agriculture

New treatments for vascular disease. Optimized agricultural production. Beefed up performance of wearable devices and flexible displays. Four students with their sights set on making the world a better place won Innovators of the Future awards at the 20th Annual FLEX Conference in late February after presenting novel ideas for advancing flexible electronics in the popular student poster event. It was clear that all of these young innovators are working on projects with the potential to impact our lives in the near future. Their work is critical to advancing products, devices and basic research in flexible electronics. Posters created by the 17 students who competed for the awards were judged by a multidisciplinary panel of industry experts. The posters reflected a broad range of applications enabled by flexible hybrid devices and covered technology for wearables, medical devices and precision agriculture. Innovators of the Future Award Winners Robert Herbert from the Georgia Institute of Technology won first place for his paper Smart and Connected Stent System with Nanomembrane Soft Sensors for Wireless Monitoring of Hemodynamics. Vascular diseases are the leading cause of death worldwide, accounting for over 30% of all fatalities. Early diagnosis and monitoring blood pressure and flow rates are critical to effective treatment. Herbert’s poster introduced a less costly, less invasive and more revealing (spoiler alert) sensor system that uses a flexible, wireless biosensor system with an inductive medical stent and capacitive pressure sensors. The laser-machined stent uses multi-layered material integration to function as an inductive coil for wireless communication while maintaining mechanical properties similar to conventional vascular stents. The stent and sensor system can be easily deployed using conventional catheter procedures. Watch his presentation. Jose Waimin from Purdue University’s School of Materials Engineering was one of two second-place winners for his poster that shows how real-time monitoring of ion concentration, moisture, pH, microbial activity and other key metrics in agricultural production can optimize crop yields while reducing environmental impacts. His work presented a scalable alternative for manufacturing low-cost flexible sensors that can be used in an array of applications. Electrodes are manufactured in a Roll-to-Roll (R2R) process to enables fast production at a very low cost per device. Watch his talk. Benham Garakani from Binghamton University, Center for Advanced Microelectronics Manufacturing (CAMM) was the other second-place winner for his paper Electromechanical Behavior of Flexible Silver Paste and Highly Stretchable Liquid Metal for Wearable Electronics. Garakani explored how to improve fabrication of reliable, comfortable wearable devices to boost performance and functionality using substrates such as nonwoven high-density polyethylene fibers (HDPE) and thermoplastic polyurethane (TPU). Garakani also examined the electromechanical reliability of screen-printed silver trace on HDPE fibers and stencil-printed liquid metal (Ga-In-Sn alloy) on TPU during isothermal fatigue cycling. Watch his presentation. Sridhar Sivapurapu from the Georgia Institute of Technology won third place for his poster Flexible and Ultra-Thin 30µm Glass Substrates for RF and mmWave Flex Applications. Sivapurapu’s poster addressed the increasing demand for maximizing the mechanical flexibility of flexible displays while maintaining or improving their electrical performance. Sivapurapu focused on both electrical and mechanical properties for determining the viability of ultra-thin glass stack-ups for flexible RF applications by benchmarking the electrical performance of the ultra-thin glass stack-up to 110 GHz. He also examined electrical characterization during bending tests using free arc bending. Watch his talk. The Innovators of the Future award was sponsored by FlexEnable, a technology provider that develops flexible organic electronics technologies and OTFT materials. All FLEX Conference 2021 presentations are available through March 26, 2021 by registering for the event. Gity Samadi is co-chair of the FLEX Conference student poster awards and program manager at SEMI FlexTech.

