Industry News, Trends and Technology, and Standards Updates

Cimetrix is pleased to announce and welcome Thomas Simon as its Director of Sales of Cimetrix Europe and Managing Director of Cimetrix GmbH. Thomas is based in Munich, Germany and will lead our growth in Europe. Thomas Simon will be responsible for ensuring the success of our growing customer base of leading semiconductor equipment manufacturers and smart manufacturing factories in Europe, providing strategic direction for Cimetrix Europe to have long-term success in the European market, overseeing local sales and account management and leading an expert team of Europe-based software engineers.

Thomas earned a Master of Science in Electronics and Semiconductor Technology and has 29 years of experience in the semiconductor, semiconductor backend, and electronics industries. He started his career as a field service engineer and then field service management working for companies such as Robert Bosch, SPTS (KLA), Centrotherm, UNAXIS (Evatec) and Suss MicroTec. Since 2011, Thomas has worked for Ulvac as Director of Sales and Business Development.

“Cimetrix has been serving European customers in the semiconductor and electronics markets for over 20 years. We have worked hard to gain a reputation for high quality products that are backed by responsive and exceptional technical support. Today, this provides us with a solid foundation of many longtime customers willing to serve as enthusiastic references. We also see strong and growing demand for Industrie 4.0 and Smart Manufacturing solutions. Accordingly, Cimetrix made the strategic decision to hire an experienced professional to lead Cimetrix’s business in Europe. We are very fortunate to have found Thomas Simon, as his vast experience in the semiconductor and electronics industries is a great fit with Cimetrix. We look forward to growing the Cimetrix team in Europe to provide even higher levels of support to our European customers.” 

-Bob Reback, President and CEO

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 Managing Director and is able to help our customers be successful and receive the highest levels of technical support.

To contact Thomas, please click the button below. Welcome Thomas!

Equipment Communication Leadership in Wafer Fabrication

For many years the semiconductor industry’s wafer fabrication facilities, where semiconductor devices are manufactured on [principally] silicon substrates, have universally embraced and mandated the GEM standard on nearly 100% of the production equipment. This includes the complete spectrum of front end of line (FEOL – device formation) and back end of line (BEOL – device interconnect) processes and supporting equipment. Most equipment also implement an additional set of SEMI standards, often called the “GEM 300” communication standards because their creation and adoption coincided with the first 300mm wafer manufacturing. Interestingly, there are no features in these standards specific to a particular wafer size.

Together, the GEM and GEM 300 standards have enabled the industry to process substrates in fully automated factories like Micron demonstrates in this video and GLOBALFOUNDRIES demonstrates in this video.

Specifically, the GEM 300 standards are used to manage the following crucial steps in the overall fabrication process:

• automated carrier delivery and removal at the equipment
• load port tracking and configuration
• carrier ID and carrier content (slot map) verification
• job execution where a recipe is assigned to specific material
• remote control to start jobs and respond to crisis situations (e.g., pause, stop or abort processing)
• material destination assignment after processing
• precise material location tracking and status monitoring within the equipment
• processing steps status reporting
• overall equipment effectiveness (OEE) monitoring

Additionally, the GEM standard enables

• the collection of unique equipment data to feed numerous data analysis applications such as statistical process control
• equipment-specific remote control
• alarm reporting for fault detection
• interaction with an equipment operator/technician via on-screen text
• preservation of valuable data during a communication failure
  

Semiconductor Back End Process Industry Follows the Lead

After wafer processing is completed, the wafers are shipped to a semiconductor back end manufacturing facility for packaging, assembly, and test. Historically this industry segment has used GEM and GEM 300 sporadically but not universally. This is now changing.

In North America, SEMI created a new task force called “Advanced Back end Factory Integration” (ABFI) to organize and facilitate this industry segment’s implementation of more robust automation capabilities. To this end, the task force is charged with defining GEM and GEM 300 support in back end equipment, including processes such as bumping, wafer test, singulation, die attach, wire bonding, packaging, marking, final test and final assembly. As its first priority, the task force has focused on updating the SEMI E142 standard (Substrate Mapping) to enhance wafer maps to report additional data necessary for single device traceability. Soon the task force will shift its focus to define GEM and GEM 300 back end use cases and adoption more clearly.

Why GEM?

GEM was selected for several reasons.

• A lot of the equipment in the industry already have GEM interfaces.
• GEM provides two primary forms of data collection that are suitable for all data collection applications. This includes the polling of equipment and process status information using trace reports where the factory can collect selected variables at any frequency. Additionally, collection event reports allow a factory system to subscribe to notifications of just the collection events it is interested in, and to specify what data to report with each those collection events.
• Most of the equipment suppliers have GEM experience either from implementing GEM on the back end equipment or from implementing GEM on their frontend equipment.
• Factories can transfer experienced engineers from semiconductor frontend facilities into the back end with the specific goal of increasing back end automation.
• GEM has proven its flexibility to support any type of manufacturing equipment. GEM can be implemented on any and all equipment types to support remote monitoring and control.
• GEM is a highly efficient protocol, publishing only the data that is subscribed to in a binary format that minimizes computing and network resources.
• GEM is self-describing. It takes very little time to connect to an equipment’s GEM interface and collect useful data.
• GEM can be used to control the equipment, even when there are special features that must be supported. For example, it is straightforward to provide custom GEM remote commands to allow the factory to determine when periodic calibrations and cleaning should be performed to keep equipment running optimally.

