Big Data

SEMICON Korea 2023 showcased the latest developments in high-priority areas including sustainability, smart manufacturing, advanced chip technologies, and workforce development. Keynotes by semiconductor leaders AMD, imec and Lam Research on critical chip industry trends.

More than 4,000 participants convened in person at the four-day SEMICON Europa Expo in Munich, November 16-19. Attendees gathered at the Executive Forum for insights into the latest trends in the semiconductor industry and heartily welcomed the long-awaited return to in-person networking.

During the COVID-19 pandemic, the SEMI Global Advocacy team has been working tirelessly to ensure the microelectronics manufacturing and design supply chain is classified as an “essential business” in the United States and for similar designations in several other countries so that SEMI member companies can maintain operations. Their efforts have included direct lobbying and letters to the governors of 16 states in the U.S., 23 European countries and several European Union officials across the continent, as well as government officials in Japan, Mexico and Malaysia. The bedrock of these efforts, and the reason they have been highly effective, is that our industry enables both modern digital infrastructure and technology critical in the fight against the virus.SEMI takes immense pride in highlighting the role of our industry in providing the building blocks for innovations that improve social and economic prosperity the world over. It is never more apparent that necessity is the mother of invention than during a crisis, and the pandemic has created a diverse range of demands for technological advancements to address the myriad of challenges it presents. Our SEMI Tech Spotlight blog series highlights some of the many ways that our industry and member companies are enabling technology employed on the front lines of this fight – and that we strongly believe will ultimately help to win it. Our first piece in this series focuses on platforms enabled by big data and artificial intelligence.Fighting the Pandemic with Big Data-AI Enabled PlatformsThe COVID-19 pandemic is testing humanity in unprecedented ways, but it is also uniting us to fight this crisis with the best weapons we have. Big data and Artificial Intelligence (AI) technologies – built with microelectronic chips and systems that generate, transmit, store and analyze data – are making a profound contribution to our arsenal for this protracted war. Big data-AI technologies are enabling platforms such as data analytics, robotics, augmented/virtual reality (AR/VR), 3D printing, and others that are already being applied to address many facets of this crisis.Big Data and Analytics Inform Policy In the fight against COVID-19, data analytics platforms are being used first and foremost to slow the rapid spread and to inform policy decisions. This requires analysis of massive amounts of data about public health and travel, often using AI algorithms. The state of California, for example, is partnering with companies such as BlueDot, Esri and Facebook to build a software platform that uses smartphones and location intelligence to track people’s movement and predict hospital needs. Taiwan owes its considerable success in limiting the spread of the virus to the extensive use of big data analytics for identifying and tracking carriers. Google and Apple are driving a joint effort that connects Bluetooth with their popular iOS and Android platforms to trace contacts of infected people. India has developed Aarogya Setu, a mobile app based on Bluetooth and location-mapping platforms, designed to alert citizens if they have crossed paths with another app user who has tested positive for the virus. This app was launched in 11 languages, and despite being entirely voluntary, it was downloaded by 50 million people in 13 days, making it the world’s fastest-ever to reach that number. Such contact-tracing apps, now being rolled out in at least 26 countries, carry inherent privacy and security challenges due to the sensitive data they access. While mitigation strategies like strict data anonymity and opt-in protocols are being implemented, these will need to be refined over time.Robotics Protect Frontline SoldiersToday’s robust robotics platforms are enabled by huge amounts of data from sensors and guidance from predictive AI algorithms. These robots can learn on the job, adapt to the environment, and work safely with humans. In this pandemic, they are perfect for minimizing human interaction with infectious environments. Companies around the world such as Boston Dynamics, Akara Robotics, UBTECH Robotics and CloudMinds have already deployed robots on the front lines of this war to assess patient health, disinfect hospital surfaces, and help health workers with Personal Protective Equipment (PPE).Robot