Part 2 of 2-part series on MSEC 2019 highlights. Read Part 1. Neural Networks on ChipTo be sure, low power is king when bringing machine learning to the sensor edge. Battery-powered, always-on sensing devices require it since frequent recharging is the death knell of any electronic product. That’s why semiconductor companies are offering new ways to conserve power.“MEMS sensor suppliers have made significant strides in the power, size and performance of their devices,” said Aspinity CEO Tom Doyle. “Yet these gains deliver only incremental power improvements to the system.”Doyle advocates a new architectural model that uses an analog neuromorphic processor to analyze all sensor data at the start of the signal chain instead of sending it downstream so power-hungry chips such as DSPs can digitize it before analysis.“The technology industry wants to take advantage of the many benefits of always-on sensing applications,” said Doyle. “Before we can reach mass proliferation, however, we need to resolve the power issues that are deal-breakers for some applications. We believe the answer to this challenge is architectural. All the data gathered by always-on sensing systems is analog in nature, yet as soon as it’s captured, it’s digitized immediately for analysis. Determining which data is important up front eliminates the digitization and processing of irrelevant data so that voice-first devices such as smart speakers and wearables/hearables can run for long periods of time without requiring battery recharge.”Syntiant CTO Jeremy Holleman agreed that on-device intelligence is the future.“Did you just fall? Is your heartrate a bit off? Deep learning provides a toolset that yields vastly superior decisions,” said Holleman. “The problem is that deep learning is computationally intensive. The answer is a neural network that performs on-device edge inferencing.”Holleman added that Syntiant’s neural decision processor was recently certified as Amazon Voice Service (AVS)-compliant for wake-word detection, making it easier to design voice control in battery-powered devices such as earbuds and wearables.MSEC Technology Showcase WinnerWith the groundswell of interest in intelligence at the edge, it was no surprise that Cartesiam won top honors among all competitors in the MSEC Technology Showcase for its NanoEdge AI, software that brings AI to the edge of the signal chain, making it easier for designers to create intelligent objects that can learn and understand.“Unlike other AI algorithmic technologies for sensing devices, NanoEdge enables both learning and inference at the edge, providing accurate and adaptive intelligence,” said Cartesiam Managing Director and Co-founder Marc Dupaquier, who accepted the award. “It’s also the only tool of its kind that does not require data scientists on board for implementation, which saves a tremendous amount of money. Our clients can build a machine learning library and embed it into their own code within weeks to realize the same caliber of unsupervised neural network that was once the exclusive domain of AI cloud vendors.”MSIG 2019 Hall of FameAt this year’s conference, MSIG Director Carmelo Sansone recognized two longtime contributors to the commercialization of MEMS and sensors: Peter G. Hartwell, Ph.D., chief technology officer at InvenSense, a TDK group company; and Thomas Kenny, professor and senior associate dean of engineering at Stanford University.Hartwell leads technology strategy and the InvenSense advanced technology research group. He has more than 25 years’ experience commercializing silicon MEMS products, including advanced sensors and actuators, and developing MEMS testing techniques.Kenny’s academic accomplishments include authoring or co-authoring more than 250 scientific papers and holding 50 issued patents. He has also advised more than 50 graduated Ph.D. students from Stanford.MSEC 2020Mark your calendar for next year’s MSEC, October 12-14, at Coronado Island Marriott Resort Spa in Coronado, Calif. Get updates from MSIG on MSEC and other upcoming events including MSTC 2020.Stay in Touch with MSIGMEMS Sensors Industry Group (MSIG), a SEMI Strategic Association Partner, is the industry association representing the global MEMS and sensors supply chain. To learn how MSIG enables professionals in the MEMS and sensors industry to innovate, address common challenges and accelerate business results, visit us today.Connect with MSIG on Twitter and LinkedIn. Subscribe to SEMI Blog: Technology and Trends.Maria Vetrano is a public relations consultant at SEMI.

