IoT

While Artificial Intelligence (AI) emerged in the 1950s, only in recent years have AI applications proliferated with the explosion of data and continuing improvements in Moore’s law that have driven rising processing speeds. Voice assistants, image analysis software, search engines, and speech and facial recognition systems were among the first applications to use AI. Today, adoption has spread to sectors such as agriculture, cybersecurity, healthcare, software development, e-government and the intelligent enterprise to generate jobs and help spur economic growth. The Edge AI Opportunity and the Microelectronics IndustryAI can be embedded in hardware devices such as advanced robots, autonomous cars, drones or Internet of Things (IoT) applications. Today, according to the EU’s digital strategy, data centres and other centralized computing facilities account for the vast majority – 80% – of AI data processing and analysis, with smart connected objects such as automobiles, home appliances and manufacturing robots that bring the compute function closer to the user representing 20%. The latter, known as Edge AI applications, are powered by edge-based machine learning chipsets, not the AI chipsets designed to run cloud-based machine learning algorithms.The EU’s white paper on AI published in February 2020 anticipates that the way data are stored and processed for AI applications will change significantly over the coming five years as edge computing applications proliferate. Most AI applications need to connect with devices that collect data and manage data flows. When the applications connect with cloud infrastructures to train large volumes of data for a machine learning model, the interface devices often require hardware support. Edge AI can minimize data transport by processing data directly from local devices to accelerate data analysis and decision-making and make data transport or accelerator hardware unnecessary, critical in reducing power consumption and enhancing data security for applications such as autonomous driving. Over the past 40 years, the ICT sector has been continuously increasing greenhouse gas (GHG) emissions despite efforts to shift to renewable energy. Cloud-based AI applications require an ICT infrastructure for high-performance computing and high-speed connectivity. According to MIT Technology Review, data centres’ AI workloads could account for a tenth of the world’s electricity usage by 2025. a mass update of cloud-based AI applications may significantly increase energy consumption, unlike with Edge AI. This is why the strategy for developing Edge AI is well-aligned with the EU’s Green Deal objectives. Europe aspires to play a leadership role in Edge AI to strengthen the sector’s competitiveness and protect the European digital sovereignty. Europe’s strong industrial competencies in embedded systems and microcontrollers will help the region promote development of European domestic AI solutions for emerging high-value IoT applications in industrial processes such as Industry 4.0, Connected and Automated driving (CSA), smart cities, climate action, healthcare, and national defence and security. With this strong strategic position in technology, Europe is well-positioned to invest to become the leader in the Edge AI global market.Preparing the Workforce for the Microelectronics IndustryTo design and manufacture leading Edge AI chipsets, European education providers and industry will need to work closely together to train the current and future workforces. Within the framework of the METIS project, a four-year project co-funded by the European Commission through the Erasmus+ programme, SEMI and imec deployed experts in the field to survey and interview focus groups. The survey identified the following key focus areas for workforce development: 1. True Capability of AI and Data Science With AI’s heavy dependence on data, the workforce of the future must be trained in areas of data science including data integrity to ensure quality, unbiased sourcing, collection and accurate analysis necessary to interpret huge volumes of data. Europe also needs to train the next generation of AI chip designers in data security and privacy – key challenges to the widespread deployment of Edge AI chips. 2. Climate Change, Sustainable Development Goals (SDGs) and Social Inclusion TrainingSince the industry must be able to develop Edge AI solutions to enable the digital transformation while limiting GHG emissions, microelectronics engineers need to be schooled in climate change and understand how their work contributes to meeting the United Nation’s Sustainable Development Goals (SDGs). Workplace diversity and social inclusion are also important target areas for education since Edge AI applications should serve various groups of people with different needs.3. EthicsChip industry workers must also be educated in ethical issues of AI related to the technology’s potential societal impact in the near future[1]. With AI applications capable of monitoring Internet searches based on users’ personal preferences and biases to deliver tailored advertising, news and other information, developers must recognize how the technology can influence thinking and behaviour of individuals and groups. This awareness can help developers strike a balance between supporting commercial interests and societal good so the microelectronics industry can ensure ethical implementation of AI. 4. Cross-disciplinary Skills Required for AIAI development requires a