drones are also delivering blood and other lab samples. For example, WakeMed hospitals in North Carolina launched the first drone delivery program approved by the U.S. Federal Aviation Administration with Matternet drones operated by UPS; while Terra Drone from Japan executed similar tasks in the hard-hit Wuhan province of China.3D Printing Speeds ManufacturingBig data-AI technologies enable 3D printing platforms by providing accurate 3D models for optimized designs and defect-free manufacturing. Low-cost, fast-cycle-time 3D printing has helped to alleviate at least some of the medical equipment shortages. For example, the U.S. Food and Drug Administration (FDA) has approved the first 3D-printed “Stopgap Face Mask” for liquid barrier protection from the SARS-CoV-2 coronavirus for healthcare workers. The U.S. Veterans Health Administration has developed this in collaboration with America Makes using an open-source database – the 3D Print Exchange from the National Institutes of Health. In another example, Formlabs worked with Northwell Health, New York’s largest healthcare provider, and University of South Florida (USF) Health to develop and test a nasal swab prototype over just one weekend, and it is now producing up to 150,000 test swabs daily. Prisma Health in South Carolina received emergency FDA authorization for VESper, a 3D printed device that allows a single ventilator to support two patients, and possibly up to four.Telehealth Becomes a “New Normal”Telehealth is not a new concept but is much enhanced by today’s microelectronics platforms that can collect and transmit rich datasets with very low latency. Further, rapid data analysis is increasingly supported by AI systems. The requirement for social distancing makes telehealth a perfect solution for many healthcare consultations. U.S. government data indicates that the daily average of telehealth claims from private insurance for upper respiratory infections increased nearly 12 times over the previous month from March 14 to April 1. Similarly, Teladoc Health coordinated 100,000 patient “televisits” in the week of March 8 – a 50 percent spike over the previous week, taking pressure off the healthcare system. The next generation of telehealth is likely to use AR/VR platforms, which use even richer datasets and AI to improve the accuracy and predictive capability of their underlying models. Consequently, these platforms can provide more realistic experiences and improved outcomes. At least 11 states in the U.S. are already working with AR/VR companies such as XRHealth and AppliedVR for primary care and many medical specialties. Accelerating the Search for a Vaccine or TreatmentThe way out of this pandemic depends on swiftly finding a vaccine and a treatment, ideally by fast-tracking the traditionally slow drug development process. Big data-AI technologies are at the forefront of such efforts globally, often using the most powerful supercomputers available. For example, researchers at the University of California, San Diego (UCSD) are using the Frontera supercomputer to build a complete model of the SARS-CoV-2 coronavirus envelope – a formidable task, requiring analysis of data from 200 million atoms and interactions between them. Researchers at Argonne National Laboratory are combining AI with physics-based models to search for a molecule that might disrupt the activity of the virus, a precursor to finding a treatment. Also, several companies around the globe such as BenevolentAI (UK), Gero (Singapore), Innoplexus (Germany-India), and Insilico Medicine (US-Hong Kong) are using AI platforms to accelerate the search for a solution. ConclusionUltimately, the success of technology is not measured by the number of bits and bytes or by the speed of algorithms. It is measured by every janitor who did not have to clean a hazardous surface because a robot did, by every doctor and nurse protected by a 3D-printed mask, and by every person whose life may be saved by the accelerated discovery of a vaccine or treatment. Big data-AI technologies, and the platforms they enable, are just coming of age – they give us hope that as they evolve in the future, we can use them to build a more resilient society and economy.Note/Disclaimer: The examples cited above are purely for illustration – they are neither comprehensive, nor intended to endorse any particular product or solution.The SEMI Smart Data AI initiative helps members realize full value in the intelligent future enabled by Big Data and Artificial Intelligence – including the large revenue upside, and the transformational potential for operational and supply-chain efficiency. For more information on the initiative, contact Pushkar Apte at [email protected] Manocha is President and CEO of SEMI. Pushkar P. Apte, Ph.D., is the Strategic Technology Advisor for the Smart Data AI Initiative at SEMI.