Part of 1 of 2-part series on MSEC 2019 highlights. Read Part 2. MEMS and sensors are proliferating across consumer, automotive, biomedical/healthcare, robotics, industrial and agriculture applications to harvest sensory data in a hyper-connected world and meet demand from consumers and organizations alike as they clamor for more intelligence in electronics.Take the ubiquitous iPhone. Shipped in 2007, Apple’s first iPhone sported five sensors. By contrast, the most feature-packed smartphones will embed up to 20 sensors by 2021, according to Yole Développement’s Jérôme Azémar. He estimates that the devices will feature four MEMS microphones, four CMOS image sensors (CIS), a RGB color sensor, a laser rangefinder, an infrared sensor, a gas sensor, a heart rate monitor and a fingerprint sensor, not to mention the MEMS inertial sensors that device users have come to know and trust.The MEMS market is expected to reach $18.5 billion in 2024 [1], up a whopping 60 percent from $11.6 billion in 2018, according to Azémar, who presented at MEMS Sensors Industry Group’s 15th annual MEMS Sensors Executive Congress (MSEC) in late October in Coronado, Calif. Add other types of sensors to the mix – CIS, environmental sensors, LiDARs, radars, ultrasonics, and fingerprint sensors – and the market will mushroom to $93 billion by 2024, said Azémar.Since MEMS Sensors Industry Group (MSIG) joined SEMI as a Strategic Association Partner three years ago, SEMI has expanded its MEMS and sensors programs to Europe and Asia while continuing to grow its U.S. conferences. “SEMI is continually investing in MEMS and sensors innovation across the supply chain,” said Dave Anderson, president of SEMI Americas and host of MSEC. “For example, MSIG is contributing to the development of the Heterogeneous Integration Roadmap, an initiative designed to drive heterogeneous integration technology development and accelerate electronics innovation. The roadmap spans device design, test and fabrication, ecosystem development, R D, equipment and materials. “At MSEC, executives and other speakers explored how AI and blockchain are remaking the food supply chain, air transportation and other sectors as MEMS and sensors improve the quality of our lives,” said Anderson.Sensing at the EdgeThe concept of artificial intelligence (AI), that a machine can harness intelligence that rivals or outperforms humans – and act without human intervention – has been a feature of the human imagination since at least the 1968 film 2001: A Space Odyssey. MEMS and sensors facilitate intelligence in a wide range of electronics such as smartphones, healthcare wearables, robots, industrial predictive maintenance systems, and cars. AI is sure to augment that functionality.MEMS and sensors are now in their third wave of evolution, a focus on edge AI, Bosch Sensortec CEO and General Manager Stefan Finkbeiner told MSEC attendees. For its part, Bosch is working to add AI to MEMS devices. The first wave integrated software with MEMS sensors, and the second, sensor fusion, enabled designers to allocate performance and power strategically to tune MEMS for resource-constrained devices. The third wave is “an active-learning phase in which MEMS facilitates real-time learning at the edge to promote greater personalization, environmental feedback, privacy of user data and improved battery life,” said Finkbeiner.Small sensor nodes with edge AI exemplify third-wave applications. Integrating low-power environmental sensors (e.g., gas, temperature, pressure, humidity and air-flow sensors), the nodes could be deployed in fire-prone forests to assess fire risk and support early detection. Access to this real-time environmental information could prove invaluable to residents and public-safety personnel alike.Google takes another tack, applying machine learning to resource-constrained devices, said Nick Kreeger, a senior software engineer at the Internet giant. The company’s Google Brain creates machine learning models that can run on inexpensive, low-power microcontrollers using Google’s TensorFlow Lite, an open-source machine learning tool that’s been deployed on a multitude of mobile devices. Inferencing is done at the device’s edge, rather than transmitted to the cloud.Meeting the power constraints of battery-powered sensing devices is another matter that starts with minimizing energy and data waste. “Deep learning is compute-bound and runs well on existing microcontrollers,” Kreeger said. “Because it’s all arithmetic, it’s low-power compared to storage access.”Already Google has worked with Plant Village, a research unit at Penn State University, and the International Institute of Tropical Agriculture (IITA) to help farmers improve food production by using machine learning and cheap sensors to spot and manage planet diseases in developing countries. And that production chain is in dire need of a boost, according to Rajendra Rao, general manager of IBM Food Trust, an enterprise-class blockchain solution.“We are on the cusp of complete failure of the food system,” Rao said. “One out of 10 people gets sick each year from foodborne illness, 420,000 die from this annually, 80 percent of companies in the food supply chain have not digitized, one-third of all fresh food in the US is thrown away, and one in five seafood samples worldwide is mislabeled.”IBM Food Trust’s work with Sucafina, which manages a global green coffee supply chain, shows how sensors can trace food from the farm to the processing plant to the consumer. With the IBM Food Trust platform, Sucafina can track the origin of the beans used in a cup of coffee – a competitive differentiator to coffee drinkers eager to support fair-trade coffee roasters.ripe.io, one of Forbes’ 25 most innovative AgTech startups, is also tackling the challenges and complexities of the food supply chain.“Our secure blockchain platform creates a digital twin of food items, transparently aggregating foods’ journey in real-time, to provide a harmonized trustworthy platform for multiple stakeholders,” said Rachel Gabato, the company’s COO. The ripe.io blockchain-based platform collects data from various sensors – temperature, pressure, light, humidity and inertial MEMS sensors. Growers, distributors and end customers including sweetgreen – a U.S. restaurant chain that depends on fresh produce – use the information to trace the origin and quality of food.MSEC 2020Mark your calendar for next year’s MSEC, October 12-14, at Coronado Island Marriott Resort Spa in Coronado, Calif. Get updates from MSIG on MSEC and other upcoming events including MSTC 2020.Stay in Touch with MSIGMEMS Sensors Industry Group (MSIG), a SEMI Strategic Association Partner, is the industry association representing the global MEMS and sensors supply chain. To learn how MSIG enables professionals in the MEMS and sensors industry to innovate, address common challenges and accelerate business results, visit us today.Connect with MSIG on Twitter and LinkedIn. Subscribe to SEMI Blog: Technology and Trends.[1] Source: Status of the MEMS Industry report, Yole Développement, 2019Maria Vetrano is a public relations consultant at SEMI.