comprehensive, cross-disciplinary skill-set to be able to integrate the work of specialists from diverse educational, cultural and professional backgrounds critical to developing non-biased AI solutions. For example, in addition to technical expertise, microelectronics AI developers must be able to communicate clearly and work in close-knit teams with non-technical experts from business, law, medicine and the social sciences.What’s Next?The microelectronics industry has a tremendous opportunity to develop new chip-based solutions for AI architectures, and apply AI techniques to improve operational efficiencies of design and manufacturing. To seize this opportunity, the industry must work closely with education providers to groom the next generation of skilled workers. This tight collaboration is critical to designing and delivering specialised courses to college and university students as well as engineers now working in the chip sector. The stakes are high. By preparing workers to develop Edge AI chipsets, the microelectronics industry can help the world confront some of the greatest challenges it faces today.For more information, see SEMI Responds to European Commission White Paper on Artificial Intelligence.METIS is a Sector Skills Alliance project co-funded by the European Commission’s Erasmus+ Program and coordinated by SEMI. The four year project, launched in November 2019, will develop a Microelectronics Skills Strategy. Based on the strategy, the METIS project will design 43 training modules for 1,100 hours learning in four key areas of the microelectronics sector.We thank Patrick Blouet (STMicroelectronics) and Jeroen Geusens (imec) for their valuable contributions to this article.[1] Ethics of Artificial Intelligence and Robotics, Stanford Encyclopedia of PhilosophyDr. Yanying Li is senior manager of Collaborative Projects at SEMI Europe.Dr. Pushkar P. Apte is the strategic technology advisor for the Smart Data AI Initiative at SEMI

Even though microchips continue to get smarter, vital security gaps continue to be exposed through such hack attacks as Meltdown, Spectre, and in recent weeks, Plundervolt. Researchers continue to discover open doors in chip architectures for malicious players to steal increasingly sensitive data, hide the identity of counterfeits, or tamper with electronics systems most anywhere along the global microelectronics supply chain. Today, it’s impossible to have full visibility of the distributed chip making process – from design and fabrication to packaging, testing and delivery. That’s why our industry’s future hinges to a large degree on establishing a hardware root of trust throughout the silicon’s operational lifecycle. Trust but verify! It’s easy to say, but how do we do it?To gain insights, SEMI interviewed Dr. Mark Tehranipoor, currently the Intel Charles E. Young Preeminence Endowed Chair Professor in Cybersecurity at the University of Florida’s Electrical and Computer Engineering Department. A foremost authority on microelectronics security and trust, counterfeit electronics detection, and supply chain risk management, Dr. Tehranipoor will be a keynote speaker at the SEMICON Taiwan Security on Chip Summit, Friday, September 25, where a full program of industry leaders will address key security challenges and solutions involving IoT, systems on a chip (SoCs), integrated circuits, physical unclonable function (PUF) technology, future design, certifications, managed services, and more.For additional insights and to hear Dr. Tehranipoor’s full presentation, register for SEMICON Taiwan 2020, which SEMI is holding as a hybrid event with both a virtual format and an in-show program September 23-25.SEMI: What are the major uncertainties in providing the hardware root of trust within the cyber domain?Tehranipoor: One of the most critical issues we’re dealing with now is loss of control over the process of designing and fabricating integrated circuits and systems. This has happened along with globalization and the movement of supply chain operations overseas to lower costs of nearly all goods, including electronics products and semiconductors. As skill sets, talent, design and fabrication have all shifted offshore, concerns have also risen about security controls across the many different segments of the microelectronics supply chain.For example, when you think about the security of military, space, transportation, power grids, financial or other networks, it becomes a major concern if you cannot trust the underlying electronics system that runs them. New SoCs are also holding more sensitive data around encryption keys, biometrics, personal information or banking data. And as reports escalate about cybersecurity gaps at the electronics part level, it’s increasingly important to establish a hardware root of trust. Today, it’s not enough for a buyer to just call up the design house and verify the electronic ID of an asset. The ID might match, but the device could have been tampered with or replaced with a counterfeit somewhere along its end-to-end journey. Unlike software or networks where problems can be automatically identified, upgraded and fixed, verifying electronic hardware is a costly and time-consuming process, especially when they’re as complex as microchips. It can take months to deconstruct, reverse engineer, inspect, and authenticate a chip. By then, discovery of any security breaches is too late.When addressing the security of electronics systems, there are three important features to keep in