Improved Overall Equipment Effectiveness Tracking

The ABFI task force has already proposed some changes to the SEMI E116 standard (Specification for Equipment Performance Tracking, or EPT). EPT is one of several standards that can be implemented on a GEM interface to provide additional standardized performance monitoring behavior beyond the GEM message set. This standard already enables reporting when equipment and modules within the equipment are IDLE, BUSY and BLOCKED. A module might be a load port, robot, conveyor or process chamber. When BUSY, this standard requires reporting what the equipment or module is doing. When BLOCKED, this standard requires reporting why the equipment or module is BLOCKED.

After analyzing the requirements of the back end industry segment, the task force decided to adopt and enhance the EPT standard. For example, the current EPT standard does not make any distinction between scheduled and unscheduled downtime. However, a few minor changes to E116 would allow the factory to notify the equipment when downtime is scheduled by the factory, greatly enhancing the factory’s ability to track overall equipment effectiveness and respond accordingly.  

Additional Future Work

Many of the GEM 300 standards can be applied to some of the back end equipment when applicable and beneficial. The task force is defining specific functional requirements and evaluation criteria to make these determinations and publish the resulting recommendations in a new standard. Representatives from several advanced back end factories are already closely involved in this work, but more participation is always welcome. For more information, click the button below!

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.

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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!

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.

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

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. 

本文的焦点是当许多半导体设备制造商面对他们那些最先进的客户提出的自动化需求时，如何在购买支持EDA（Interface-A）标准的软件产品，或者自主开发之间做出决策。

鉴于我本人在今年初加入Cimtrix之前，曾经在一家半导体装备公司里担任EDA标准实现项目的主要开发人员，我想解释说明一下选择商业解决方案的利与弊。

• 利

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

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。

3. 时机

一个商业的EDA解决方案可以帮助OEM在短时间内开发出合格的EDA接口。自主开发EDA会给本已紧张的交付进度增加时间压力，如果需求来自一个新客户，第一个支持EDA标准的设备供应商通常会更有优势。在业务方面，EDA功能很有可能是获得订单的关键。在技术方面，第一个EDA的使用会成为整个Fab的范例，可以被用来制定其他设备在生产环境中必须满足的操作要求。

4．服务

使用商业EDA解决方案通常包括来自软件供应商的良好的技术支持，这些技术支持可能包含在最初的许可证费用中，或者是单独的技术支持合同。这意味着OEM公司不需要维持一个专门的软件团队来维护和解决遇到的软件问题。相反，他们可以依靠更专业的支持团队，而不用担心任何内部开发人员离开公司所带来的影响。

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。

• 弊

1.成本

OEM必须为商业软件的许可证，以及可能的、每年的技术支持支付费用。

2.知识产权(IP)

一些OEM公司为了对EDA功能的源代码有完全的控制权和所有权，他们选择自主开发并拥有这些软件，其原因是大多数商业软件包通常不会为基本许可证的使用者提供源代码。

3.修复错误的时间

如果在商业软件包中发现错误，设备工程师甚至工厂客户可能需要帮助软件供应商找到根本原因。他们还必须等待供应商修复并发布新版本的软件。这对于使用者来说非常不方便。

如果您的公司正面临这样的决定，请联系我们——我们很乐意分享我们的专业知识和市场知识，并协助您做出明智的决定。

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The 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

Simply 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.

You also might be interested in the following information:

Meet Mark Bennett, a member of the Solutions Engineering team. Read on to learn a little bit more about Mark.

How long have you been working at Cimetrix?

I have  been with Cimetrix for over 15 years. I started back when Cimetrix was primarily involved with robotics.

Where did you go to school and what did you get your degree in?

I went to Brigham Young University, and got a B.S. degree in Mechanical Engineering.

What brought you to Cimetrix originally?

At the time, I was working in the HVAC (Heating Ventilating and Air Conditioning) industry as a Mechanical Engineer. This was my first job out of college, and I decided that I didn’t want to make HVAC my career choice.  I got introduced to Cimetrix by my brother, who was working with Cimetrix as a customer.

What do you like most about your job?

I like solving problems and learning new things. What we do is not rocket science, but it’s probably just about as challenging.

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

Solve customer issues and help them successfully get their equipment deployed.

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

A few years ago, I was sent to TSMC in Taiwan to help a customer get a tool accepted in the FAB. They were having problems getting the E84 automated material handling system working. It was a very difficult assignment because the tool was already installed in the FAB and there were a lot of problems to fix. The FAB only allowed us to perform one or two tests per day. So, I captured log files from the tests, went out to the parking lot, and made code changes in the car. To fix the problem, I pretty much had to rewrite the entire E87 AMHS handling code, and a lot of the load port code as well.

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

Most of the challenges I face involve solving issues that customers report. Here are some things that I might try:

• Reproduce the problem using a sample application. Try to identify if this is a problem with the product, or if the customer is not using it properly.
• Search our database to see if this issue has been reported before. Find out how it was resolved in the past.
• Look through the SEMI standards to see how it should behave.
• Look through product documentation and release notes.
• Ask others for their opinions/suggestions.

What’s your favorite vacation spot?

Lately, we have been staying close to home for vacations.  We have taken trips to the San Francisco Bay area.  We enjoy that.

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

I’ve learned a lot about the SEMI standards. I have also learned a lot about software development and programming.

What do you like to do in your free time?

I enjoy watching movies. I also like trying to perfect my cooking skills on my Kamado barbecue grille.

As part of the CIMControlFramework (CCF) product for creating equipment control applications, Cimetrix developed a logging package. Our logging package has two parts – collecting the log messages and analysis of the messages.

The logging package allows you to assign a source and a type for each log message. The source specifies where the log message originated. The type is a category that can be used to route the log 

messages to specific output locations called log sinks. We have found the most useful log sink to be a text-based log file. The logging package can be configured for the types of messages to log. It can also be configured for how long to keep log files and how many to keep. This helps keep hard drives from getting too full.