In the long unfolding arc of technology innovation, artificial intelligence (AI) looms immense. In its quest to mimic human behavior, the technology touches energy, agriculture, manufacturing, logistics, healthcare, construction, transportation and nearly every other imaginable industry – a defining role that promises to fast track the fourth Industrial Revolution. And if the industry oracles have it right, AI growth will be nothing shy of explosive.“The gains these days are not incremental,” said Ajit Manocha, SEMI president and CEO, said to a gathering in July of the Chinese American Semiconductor Professional Association (CASPA) for its Summer Symposium at SEMI’s headquarters in Milpitas. “They are hockey stick – exponential – with AI semiconductors growing in market size from $4 billion this year to $70 billion in 2025.”Manocha left little doubt that AI is remaking the semiconductor industry and, in the process, the world at large. Internet of Things (IoT) and 4G/5G, both key AI enablers, will account for more than 75 percent of device connections by 2025.“Today, 30 billion devices worldwide are connected,” Manocha said, citing an Applied Materials prediction that the number of connected devices globally will grow to between 500 billion and 1 trillion by 2030. Those devices will generate stunning amounts of data collected, interpreted and used to reason, solve problems, learn and plan, leading to the holy grail of autonomous machine behavior.To process this colossal amount of data central to the promise of AI, the industry must break through the limits of a key technology: memory. Memory a Critical AI BottleneckThe challenge for memory starts with performance. Historically, every decade gains in compute performance have outpaced improvements in memory speed by 100 times, and over the past 20 years that gap has grown, said Steven Woo, a fellow and distinguished inventor at Rambus, presenting at the symposium. The upshot is that memory has bottlenecked compute and, in turn, AI performance. The industry has responded with new ways to implement memory systems on AI chips. Each is suited to unique performance requirements and, of course, comes with trade-offs. Among the frontrunners: On-chip memory delivers the highest bandwidth and power efficiency but is limited in capacity. HBM (High Bandwidth Memory) offers both very high memory bandwidth and density. GDDR balances trade-offs among bandwidth, power efficiency, cost and reliability. Since 2012, AI training capability has grown 300,000 times, besting Moore’s law by 25,000 times in doubling every 3.5 months, a blistering pace compared to the 18-month doubling cycle of Moore’s law, Woo said. The staggering improvements have been driven by parallel computing capacity and new application-specific silicon like Google’s Tensor Processing Unit (TPU).These specialized silicon architectures and parallel engines are key to sustaining future gains in compute performance and combatting the slowing of Moore’s Law and the end of power scaling, Woo said. By rethinking the way processors are architected for certain markets, chipmakers can develop dedicated hardware capable of operating with 100 to 1,000 times greater energy efficiency than general purpose processors to overcome another big limiter to scaling compute performance – power.For its part, the memory industry can improve performance by signaling at higher data rates and using stacked architectures like HBM for greater power efficiency and performance, and by bringing compute closer to the data.Memory scaling for AIA key challenge is scaling memory for AI. Demand for better voice, gesture and facial recognition experiences and more immersive virtual reality and augmented reality interactions is tremendous, said Bill En, senior director at AMD, speaking at the symposium. These capabilities require more processing power across both high-performance computing (HPC) for big data analytics and machine learning as it relies on AI and machine intelligence to generate meaningful insights. Emerging machine learning applications include classification and security, medicine, advanced driver assistance, human-aided design, real-time analytics and industrial automation. And with 75 billion IoT-connected devices – all generating data – expected by 2025, there will be no shortage of data to analyze, En said. The wings alone of a new Airbus A380-1000 feature some 10,000 sensors.Mountains of this data are stored in massive data centers on magnetic hard drives, then transferred to DRAM before moving to SRAM within the CPU for the handoff to the compute hardware for analysis.With data growing at an exponential clip, the question is how to make sure all other memory systems can handle the flood of data. AMD’s answer is a chiplet architecture featuring eight smaller chips around the edge that drive the compute and a large chip in the center that doubles the IO interface and memory capability to in turn double chip bandwidth.AMD has also moved from a legacy GDDR5 memory chip configuration to HBM to bring memory bandwidth closer to the GPU for more efficient processing of AI applications. The HBM provides much higher bandwidth while reducing power consumption. Compared to DRAM, AMD’s HBM delivers a much faster data rate and far greater memory density, En said.Over the next decade, look for more performance improvements from multi-chip architectures, innovations in memory technology and integration, aggressive 3D stacking and streamlined system-level interconnects, he said. The industry will also continue to drive performance gains in devices, compute density and power through technology scaling.Michael Hall is a global marketing communications manager at SEMI.