The march of innovation in semiconductor microfabrication technology over the past 60 years has produced electronic devices and information systems that have transformed industries and lives around the world. And while advances in chip technology continue to make it possible to collect, transmit, store and process more data for a rapidly growing universe of applications, the pace of innovation is now facing strong headwinds. Powered by chip innovation, data centers have become massive centers of information processing but, on the downside, enormous consumers of electricity. Today, the power-hungry hubs account for five percent of the world's electricity usage, a proportion that is growing every year, raising important questions about sustainability. Compounding the challenge, the pace of Moore's Law, for decades the engine of electronic device and information system innovation, has slowed. While the research and development of state-of-the-art semiconductor fine processing technology remains robust, developing the advanced manufacturing technology for mass-producing more sophisticated electronics devices is becoming harder, as is ensuring business profitability."It has become difficult for semiconductor technology to continue to evolve as it has in the past," said Akira Minamikawa, Research Director of Technology Research at IHS Markit, who moderated the Semiconductor Executive Forum – View by Top Two in the Era of Digitalization on opening day of SEMICON Japan 2019 at Tokyo Big Sight. Held at the SuperTHEATER, the forum featured Terushi Shimizu, representative director and president at Sony Semiconductor Solutions, and Atsuyoshi Koike, president at Western Digital Japan, two industry powerhouses that could figure heavily in the future of digital technology. SuperTHEATER, the main stage at SEMICON Japan 2019 Image sensors evolve to become eyes of AIImage sensors are becoming eyes of artificial intelligence (AI) and intelligent systems that monitor people and events worldwide, collecting data that one day could help puzzle out growing social challenges such as energy conservation and traffic congestion. With 51 percent market share on the strength of its industry-leading technology, Sony Semiconductor Solutions dominates the image sensor market. Despite last year’s global semiconductor industry slump, the company’s “business continues to enjoy strong growth and we are very busy,” said Shimizu, who attributed the company’s robust performance to the rising importance of the social role of image sensors and the expanding number of applications they support.The success of the company’s image sensors can also be traced to its division of the image sensor market into two application categories: "Imaging" focuses on capturing beautiful image data, while "sensing" aims to collect data that accurately describes the state of a subject and its surroundings."In 2019, sales of imaging products for smartphones grew rapidly,” Shimizu said in his market overview. “This is due to the average annual 15 percent growth rate of multi-camera smartphones, with some phones today featuring seven cameras, and an average annual growth rate of 20 percent in sensor size to produce higher image quality."But Shimizu cautioned that Sony Semiconductor Solutions doesn’t expect the smartphone sensor market to maintain that fast growth rate."The imaging market is expected to grow until 2022, but after that, the sensing market will drive market growth,” he said, adding that the company’s “capital investment plan is based on this scenario."AI will be key in catalyzing growth of the sensor market as integrations of AI processing engines and sensing images grow in sophistication to capture images undetectable by the human eye, Shimizu said. AI will extract insight from captured image data. For its part, Sony will apply its layer stacking technology to sensing products."By stacking an AI processing engine, we want a significant portion of the recognition processing done within the sensor chip," Shimizu said.One sensor the company already offers collects in-depth information for indirect time-of-flight (ITOF) 3D ranging for new user interfaces relying on autonomous or gesture control for robotics. The sensor “was first used in smartphones in 2018 and saw widespread adoption in 2019," Shimizu said.Sony Semiconductor Solutions plans to focus on developing new sensors for integration with their ultrasonic cousins. Aided by optical deflection technology, the sensors will be used for product quality inspections during manufacturing.With the company’s growing strengths in sensor technology, it hopes “to increase sales of sensors from a few percent of the company’s total sales in 2018 to 30 percent in 2025,” Shimizu said, pointing to its goal "to capture 60 percent share of the image sensor market by 2025."Data as one way to spread happinessAt the heart of consumer devices such as smartphones and computers and also cloud servers, NAND flash has made it possible to process vast troves of data