Industry News, Trends and Technology, and Standards Updates

Meet Rich Kingsford, CCF Services project Manager at Cimetrix. Read on to learn a little bit more about Rich.

How long have you worked at Cimetrix?

I've been at Cimetrix for just under a year.

When did you graduate and what degree did you get?

I finished my graduate work and received my MBA in 2012.

What drew you to Cimetrix originally?

I had never worked on hardware integration before – just software integrating with other software.  I wanted to do something new and round out my experience.

What is your role at Cimetrix currently?

I am the Project Manager for the CCF Services team. I oversee and coordinate various projects with a variety of clients, concentrating on things such as scope, timeline, execution, quality, resources, and finance.

What do you think it means to a client to have a great CCF services team?

It's important that our clients know we are executing successful project after successful project. To me, this means we knock out all the scope in the desired timeline while staying within budget, even if the scope changes or other challenges hit us.

What do you like best about the work you do at Cimetrix?

I like seeing the iterative improvements to our analysis, reporting, and tracking systems. Finding and addressing the vulnerabilities in these is so important. I also enjoy learning about machine risks and mechanisms we can build to prevent the risk events or handle them if they occur (contingency planning).

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

In a status meeting recently, a client asked us for a contingency plan for when a wafer might slip out of place on a FOUP. We designed a solution that would identify the risk event, alert the user, and take damage-prevention metrics. This taught me a valuable risk mitigation tactic and helped the customer to gain a really cool preventative control.

What is one of the hardest challenges you’ve been faced with at Cimetrix and how did you overcome the challenge?

One challenge that comes to mind was when a client wanted payment options that were different from our standard practice. We’d never done things in this new way before, so we responded quickly by designing a solution, getting everyone on the same page, and trying it out. It worked ok and we learned a lot.

What is your favorite vacation spot?
Favorite is a tough one, but Bear Lake comes to mind – I love the KOA campground over there (especially its Pickleball and Shuffleboard courts).

What do you like to do in your free time?

I really enjoy instructing a few courses at some universities. I teach a software development capstone, an agile management, and a finance class. I also like playing Pickleball, Pool, Basketball, and board games when I can persuade my kids to put the screens down and play with me.

Welcome to the first posting in the Cimetrix CIMControlFramework (CCF) Services blog series! While Cimetrix has been providing professional services for many years, in order to better serve the growing demand from many new equipment maker customers worldwide that have purchased our CCF product, Cimetrix earlier this year formed a new CCF Services group, reporting directly to the CEO. Being a senior developer at Cimetrix for the past 15 years in a variety of positions, I was delighted when asked to lead this group. We have an outstanding team of software engineers highly experienced in factory automation, equipment control software and SEMI standards. We are dedicated to ensuring our customers’ success by providing training, consulting, and developing custom solutions for our CCF customers. We love learning about the myriad ways that companies can integrate CCF with their equipment to meet the material handling and factory automation requirements of their factory customers. Our goal for these articles is to share some of the lessons learned and other implementation insights to help you efficiently build manufacturing equipment that is sophisticated, robust, and productive. To this end, our first posting will deal with one of the most common requests we get – enjoy!

- Forward by Brent Forsgren, Director of CCF Services

How we helped a customer deliver a GEM-compliant equipment using CCF

The Goal

One of our recent customers wanted to build a new type of LED manufacturing equipment that could be controlled by a Factory Host using the standard GEM Remote Commands: PP_SELECT (Process Program Select), START, STOP, ABORT, PAUSE and RESUME. The equipment could be delivered in a variety of physical configurations, including 1-to-multiple source cassettes for product material, and 1-to-multiple process modules. It also had multiple destination cassettes to be filled according to the post-process analysis results. The initial instance of the equipment had 4 loadports (LPs) and four process modules (PMs).

The functional requirements were clear – that was the good news. Now for the rest of the story… the project schedule and budget constraints were closing in, so we needed to work quickly and efficiently with the customer to get it done. Sound familiar?

The Approach

The Cimetrix CCF Services team always works closely with the software team of the equipment manufacturer. In this case, we started with one week of mutual discovery and in-depth hands-on training. Team members were fully engaged and picked up the CCF capabilities very quickly. This included even some of the more advanced features, such as developing a scheduler that would control the components of the customer’s application. We regularly fine tune training modules to 1) introduce CCF concepts, 2) expose common challenges and potential approaches, and 3) provide realistic implementation practice exercises. As anticipated, the customer was able to use the results of the training exercises in the actual equipment control solution. We also kicked off the project with our work-breakdown exercise to more deeply explore the unique requirements for their specific equipment type.

After an intense first week, everyone on the project team concluded that CCF would in fact be a strong match for their needs. CCF features direct integration with our CIMConnect, CIM300, and CIMPortal connectivity products to provide full GEM, GEM300 and EDA compliance. Because the Cimetrix connectivity products are deployed in every semiconductor 300mm factory in the world, our customers can be assured that they will meet their customer’s factory automation requirements. In this application, the end customer’s LED factory only required GEM.