At the SEMI FLEX 2019 and MEMS Sensors Technical Congress (MSTC) (MSTC) February 18-21 in Monterey, California, I had the pleasure of meeting many old friends and colleagues as well as making some great new acquaintances. With MEMS and sensors still a relatively young industry, I am delighted that our community is thriving. We continue to see double-digit growth rates, there is plenty of innovation, and the technology generates massive amounts of data that gets everyone excited about artificial intelligence, deep and machine learning, and blockchain. Those are all the buzzwords that any tech startup needs for funding these days.While it is hard to single out any one presentation at conferences, I was particularly struck by Nadia Shakoor’s keynote address, “Driving Advances in Crop Breeding and Smart Farm Management.” From Nadia I learned that the world’s largest agriculture sensing platform was a mere 45 minutes south of where I live in Phoenix, Arizona. This is a major embarrassment to admit as I have lived here for almost 30 years, have been involved in MEMS and sensors for a decade, and have a particular passion for the use of sensors in agriculture and food to improve crop yields and food quality, and to reduce food waste. This humongous sensor was hiding in plain sight right under my nose!After Nadia’s keynote, I just had to speak to her at the break. Nadia is the senior research scientist and project director for TERRA-REF at the Danforth Plant Science Center based in St. Louis, Missouri. Nadia’s work employs field-level crop phenomics, the biological study of the set of physical and biochemical traits belonging to a given organism (phenomes). Phenomes are fascinating because they change in response to genetic mutation and environmental influences. The Danforth Plant Science Center and its partners are involved in many phenotyping projects using autonomous vehicles, drones, field scanners, satellite imaging and more.After the FLEX MSTC event, I emailed Nadia to ask if I could visit the field scanner and her partner team at the University of Arizona in Maricopa, Arizona. She kindly introduced me to Maria Newcomb, a plant research scientist at the site, who gave me a good look at this mother of all field scanners: the Transportation Energy Resources from Renewable Agriculture Phenotyping Reference Platform (TERRA-REF). TERRA-REF aims to transform plant breeding by using remote sensing to quantify plant traits such as plant architecture, carbon uptake, tissue chemistry, water use and other features to predict the yield potential and stress resistance of 400+ diverse sorghum lines. The TERRA-REF Field Scanner at the University of Arizona Maricopa Agricultural Center. It’s the largest field crop analytics robot in the world, one that’s critical to the crop research underway at the Donald Danforth Plant Science Center in St. Louis, Missouri. Source: Steve Whalley TERRA-REF’s Lemnatec Field Scanalyzer is the largest field crop analytics robot in the world. This high-throughput phenotyping field-scanning robot has a 30-ton steel gantry that autonomously moves along two 200-meter steel rails that have recently been extended another 170 meters. It continuously images the crops growing below it by using a diverse array of cameras and sensors to observe the field at a dense-collection frequency with high resolution. These sensors include RGB stereo; thermal, chlorophyll fluorescence imaging system; hyperspectral cameras; a 3D laser scanner; and environmental monitors.Plant breeding is currently limited by the speed at which phenotypes can be measured, and the information that can be extracted from these measurements. Current instruments used to quantify plant traits do not scale to the thousands or tens of thousands of individual plants that need to be evaluated in a breeding program. The TERRA-REF field scanner system, on the other hand, uses sensors to scan over one acre of plants, collecting thousands of daily measurements throughout the growing season, and these are used to determine plant phenotypes and inform breeding decisions. TERRA-REF’s advanced sensor technologies include: Hyperspectral (250nm-2500nm) Thermal Infrared 2D and Stereo RGB PSII chlorophyll fluorescence 3D laser Environmental sensors The TERRA-REF field scanner platform features a massive sensor-rich scanner head. Source: Steve Whalley The humongous TERRA-REF field-scanner was certainly a sight to behold, looming like a cargo-ship container crane in the vast flat plains of the Arizona desert landscape. I’ve only scratched the surface of what this enormous sensor platform can accomplish so if you are a MEMS/sensor company interested in agriculture and food production, I encourage you to get more information at terraref.org and pay a visit next time you are in the area.Steve Whalley, CEO, Strategic World Ventures, is a strategic consultant to SEMI-MEMS Sensors Industry Group (MSIG). He also consults with established and emerging semiconductor, MEMS and sensors companies.