anytime, anywhere. In recent years, the technology has enjoyed stronger adoption for use as the storage medium of choice for edge computing, stationed between end devices and the cloud to help streamline data utilization. But the technology isn’t merely about making smarter use of bits and bytes."We would like to promote the technology development that can support the use of data to bring happiness to people around the world," Koike of Western Digital Japan said. The company calls data that contributes to individual happiness and helps solve social issues "data for good" and, like the Sony Semiconductor Solutions bifurcated classification of the image sensor market, categorizes information into “big data” and “fast data.”For example, big data can leverage AI to drive dramatic improvements in the interpretation of test data and, ultimately, the diagnostic accuracy of mammography for breast cancer screening, aiding in early detection to help save lives, Koike said. Fast data can be harnessed to analyze data collected from a manufacturing equipment line in real time to improve production efficiency. The company’s plant in Yokkaichi, Mie Prefecture, which the company operates in cooperation with Japanese memory manufacturer Kioxia, already uses fast data to bolster production.More NAND flash innovation and greater supply capacity are critical to developing "data for good," Koike said. "It is difficult to expand clean rooms at the same pace as data usage grows. In order to continue to advance technology and enhance supply capacity, we need to adopt new ideas for building production lines. We need a smaller equipment footprint, shorter cycle time and higher throughput."Semiconductor market shows signs of recoveryIn their discussion of the short-term outlook for the semiconductor market, Shimizu and Koike pointed to the importance of strengthening the talent pool of Japan’s semiconductor industry as global competition heats up with China’s pursuit of semiconductor independence and the industry pulls out of the 2019 slowdown fueled by weak memory prices. While Sony’s business has been buoyed by strong image sensor demand for smartphones, the devices “did very well, but other applications didn't," Shimizu said. Even the image sensor market stagnated.Despite the 2019 slump, market conditions and capital investments by semiconductor manufacturers have been on the upswing."In the second half of 2019, the Chinese market showed signs of recovery triggered by 5G,” Shimizu said. “In 2020, this movement is going to be in full swing around the world and we will be busier than last year."Koike agreed: "The semiconductor market for data centers will recover with 5G. The hard disk shortage is already an indication of a recovery, a turnaround that will undoubtedly extend to solid state drives (SSDs). In addition, advances in autonomous driving technology will ensure continued growth of the automotive semiconductor industry.”Japan should embrace international competition, not fear China's pursuit of chip independenceIt's no secret that China is investing heavily in its semiconductor development capabilities to move up the microprocessor value chain. Minamikawa posed the question: How should Japanese chip companies navigate the shifting regional balance of power? "It is natural for China to strive to establish domestic procurement of semiconductors that are fundamental technologies for various industries,” Koike said, “I think the efforts of Chinese companies are outstanding in that they are not pursuing short-term results, such as improving yields in the near future, but are making efforts with an eye to achieving results in 10 years. Japan has a variety of options including working with China to create joint ventures and competing head-on. Regardless of which choice we make, however, it is imperative for the survival of domestic companies that Japan maintains its technological competitiveness to remain ahead of China."Shimizu said that Sony’s “Chinese customers are quick to take action and study extremely hard. We often have opportunities to share our roadmap with them and explore innovation opportunities together. Before, they were passive and relied on us for insights into new technologies, but now they are more assertive and I sense that they will start to drive innovation.”Koike added that "although Japanese companies often talk about business globalization, neither Chinese nor American companies say much about it. While global expansion is a major requirement for business, I think Japanese companies need to focus more on the Japanese market overall, not just when they think about the growing competitiveness of Chinese companies." L-R: Akira Minamikawa, Research Director of Technology Research at IHS Markit; Atsuyoshi Koike, president at Western Digital Japan; Terushi Shimizu, representative director and president at Sony Semiconductor Solutions Talent key to bolstering competitiveness of Japan’s semiconductor industryMinamikawa of IHS Markit didn’t mince words in describing