL). For me to be effective, this client must have sufficient privileges for the kinds of work I need to do, which may include using existing DCPs (Data Collection Plans), creating additional DCPs, viewing interface configuration parameters (e.g., Max Sessions) and ACL entries, browsing the metadata model, and looking at the SOAP logs. Results of some of these tasks using the ECCE Plus are shown below.

This may sound like a lot of trouble, but with a little help from your company’s IT support team, you can follow the “shelter in place” guidelines and STILL work effectively on your EDA-related tasks. And when the current crisis has passed, you’ll know how to be even more effective when you’re on the road!

We hope the posting is useful for you, and most importantly, that you and your loved ones stay safe and calm.

To our valued clients and partners –

With the ongoing spread of COVID-19 (Coronavirus), we are in unprecedented times. This situation changes rapidly, and Cimetrix wants to reassure our clients and partners that we are continually adapting our operations and business practices to ensure that we continue to serve your needs and that no client experiences a decline in the quality or responsiveness of our technical support.

Today I want to personally share what we are doing to maintain continuity during this time.

TECHNICAL SUPPORT

As always, our technical support capabilities can be accessed around the clock, anywhere in the world. We have offices throughout Asia, the U.S. and Europe to make sure that your needs are taken care of 24 hours a day. While many of these offices are in countries that have asked their residents to self-isolate, we will continue to work remotely to make sure all the needs of our clients are covered.

PRODUCT SUPPLY

Some of our clients have asked if our supply of products could be interrupted during the COVID-19 virus. We currently expect no interruptions whatsoever in our supply of products.

SAFTEY OF OUR CLIENTS AND EMPLOYEES

I have personally requested that the employees of Cimetrix stay home if they show any signs of illness. In addition, I have also issued a statement to all employees saying they should work from home if their local government requests it, or if they feel their health could be compromised. Cimetrix has long been a proponent of the work-from-home option, allowing even employees near a Cimetrix office to work from home several days a week. We are now very experienced at working collaboratively with employees in many different locations, including employees working from home. We do not expect any decline in our ability to serve our clients or continue executing our product roadmaps.

In addition, when and if it might be appropriate for our team members to visit our clients’ facilities, our team members have been coached on appropriate hygiene requirements as well as ensuring they will not visit if they feel unwell. As always, the health and safety of our clients, employees and partners is of paramount concern.

Cimetrix is determined to stay connected and working for you. We will continue to evaluate this evolving situation, and are here to assist all of our clients as needed.

Meet Clare, a member of our Solutions Engineering team. Clare lives in China and is an integral part of our China office. Read on to learn a little bit more about Clare.
How long have you worked at Cimetrix?

I have worked at Cimetrix for 22 months, since May 2018.

Where did you go to school and what is your degree?

I got my Bachelor’s degree at the Harbin Institute of Technology (Harbin, Heilongjiang Province, China) and my Master’s degree at Fudan University in Shanghai, China. What is your role at Cimetrix?

I am a Cimetrix Solution Engineer located in China. 

What drew you to Cimetrix originally?

I have known of Cimetrix for many years and have been learning from the Cimetrix website. Cimetrix can be called a mentor for my working in the past few years when it comes to technology standards and expertise. It was great to be able to join Cimetrix and get to know more people as a part of this team.

What do you enjoy most about the work you do?

Sharing my experience and knowledge with others and learning from different people at the same time is what I enjoy most about the work I do.

What do you think it means to provide great customer support?

I think we provide great customer support by not just replying why or what their solution is, but also telling them how to fix their problems on their own.

What is the biggest accomplishment you’ve had at Cimetrix?

My biggest accomplishment is the localization of Cimetrix articles and coordination for EDA Seminars with SEMI China.

How do you deal with challenges that come up at work?

As challenges come up at work I like to just keep learning and consult with all of the experts on our team. Our team is all around the globe and everyone has a special expertise about something, so we are constantly learning from each other.

What’s something you’ve learned while working at Cimetrix?

The passionate support of Cimetrix! It is not only about solving the current problem, we really care about the customer’s need and want to help them to improve their skills and products.

What do you find to be most challenging about your job?

To support our customers’ need for comprehensive understanding of the equipment, the software and factory automation related knowledge. The limited hands-on experience on equipment control software is a big challenge for me.

Do you have a favorite quote or saying? Why?

天道酬勤 (God rewards the diligent)

What are your top 3 favorite books and/or movies?

A Dream in Red Mansions, Gone With The Wind and The Shawshank Redemption.

What’s your favorite vacation spot?

My hometown, Inner Mongolia

2019 was another exciting year for Cimetrix. In our journey as a Smart Manufacturing and Industrial IoT solutions provider, we were able to increase revenues year-over-year to a new record high during a year that saw double-digit revenue drops for capital equipment suppliers in the semiconductor industry. Also, our attention to fiscal discipline enabled us to achieve our tenth consecutive year of profitability and further strengthen our strong cash position.