The more than 53,000 people who flocked to SEMICON Korea last month were treated to a motherlode of insight into the future of the semiconductor industry as 470 companies exhibited innovative technologies in more than 2,000 booths. But the annual event’s most arresting numbers came in keynotes and other presentations pointing to the extraordinary industry growth that lies ahead.“It is no exaggeration to say that 90 percent of the world’s data has been generated in the last few years,” said Jim Feldhan, president of Semico Research. “This explosive growth of data is expected to continue. That's why server shipments will grow by 20.3 percent, or 30 million units, this year alone.”Feldhan said that the Internet of Things (IoT) will be a chief driver of semiconductor industry growth, with IoT expected to be applied in areas as varied as automotive, smart cities, edge computers, finance, architecture, agriculture and healthcare. For its part, artificial intelligence (AI) will start to exercise human-like judgment. Feldhan noted that in many instances in these fields, “it is more accurate to apply AI and vision systems than to rely on traditional decision-making.”Yoon Jong Lee, senior vice president of DB HiTek, predicted that the Internet, AI and 5G will drive market growth. “Looking back over the past 30 years, semiconductor market growth was powered by PCs, the Internet and cell phones, yet last year memory accounted for 35 percent of total semiconductor sales, more than double the figure in 2016,” he said. He predicted that, in 2019, the foundry sector will outstrip the semiconductor market in growth, noting that the average growth rate of the semiconductor industry is expected to be 4.1 percent, compared to 7.1 percent for the foundry market. Clark Tseng, director of SEMI, reported that the strong semiconductor growth in 2018 is unlikely to continue in 2019 due to the decline in memory pricing, as well as mobile and PC demand. “Demand for semiconductors is likely to decline in the first half as the industry is still digesting inventory and rebound in the second,” Tseng said. Semiconductor industry growth headwinds include decreases in high-end smartphone purchases, PC demand and demand for DRAMs for servers in data centers, Tseng said. Declines in economic growth and consumption in China and the U.S.-China trade war will also contribute to a slowdown. However, Tseng noted that, over the long term, technology innovation will continue and that the semiconductor industry’s prospects remain bright.One key innovation will be the elimination of AI’s reliance on Internet connections in the future. In his opening day keynote, Eunsoo Shim, senior vice president at Samsung Electronics, emphasized that AI technology that operates without the Internet in the future is essential. “We are developing 'on-device AI' technology that incorporates AI algorithms in products such as smartphones and autonomous vehicles,” he said. "When on-device AI technology is implemented, it reduces reliance on the Internet, battery consumption, and data latency.” Reducing latency will significantly improve device response time.Walden C. Rhines, CEO Emeritus of Mentor, a Siemens business, predicted that AI will fuel rapid memory growth. The memory semiconductor (DRAM, NAND flash) market is expected to see a temporary slowdown this year, with the market expected to rebound in 2020. Rhines said that memory could be seen as an early market with rapid future growth, citing memory market super-booms in 1995 and 2000.“Memory production has not decreased since 1995 or 2000,” he said. “Although memory prices will temporarily fall this year after significant market growth in 2017 to 2018, the market will continue to grow as memory production increases,” he said. Rhines added that “although memory prices will drop by about 10 percent this year, he believes prices will increase 6 percent next year.” He also predicted the steady growth of the non-memory semiconductor market as AI technology matures and China’s investment in fabless companies continues.Indeed, SEMICON Korea speakers made it clear that concerns about the growth of the semiconductor industry are expected to be short-lived. While overall growth is likely to slow in 2019, the industry is expected to rebound steadily – powered by the semiconductor industry paradigm shift led by AI, IOT, and autonomous driving – and reach a new high of nearly $541 billion in 2020.Jaegwan Shim is a marketing specialist at SEMI Korea.