the talent shortage in the Japanese semiconductor industry as “grave,” saying that “the workforce challenge is not endemic to the electronics industry as evidence grows that the number of people obtaining doctorates in Japan is falling and the educational level of the Japanese population as a whole is in decline.”Three years ago, Shimizu interviewed professors on Kyushu island for insights into Japan’s talent shortfall. He came away feeling that “Japanese semiconductor companies were not sufficiently communicating the industry's talent and innovation needs to professors. To help professors and students better grasp the appeal and potential of the industry, we have started to send frontline engineers to universities to educate students and instructors about their work and careers. Expecting corporate HR departments to alone solve the talent shortage won’t work.”"In Japan, if you advance to a doctoral course, you will have a hard time getting a job, which is a strange situation,” Koike said. “Companies and universities need to work together more closely to better understand how to attract and hire doctoral graduates."Minamikawa said companies must have strong leaders with clear missions to attract the right talent, but Koike pointed to the drawbacks: "The image of a company with a strong leader seems to be cool, but it also has a downside because engineers stop thinking for themselves and wait for instructions from the top. I believe it is important for company leaders to have ongoing discussions at all organizational levels and lead the way in times of confusion."Shimizu agreed, citing his own company as an example."Thankfully, our company is very busy right now,” he said. “However, some employees are starting to request more time to think about how to improve the quality of their work. To maintain and strengthen our competitiveness and continue business growth, I believe it is important to cultivate an environment that encourages each employee to take more time to think for themselves."Motoaki Ito is the CEO of Enlight, Inc. and a reporter for SEMI. Mayumi Amagai is a marketing manager at SEMI Japan.

We are living in a digital world where semiconductors are taken for granted, AI is bringing semiconductors back into the deserved spotlight, and now we are witnessing the dawn of the Cognitive Era enabled by semiconductors,” SEMI president and CEO Ajit Manocha said to an audience of more than 500 during his presentation – Rebirth of the Semiconductor Industry – at the First Global IC Entrepreneur Conference.Speaking at the Shanghai event in mid-December, Manocha recalled how, when he first entered the semiconductor industry in the 1980s, semiconductors revenue topped out at about $10 billion. Now, with sales having swelled to a staggering $450 billion, the industry is on a much faster growth track. Revenue could reach $500 billion by the end of 2020 and trillions of dollars by 2030. Over the past two decades, chips have given rise to social media and e-commerce powerhouses such as Google, Facebook, and Alibaba. All rely on heavily on chips, the engines of data centers across all industries. Wave after wave of technology innovation have been powered by semiconductors – from mainframe computers in the 1970s, personal computers in the 1980s, the Internet in the 1990s, and mobile and social networking in the early 20th century, to the current shining stars of technology such as IoT, big data, new memory, virtual reality, autonomous driving and artificial intelligence, Manocha said. New applications across areas such as smart manufacturing and digital healthcare are stoking the latest round of semiconductor growth.The rise of AI, like all the technologies before it, has renewed the semiconductor industry once again with its promise to drive growth of all industries worldwide, Manocha said. Five years ago, IoT was but a gleam in a technologist’s eye, more hype than reality with doubt about its viability running deep. Today, with about 60 percent of people in the world connected to the Internet, the enormous promise and potential of IoT is flowering. Industry growth will explode as the melding of AI and IoT birth countless applications and innovations in SMART transportation (0 emissions; 0 fatalities; 0 congestion), smart sensors (agriculture, infrastructure, healthcare) and SMART “Everything” (people, devices, homes, cities, industries, and the list goes on). Indeed, AI is now widely recognized as a chief growth driver of the semiconductor industry well into the future, with semiconductor technology at the core of AI innovation, he said. Semiconductors are thrusting the fifth industrial revolution into the fast lane. China’s much-anticipated rise as an industry powerhouse over the next few years will only accelerate industry growth, turning current disruptions into future opportunities as SEMI China continues to cultivate connection, collaboration and innovation in China’s fast-growing semiconductor sector.Cherry Sun is a marketing manager at SEMI China.