To address requirements that may go beyond the basic GEM standards, CCF also provides support for custom remote commands, data publication, and alarm management. Finally, CCF supports integrating custom hardware devices using CCF’s base Equipment Classes.

To prove all was working, we chose the Cimetrix EquipmentTest product to develop and execute a set of unit tests that emulate communications with the factory software using GEM messages. This was not intended to be a comprehensive set, but rather just enough to show the equipment passed round-trip system testing. In this context, round trip means showing that the equipment can move material from the incoming cassette to the aligner to the process module and back into the cassette. EquipmentTest also supports editing message settings and parameters on the fly to experiment with different configurations of a round-trip test.

The Challenge: “The Host is unavailable, but we need to validate that the equipment is both GEM compliant and accomplishes the communication flows the end user requires.”

We get this challenge a lot… Our customers almost always develop the host interface and the embedded control software in parallel and integrate them later in the project. This makes sense at one level, but it does introduce a “chicken and egg” problem for testing this kind of GEM interface. In particular, how can our customer provide evidence that the solution will work with the factory host without testing with the actual host system? Our answer: apply our EquipmentTest custom plugin capability to simulate the end user’s host so we can validate all necessary communication between host and equipment.

Our protocol validation product, EquipmentTest, makes it possible to simulate communications between an equipment control implementation and the host. And although it is impractical to implement scenarios for every possible interaction, we can create enough representative scenarios to be confident the “happy path” (i.e., no errors) will work and that the interface will handle a large handful of “sad path” cases as well.

Outcome

We passed all the tests! “Let’s go get some tacos.”

Specifically, we validated that the communications interface supported…

• Standard GEM Remote Commands
• Custom Remote Commands
• Material tracking
• Data publication

In closing, we must emphasize that our customer should take most of the credit here. Nevertheless, we enjoyed observing, consulting, and testing the equipment. It is always gratifying to see the CCF solution fit so seamlessly into the hardware, execute its commands with optimal timing, and not break anything in the process! Truly a successful, joint team effort.

If the situation above resonates with your current challenges and past experiences, give us a call. We look forward to working with your software engineering team to speed your time-to-market and deliver a high-quality solution quickly, allowing your team members to focus on developing value-added functionality for your customers.

Meet Brent Forsgren, the Director of CCF Services at Cimetrix. Read on to learn a little bit more about Brent.

How long have you worked at Cimetrix?

I have been at Cimetrix for over 15 years!

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

I graduated from Brigham Young University and my degree is in Computer Science.

What drew you to Cimetrix originally?

I wanted to find a smaller company where I could come in and immediately make an impact. Cimetrix fit that perfectly. 

What is your role at Cimetrix currently?

I am the Director of CCF Services, where my team and I provide solution architecture guidance to our client's success. For our customers, this means they should have complete confidence that we will work hard to ensure they are successful. 

What do you like best about the work you do at Cimetrix? 

I love working with our clients and seeing them have successful outcomes.

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

I knew nothing about the semiconductor industry before I came to work at Cimetrix. Everything I know about semiconductors and the electronics industry, I learned while working here.

What is one of the hardest challenges you've been faced with at Cimetrix, and how did you overcome the challent?

I had not been with Cimetrix for very long when I was asked to help a client implement a GEM300 solution for their tool. As I mentioned above, I was brand new to the semiconductor industry, and that included the SEMI Standards and the GEM300 standards. I had read through the GEM300 standards, but I had not yet had an opportunity to apply them. Fortunately for me, there were GEM300 experts at Cimetrix. With their guidance and help, I was able to successfully deliver a CIM300 solution to the customer and I helped install and test it in the factory. I appreciate the team environment here at Cimetrix.

What’s your favorite vacation spot?

I really like Kauai, Hawaii.

What do you like to do in your free time?

I like to work in my yard and in my vegetable garden. I also enjoy flying my drones and playing with my two dogs (Boxers).

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!

Meet Samson, a member of our Solutions Engineering team. Samson lives in Taiwan and is an integral part of our Taiwan team. Read on to learn a little bit more about Samson.

How long have you worked at Cimetrix?

I have been here about one and a half years

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

I graduated from Taiwan Tamkang University. My bachelor’s degree is Management Information System (MIS).

What is your role at Cimetrix?

I am an engineer on the Solutions Engineering team, and I am based in Taiwan.

What drew you to Cimetrix originally?

When I interviewed, I liked the Cimetrix working culture very much.

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

Our customers sometimes have some limitations when they are using our software. We need to understand what the current situation is that they face before we give them any suggestions. We not only provide good software to our customers, but we also try to provide the best service.

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

Working at Cimetrix is very special. You need to keep learning all the time, because there is so much knowledge we have to pick up.

What are your top 3 favorite books?

The Little Prince
Crime and punishment
Turn left and turn right (向左走向右走)

What’s your favorite vacation spot?

I most enjoy going to my grandfather’s house. It is located in a rural area in the south of Taiwan. We have a very big courtyard in the front of house. On summer nights we roast chicken, corn and sweet potatoes.

What do you like to do in your free time?

Stay with family, cycling, cook a cup of tea.

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.