Cimetrix continues to provide software that makes the world’s most sophisticated and expensive manufacturing equipment smarter, as well as an innovative IIoT platform for the world’s leading factories. We focus on ensuring the success of our worldwide customers with local presence and support. Our global team members in North America, Europe, Japan, Taiwan, Korea, China and Southeast Asia provide unmatched expertise and technical support to our customers.

For 2020, Cimetrix expects a double-digit increase in revenues as the results of our growth initiatives undertaken over the past several years gain further traction. We believe the foundation of Smart Manufacturing and Industrial IoT begins with smart equipment and smart connections. Furthermore, we believe that Cimetrix is uniquely positioned to help equipment manufacturers and factories in their pursuit of Smart Manufacturing. We will relentlessly pursue understanding our customers’ challenges and providing them with innovative solutions.

From all of us at Cimetrix, we thank our customers, partners and shareholders for the faith and confidence they have placed in us. We will continue to strive for excellence in satisfying our worldwide base of customers and delighting them with innovative new products and solutions.

Sincerely,

Bob Reback
President and Chief Executive Officer

When it is time to deploy equipment in a factory it is very apparent if proper software testing has been conducted. As Ron Michael said, “If you automate a mess, you get an automated mess.” This notion holds true for GEM-enabled equipment. Software tools are available that are designed to make automated testing painless and efficient. While it is important to test all software on the equipment, this blog focuses on testing the GEM interface.

Testing the GEM interface is crucial throughout the equipment’s Software Development Life Cycle as you will see below.

Development Phase

The stakeholder (customer) has communicated the need for the equipment to have a GEM interface so it can integrate with an in-house GEM host. The customer’s written specification includes the GEM scenarios the equipment must support to interact effectively with the host.

As the requested features are added to the GEM interface, the developer must be able to simulate the host’s role in each scenario. Testing is crucial to ensure the equipment correctly satisfies each requirement. After the GEM interface is completed, E30 compliance testing is paramount before deployment.

Deployment Phase

After the equipment is set up in its permanent location, the field engineer will need a way to connect to the equipment and test the GEM interface before the equipment is connected to the factory host.

Once the equipment is in production it can be difficult to gain access to the equipment because of its geographical location or factory access restrictions. So deploying equipment that has a tested and compliant GEM interface allows you to avoid a significant loss of time and resources and ensure a smooth deployment.

Sustaining and Maintenance Phase

The GEM interface should be tested after every software update, GEM feature addition, or any change that could affect how the interface performs.

In this sustaining and maintenance phase equipment that have been properly tested experience less downtime.

Using the Right Tools

Some of the biggest challenges that equipment manufacturers face stem from not having the correct GEM testing tools.

Perhaps they have a testing tool, but it is outdated and therefore, not effective. Having outdated tools in your testing portfolio is much like hanging on to a worn, rusty wrench. It may appear to be working, but it is gradually stripping the bolts. As Benjamin Franklin noted, “The best investment is in the tools of one’s own trade.” Therefore, as developers, it is important to know when it is time to “throw away the rusty wrench.”

Cimetrix EquipmentTest^TM is a new software tool designed to reduce factory acceptance time and harden your factory GEM interface. It also helps factories and equipment suppliers characterize equipment, gather information from equipment, determine an equipment’s compliance to SEMI standards, and consolidate any equipment-specific unit tests into a single interface.

EquipmentTest is the multi-purpose tool that every equipment developer should have in their toolkit.

To understand why, let’s look at a few of its key features.

The Message Tab

The Message tab in EquipmentTest is crucial during development and testing. As parts of the GEM interface are completed, the ability to send atomic messages or to reply to messages from the equipment is vital. The messages are formatted in SMN (SEMI E173, SECS Message Notation). This XML syntax combined with a library of raw message templates makes it easy to quickly create and send SECS messages without writing any code. This is especially useful in situations such as sending a remote command to the equipment or ensuring a GEM alarm is reported to the host.

Users can also define custom messages and add these messages to their own libraries. These messages can then be saved into the EquipmentTest profile for that equipment to be used again later.

GEM Compliance Plug-in Report

EquipmentTest Pro provides an out-of-the-box GEM (SEMI E30) compliance testing capability called the GEM Compliance plug-in. This plug-in ensures that all GEM requirements implemented on the equipment are done so correctly. The GEM Compliance plug-in also provides a report that can be used to determine what areas of the GEM standard the equipment has implemented properly, and where improvement is needed. This report can help mitigate a common scenario I have witnessed where an inadvertent lack of congruence between stakeholders leads to missing or improperly implemented GEM items.

EquipmentTest is also configurable so that if a certain area of GEM functionality is not required by a factory, the report will define it as “not implemented.” EquipmentTest allows developers, testers, and all stakeholders to deploy their GEM interfaces with confidence.

Test Execution

Tests can be run one at a time, or as a group. Each test contains embedded documentation that explains the test purpose and the steps that comprise the test. The Output tab shows the results of the test. The SMN log can be used when a test fails for diagnostics or to view the contents of messages that were sent and received by EquipmentTest.