Even for someone who has been in this industry since the days of the TI Datamath 4-function calculator and the TMS1100 4-bit microcontroller (yes, that’s been a LONG time – the movie Grease premiered the same year!), it is sometimes hard to grasp the scope and complexity of what happens in today’s leading-edge semiconductor gigafabs. In fact, the only way to comprehend the enormous volume of transactions that occur is to consider what happens in a single minute – this is illustrated in the infographic we have labeled “The Gigafab Minute.”* It’s amazing enough to think that a single factory can start 100,000 wafers every month on their cyclical journey through 1500 process steps… and have 99%+ of them emerge 4 months later to be delivered to packaging houses and then on to waiting customers. It’s quite another to realize that all of this happens continuously (24 x 7) and automatically. “How is this possible?” you ask.Well, a big part of the solution is the body of SEMI standards which have evolved since the early 80s to keep pace with the ever-changing demands of the industry. From an automation standpoint, many of these standards deal with the communications between manufacturing equipment and the factory information and control systems that are essential for managing these complex, hyper-competitive global enterprises.A significant characteristic of these standards is that they have been carefully designed to be “additive.” This means that new generations of SEMI’s communications standards do not supplant or obsolete the previous generations, but rather provide new capabilities in an incremental fashion. To appreciate the importance of this in actual practice, consider how the GEM, GEM300, and EDA/Interface A standards support the transactions that occur in a single Gigafab Minute.Starting at 1:00 o’clock on the infographic and moving clockwise, you first notice that 2.31 wafers enter the line. Of course, these are actually released in 25-wafer 300mm FOUPs (Front-Opening Unified Pod), but 100K wafers per month translates to 2.31 per minute. Since these factories run continuously, once the line is full, it stays full. And with an average total cycle time of 4 months, this means that there are 400K wafers of WIP (work in process) in he factory at any given time. This number, and the total number of equipment (5000+), drive the rest of the calculations.GEM (Generic Equipment Model) – SEMI E30, etc.The GEM messaging standards were initially defined in the early 90s to support the factory scheduling and dispatching applications that decide what lots should go to what equipment, the automated material handling systems that deliver and pick-up material to/from the equipment accordingly, the recipe management systems that ensure each process step is executed properly, and the MES (Manufacturing Execution System) transactions that maintain the fidelity of the factory system’s “digital twin.”Every minute of every day, GEM messages support and chronicle the following activities: 240 process steps are completed (i.e., 240 25-wafer lots are processed), 300 recipes are downloaded along with a set of run-specific adjustable control parameters, and 600 FOUPs are moved from one place to another (equipment, stockers, under-track storage, etc.). For each of these activities, the factory’s MES is notified instantaneously.GEM300 – SEMI E40, E87, E90, E94, E157With the advent of 300mm manufacturing in the mid-to-late 90s, a global team of volunteer system engineers from the leading chip makers defined the GEM300 standards to support fully automated manufacturing operations. Starting at 5:00 o’clock on the infographic, the number of transactions per minute jumps almost 3 orders of magnitude, from the monitoring of 900 control jobs across 4000 process tools to the tracking of 360,000 individual recipe step change events. This level of event granularity is essential for the latest generation of FDC (Fault Detection and Classification) applications, because precise data framing is a key prerequisite for minimizing the false alarm rate while still preventing serious process excursions. In this context, more than 6000 recipe-, product- and chamber-specific fault models may be evaluated every minute.Simultaneously, the applications that monitor instantaneous throughput to prevent “productivity excursions” and identify systemic “wait time waste” situations depend on detailed intra-tool wafer movement events. In a fab with hundreds of multi-chamber, single-wafer processes, 75,000 or more of these events occur every minute. EDA (Equipment Data Acquisition) – SEMI E120, E125, E132, E134, E164, etc.Rounding out the SEMI standards in our example gigafab is the suite of EDA standards which complement the command and control functions of GEM/GEM300 with flexible, high-performance, model-based data collection. The EDA standards enable the on-demand collection of the volume and variety of “big data” required from the equipment to support the advanced analysis, machine learning, and other AI (Artificial Intelligence) applications