mind. First, there’s confidentiality. The device shouldn’t leak information to an unauthorized user. Second, there’s integrity. Unauthorized users should not be able to manipulate an SoC’s sensitive data. The third feature is availability, which can be a result of Denial of Service (DoS) attacks. If the device is under attack and can’t access your online service or network, you must still have security measures for your electronics system to be available in a safe mode while you simultaneously identify the problem, recover from it, and return to normal functions.SEMI: What framework should be followed to establish greater trust and confidence across the entire microelectronics supply chain?Tehranipoor: In the United States, we recognize it may not be possible to bring all manufacturing, design, and delivery teams back to this country and have them certified by the U.S. Department of Defense. You could do some of it, but it would be very costly and complex to bring back all the design, fab, testing, and packaging operations involved with electronics systems and still have complete control.The most practical approach is to make sure we design electronic systems with security and trust in mind from the start. We need to provide security features up front throughout the extended supply chain – into the design flow, fab flow, and out into the field to make it easier and faster for anyone at any point to verify the authenticity of an electronic system as well as identify and mitigate a problem. Finally, we have to remember that we are all in this together – designers, developers, packaging facilities and fabs. We can’t just blame semiconductor manufacturers or any other single entity. As a result, we must be cooperative and collaborative by focusing on this issue as a consortium. Everyone in this ecosystem must come to the table, share best practices, establish standards, and initiate best practices for device to system authentication.SEMI: How can SEMI and the SEMI Electronic System Design (ESD) Alliance help the industry meet these challenges?Tehranipoor: It’s certainly of utmost importance for members of organizations like SEMI and its ESD Alliance committees to jointly develop and adhere to standards or guidelines that establish hardware root of trust across all participants in the global supply chain. At the same time, such alliances should make it a high priority to protect each company’s intellectual property (IP). Collectively, we need resolutions that allow us to develop unique IPs and more easily trace, identify, and verify the authenticity of electronics systems as they flow throughout the end-to-end electronic supply chain. Great efforts are under way and progress is being made. But it’s not enough. Clearly, more needs to be done to establish root of trust standards at the chip level.I can’t emphasize enough the importance of consortia like the SEMI ESD Alliance to create an environment where industry, government, and academia can come together, share best practices and even case studies on how they handled security vulnerabilities and breaches. We understand that not everyone wants to share their security problems, vulnerabilities, or attack surfaces, but learning from each other’s experiences can have a tremendous impact on industrywide progress. If you don’t know what you need to address, you won’t be able to address it when it happens.I also encourage organizations like SEMI to create standards or guidelines that reduce the complexity of microchip designs for security purposes. Realtors often say there are three things to consider in finding a home that will appreciate in value: Location, location, location. To build more secure electronics systems, my mantra is: Automation, automation, automation. Complexity is the enemy of security. By using automation to simplify security mechanisms and detect inconsistencies, it will be easier to find and fix security problems, not to mention lower costs at the same time. SEMI: What will an attendee take away from your talk at SEMICON Taiwan?Tehranipoor: I have a large team of researchers who day and night spot vulnerabilities by attacking and assessing data from different electronic systems set up in our labs. Attendees will see real-world examples and lab animations that show how electronics systems can be hacked most anywhere across the supply chain. They will also learn about step-by-step security solutions we have developed at the microchip level. We need to do a better job of protecting the security of our semiconductor assets and the electronic solutions or services they power. My call to action will be that we need to invest more in research and foster an environment of more open trust and cooperation. We can do this by bringing together different countries, companies, and organizations in the microelectronics ecosystem to overcome this major challenge.Dr. Mark Tehranipoor is currently the Intel Charles E. Young Preeminence Endowed Chair Professor in Cybersecurity at the ECE Department, University of Florida. He is currently serving as Director for Florida Institute for Cybersecurity Research (FICS), National Microelectronics Security Training Center (MEST), CYAN Center of Excellence, and ECI Transition Center. He also serves as Program Director of Cybersecurity for UF Herbert Wertheim College of Engineering. His current research interests include IoT security, hardware security and trust, and reliable circuit design.Samer Bahou is senior manager of corporate communications at SEMI.