Custom Tests

Every equipment is unique. Moreover, a particular equipment’s unique features are likely what differentiate it from the competitive alternatives and therefore contribute significantly to its value. For this reason, it is impossible to test every behavioral scenario of all manufacturing equipment. Inevitably, innovative equipment will require custom testing. Custom testing may also be required to ensure the equipment will meet the specific requirements of a given factory.

Support for custom testing is one of the most valuable features of EquipmentTest. Unlike its predecessors that use a limiting scripting language, EquipmentTest allows users to create custom tests called plug ins in standard .NET programming languages. The ability to write host-side tests in an extensible programming language, with access to the EquipmentTest’s SECS/GEM software libraries offers limitless testing possibilities. This makes sending and receiving SECS messages in a custom test very simple (as shown below).Once a developer creates a test, the project Dynamically Linked Library (.dll) file can be distributed to others involved in the testing project. This allows engineers, technicians, and other stakeholders to load the custom plug-in and test the equipment without writing any code.

Trace Report Test Example

This plug-in was created during training and showcases the basics of plug-in development. When we load our custom plug-in, the look and feel is the same as the Cimetrix-provided plug-ins.

Documentation

The documentation displayed in the UI is populated from the following method decorations.

Parameters

Parameters can be changed by the EquipmentTest user and can be of any type, even custom data types.

Test Logic

As the test runs, everything that is printed to the console in code shows up in the output window.Assertions

Assertions are what a test actually evaluate. In this example, we assert that all samples of the trace are sent by the equipment. If any assertion fails, the test will fail on the UI. In this case, “1 or more samples did not complete” would appear on the UI upon a test failure.

SMN Log

The SMN log contains all messages transmitted during the test. This can be very helpful for diagnosing the root cause of a test failure when used with the test output.

Conclusion

The Cimetrix EquipmentTest software is designed to make automated testing painless and efficient. Using this shiny new tool instead of a rusty one can make deploying a quality GEM interface much easier and helps ensure your new or existing GEM interface is fully E30 compliant.

For more information on Cimetrix EquipmentTest visit our website today.

오늘 1월 31일 SEMI 협회는 코로나바이러스가 확산됨에 따라서, 2/5일부터 개최 예정이였던 SEMICON Korea 2020을 전면 취소할 수 밖에 없음을 알려 왔습니다. 궁금한 점이 있으시면 연락주시기를 바라며, 건강에 더욱 유념하시기를 부탁드립니다.

The SEMI Association has announced that, due to recent health concerns, they feel they have no choice but to cancel SEMICON Korea 2020. Please let us know if you have any questions, and feel free to reach out to us at any time.

Read now in Korean or below in English.

세미콘 코리아 2020이 2월 5일부터 7일까지 코엑스에서 개최될 예정입니다. 씨메트릭스는 한국 파트너사인 링크제니시스와 부스 #C818에서 여러분들을 맞을 준비를 하고 있습니다. “Design the Future”라는 주제로 반도체 제조, AI등 첨단 주제를 30여개의 프로그램이 진행될 예정이면, 저희 씨메트릭스와 링크제니시스는 다음과 같은 내용을 준비하였습니다.

• 빅데이터/AI/머신러닝에서의EDA/Interface A의 역할 (고객사와의 공동 연구 제안 중)
• 최근 한국과 중국에서 씨메트릭스가 주최한 EDA 세미나에서 많은 관심을 받은 Freeze III에 관한 안내 – 큰 주목을 받고 있는 이유는 데이터 처리 속도의 괄목한 만한 향상에 대한 기대감
• EDA 개발시 혹은 검수시 오는 효율적이고 철저한 테스트의 어려움과 복잡함을 자동화를 통하여 해결
• 많은 장비회사가 미래 성장을 위해서 준비하고 있는 소프트웨어의 고도화를 위한 로드맵 제시

부디 방문해 주시기를 바라며 미팅을 원하실 경우 아래의 버튼을 통하여 신청해 주시기 바랍니다.

SEMICON Korea 2020 is almost here and Cimetrix is headed to the show! We will be co-exhibiting with our partner Linkgenesis at booth #C818. The show will be at COEX in Seoul on February 5-7. We look forward to the show and hope to see you there!

This year’s SEMICON Korea theme is: Design the Future and will feature more than 30 technology programs offering leading insights into semiconductor manufacturing, AI and more. Cimetrix recently held a seminar, in partnership with SEMI, around the topic EDA/Interface A, and this seems to be a major talking point both for SEMICON Korea, and around the world at this time.

If you want to find out more about EDA/Interface A, and how it can help with your Smart Factory goals, be sure to stop by our booth #C818. Some of the things you might learn are:

• How EDA/Interface A leads the Big Data/AI/Machine Learning initiatives in the semiconductor world.
• Hear recent news on the Freeze III that ensures a huge performance gain with existing EDA.
• EDA acceptance testing can be difficult due to its complexity. Find out an easy way of testing the EDA interface .
• Good equipment needs good software inside. Find out how to prepare competitive software with a good software roadmap.

We hope to see you at our booth, or you can request a meeting any time by clicking the button below.