that are becoming increasingly prevalent in leading semiconductor manufacturers. As EUV (Extreme Ultraviolet) lithography moves from pilot production to high-volume manufacturing at the 7nm process node and beyond, the litho process area will become a major source of process data by itself, generating 10 GB of data every minute. This is in addition to the 100 GB of data collected from other process areas. The End ResultThe final wedge (12:00 o’clock) in our infographic highlights the real objective – which is producing the millions of integrated circuits that fuel our global economy and provide the technologies that are an integral part of our modern way of life. Assuming a nominal die size of 50 square mm (typical of an 8 GB DRAM), the 2.31 wafers we started at 1:00 o’clock result in almost 3200 individual chips. But none of this would be possible without the pervasive factory automation technology we now take for granted. So, as you finish reading this posting on whatever device you happen to be using, take a micro-moment to acknowledge and thank the hundreds of standards volunteers whose insights and efforts made this a reality!You may not be responsible for running a gigafab anytime soon, but the SEMI standards used in this setting are no less applicable to any Smart Manufacturing environment. Give us a call if you’d like to know more about how these technologies can benefit your operations for many years to come.Alan Weber is Vice President, New Product Innovations, at Cimetrix Incorporated. Previously he served on the Board of Directors for eight years before joining the company as a full-time employee in 2011. Alan has been a part of the semiconductor and manufacturing automation industries for over 40 years. He holds bachelor’s and master’s degrees in Electrical Engineering from Rice University. For more information on SEMI Standards, please click here.

A Communication ProblemAs the industry ventures towards a more connected world, the semiconductor test community is facing increasingly stringent performance, quality and reliability targets, particularly in the high-stakes automotive, communications, and medical sectors. It is, therefore, important for device makers to know how their components will perform before their products hit the road, reach for the skies, or get placed inside the body. Access to test data is critical to mitigating failure risks. Yet many challenges are associated with accessing test and manufacturing data. One hurdle is that component suppliers are often reluctant to provide test data for fear of revealing sensitive information about their design and/or manufacturing IP. With customers sourcing their components from multiple vendors, IP leakage is a valid concern and, consequently, a barrier to access. Certainly, these issues can be negotiated contractually, but only after striking the delicate balance between access and cost. Beyond access, the quality of test data itself – which can be fragmented and even corrupted – is not always assured. As a device moves through the typical product flow (i.e., fab to sort to assembly to test), it inevitably changes hands (e.g., from foundry to OSATs). As a result, information about the device can become a patchwork of data where formats vary and certain fields, at times, may get overwritten. These potential gaps in test data flow underscore the need for consistent communications of manufacturing information from one process or stakeholder to the next. While standardization could help, it is currently lacking in many of these critical data-flow chains in the manufacturing, test, and assembly areas. An Industry Alliance Aimed at Solving Test Industry ProblemsEfforts to establish standardized solutions to these test industry issues are under way by the SEMI Collaborative Alliance for Semiconductor Test (CAST) Special Interest Group. CAST activities are currently structured around establishing standards on data formats, communication protocols, and chip traceability.Rich Interactive Test Database (RITdb)While Standard Test Data Format (STDF) is widely used in the semiconductor industry, it does not directly support the new use models in today’s test environment, such as real-time or pseudo real-time queries, adaptive test and streaming access. The STDF V4 record format is not extendible and, because the standard itself can be imprecise, it tends to result in many interpretations. These limitations become apparent when there is a need for more efficient and flexible format to manage “big test data.”The RITdb group has been working on the next-generation format following STDF to allow more flexibility in data types and support for adaptive test. The group aims to provide a standards-driven data environment for semiconductor test including simple standards-based data capture, transport and relationship model for eTest, probe, and final test data. Its work also seeks to support equipment configuration management and operational performance data. More importantly, RITdb enables a real-time streaming model that provides