ULVAC Technologies’ David Mount is working with The CIA. Is he the Jack Reacher of the MEMS and sensors industry, jetting around the world to secret meetings, you wonder? While David isn’t quite the super-spy that you might have imagined, he is doing some fascinating work on behalf of ULVAC Technologies, the world leader in vacuum technology.ULVAC has been collaborating with The Culinary Institute of America (CIA) on Menus of Change, “a ground-breaking initiative from The Culinary Institute of America and Harvard T.H. Chan School of Public Health that works to realize a long-term, practical vision integrating optimal nutrition and public health, environmental stewardship and restoration, and social responsibility concerns within the food service industry and the culinary profession.”ULVAC also partners with Menus of Change (MOC) University Research Collaborative, a group of elite universities and food-service executives working together to “accelerate efforts to move Americans toward healthier, more sustainable, plant-forward diets.” MEMS Sensors Industry Group’s Nishita Rao caught up with David, a featured speaker at MEMS Sensors Executive Congress on October 29-30, 2018, in Napa, Calif. to give MSEC attendees a preview of David’s talk. SEMI: How did ULVAC get involved with The CIA on Menus of Change?Mount: People in the MEMS sensors industry may not know that ULVAC started as an equipment supplier to the food industry. In 1952 ULVAC began supplying freeze-drying equipment – which relies on vacuum technology — to food companies tasked with providing long-lasting foods and beverages for the U.S. military under the Marshall Plan. Think instant soup, ramen noodles and Tang. While ULVAC’s technology portfolio is now very broad — spanning deposition equipment for the semiconductor industry, vacuum brazing for automotive, and even vacuum freeze-drying of vaccines that can be shipped dry but combined with distilled water for administration — the company has kept a hand in food technology. ULVAC’s vacuum cooling equipment rapidly and safely cools foods, dramatically increasing shelf life.The CIA is at the forefront of innovation in food technology, so we worked with them to test a vacuum cooling system that can also be used in the kitchen or in the field. In the Central Valley of California, for example, it can be 104ºF in the fields where lettuce is picked; our vacuum cooling system can cool that lettuce down to 47ºF in minutes.The CIA is also developing prepared foods for industrial settings such as university cafeterias and airlines. A prepared chicken dish, for example, might be cooked at 350ºF and then cooled to refrigeration temperatures. The potential problem is that bacteria can grow when you cool that food for storage. Some of The CIA test kitchens in California are using ULVAC’s vacuum cooling system to quickly and safely cool prepared foods.Vacuum-cooling is just one stage in food production, of course. Sensors are also widely used in food production and safety.SEMI: How do The CIA test kitchens use sensors?Mount: Nearly all aspects of production, processing and management in agricultural and food systems involve measurement of product and resource attributes. Sensors are a natural fit here as they can provide inspection capabilities that are accurate, fast and consistent. I plan to dive into some specific examples of the ways that The CIA and the MOC Research Collaborative are employing sensors to increase the safety of food and agricultural production.SEMI: What would you like MSEC attendees to take away from your presentation?Mount: I love knowing that the work that we do in this industry can benefit humanity. Applying our various technologies to food and agricultural production is just one way to do that. I encourage MSEC attendees to explore those markets that improve human quality of life – as well as the life and health of our planet and its other inhabitants. ULVAC Technologies senior advisor David Mount is a 35-year veteran of the vacuum and thin film equipment industry. He tried to retire from ULVAC but they would not let him go! David consults with ULVAC on strategic projects such as the company’s collaboration with the CIA.He will present Sensors in Food and Agriculture on Tuesday, October 30 at the MEMS Sensors Executive Congress.Register today to learn more about how sensors are transforming the food industry.Nishita Rao is a marketing manager at SEMI.