the ability to collect and monitor data/systems from sand to landfill.Real Time Adaptive Test (Courtesy HIR)Work by the RITdb group will ultimately be developed into SEMI Standards. The SEMI Standard spec will be in MS Word while the database itself in a different format. A spec editor will help ensure it is used correctly. The group also plans to expand the spec beyond probe and final test. Meanwhile, the group is working to streamline RITdb and implement different extensions (e.g., tester log, streaming). Additional work will be needed on probe maps and test cases (i.e., be able to run verifiers to validate the spec).Tester Event Messaging for Semiconductors (TEMS)Today, semiconductor testing continues to see a surging demand for real-time data analysis, real-time ATE input and control of the test flow to improve test yield, throughput, efficiency, and product quality. At the same time, test equipment and test operations around the world use a diverse range of data formats, specifications, and interface requirements that drive up customer service and application engineering costs for ATE vendors, OSAT companies, IDM test operations, software providers, and handler equipment. A common ATE hardware and software communications interface would help reduce the cost, time and complexity of integrating ATE equipment into data-intensive test operations.Overview of Test Cell CommunicationThe TEMS group was chartered to develop a standardized ATE data messaging system based on industry-standard internet communication protocols between a test cell host and a server. The standard will be limited to ATE data messaging, using RITdb entity types as applicable, standard data format, and control requirements. It will have no impact on other test communication interfaces such as those involving handlers, probers, test instrumentation, and other systems covered by existing standards (e.g., SEMI E30, E4, E5, STDF). The group is developing a set of standards to define a vendor-neutral way to collect test cell data. The primary spec defines the model while a subordinate spec defines the transport layer to maintain consistency with prior standards.Chip ID TraceabilityChip ID Traceability is the most recent group formed under CAST. The group’s formation came on the heels of the 2017 CAST Workshop that focused on Component System Level Test. SLT is widely considered a burden that most chip manufacturers prefer to avoid, but it is essential to achieving lower DPPM (Defective Parts Per Million) goals at system level. The cost to develop and maintain SLT equipment in-house and at OSATS is significant. SLT test engineering requires different skills than regular ATE test engineering. The engineers must understand the final application environment and the data flow that is subjected to the component. Defect causes need to be isolated and communicated back to the vendor or ATE test engineer for corrective action. Mapping such SLT failures back to the ATE production tests is a big, labor-intensive challenge.Component traceability is a big concern. Most newer technologies have ECID (Electronic Chip Identification). However, many product types representing significant volumes do not provide ID traceability. Without component-level traceability, it is extremely difficult to analyze failures and drive corrective action. Additionally, there is basic manufacturing data, including chip ID, that is needed across the supply chain, but this is often blocked and difficult to obtain from suppliers. Such data analysis is difficult across "silos" due to sharing/security barriers. Die-level Identification Traceability (I T) ModelThe Chip ID Traceability group was chartered to develop a standardized approach for enabling traceable die-level identification (ID) throughout the IC manufacturing, test, and assembly processes to the point of use in the final system. The approach defines the use of a simple, unique identifier that IC suppliers and board-level manufacturers can use to communicate about a specific device for the purposes of performance or failure analysis. The identifier will enable suppliers and customers to communicate specific component information and, with NDAs (non-disclosure agreements) in place, send manufacturing data back and forward through the supply chain for data analysis. The group is developing a standardized model focusing on key concepts, behaviors, and requirements for enabling die ID and traceability. The model defines minimum chip ID and traceability for new design and manufacturing implementation as well as for backwards compatibility with existing methods. The resulting standard would apply to different chip configurations ranging from single integrated circuits to multi-chip/3D structures. It can be adapted for use with a range of technologies, ranging from legacy systems to the latest in electronic chip identification (ECID). A copy of the draft proposal can be downloaded here. The Chip ID Traceability group is soliciting feedback to the document. Please contact Paul Trio at SEMI ([email protected]).