The world’s most advanced manufacturing factories are leading the way in driving efficiency and sustainability.In advance of its 2020 meeting, the World Economic Forum welcomed Micron into its Global Lighthouse Network, a group of advanced manufacturers “that are showing leadership in applying the technologies of the Fourth Industrial Revolution to drive operational and environmental impact.”For years, Micron has been helping clients integrate artificial intelligence (AI), big data analytics and the industrial internet of things (IIoT) into their factories. And now Micron’s factory is one of the first facilities in Singapore, along with Infineon, to be recognized by the Global Lighthouse Network.In a recent interview with Channel News Asia, Manish Bhatia, executive VP of Global Operations, explained how Micron has been practicing what it preaches: “Our products enable new technology trends such as IoT, 5G, cloud computing and autonomous driving. Applying these technologies in our own manufacturing facilities demonstrates the enormous potential in driving business value. Industrial IoT and artificial intelligence are part of the biggest revolution since the advent of robotic manufacturing productivity 50 years ago.”For Micron, this journey started with the need to “keep pace with the technological advancement of our semiconductor processes,” Manish said. “We wanted to provide higher-capacity, higher-performance, lower-cost and lower-power chips.”This meant embarking on the same journey they guide clients through: “We started by focusing in 2014 on simple statistical analysis to improve our production processes,” Manish said. “Following that, we developed more complex deep learning and AI capabilities to draw insights from our data. Most recently, we introduced IoT sensors — like cameras and acoustic sensors — to gather even more data that allows us to further improve our production processes.”The Singapore factory plays a critical role in developing leading-edge NAND. Micron’s Singapore presence, composed of two wafer-fabrication facilities and one assembly and test facility, serves as the base for worldwide operations. With over 500,000 square feet of cleanroom space, the location is also a designated NAND Center of Excellence, driving the implementation of the company’s leading-edge 3D NAND production for use in mobile phones, solid-state drives, digital cameras and more. Micron employs approximately 8,000 people in Singapore.The World Economic Forum says the results of the Singapore transformation have been spectacular: Micron’s “semiconductor fabrication facility has integrated big data infrastructure and IIoT to implement artificial intelligence and data science solutions, raising product quality standards and doubling the speed at which new products are ramped.”Below are notable achievements that Micron was recognized for: Automation of production and maintenance produced a 4% tool availability improvement. The IIoT-enabled smart factory led to a 22% scrap and product downgrade reduction. Advanced analytics for process optimization with OEMs reduced time to ramp new products by 50%. Deep learning optical-defect detection created a 2% yield improvement. The integrated deviation management platform reduced time to resolve quality issues by 50%. Micron was a natural choice for the Global Lighthouse Network, an organization whose creation is timely. The World Economic Forum points out that “global production industry is lagging in its adoption of Fourth Industrial Revolution manufacturing technologies, with more than 70% of companies stuck in pilot-phases … [There is] a need for a neutral learning platform to showcase top-use cases, roadmaps and organizational approaches to adopting and scaling technologies from which other companies globally could benefit.”As part of the Global Lighthouse Network, Micron will be able to share knowledge and best practices with peers, support new partnerships and help other manufacturers deploy technology, adopt sustainable practices and transform their workforces. We can all build on this community of like-minded organizations, levering technology to improve efficiencies and promote sustainability.This recognition from the World Economic Forum is a win-win. We look forward to joining the club of lighthouse factories around the world and to helping propel the entire global manufacturing industry into the Fourth Industrial Revolution. At Micron, we are at the forefront of this transformation and welcome the opportunity to serve as a lighthouse.Koen De Backer is responsible for driving Micron’s smart manufacturing initiatives and digital operations including capabilities with IoT, artificial intelligence, advanced analytics, cognitive computing and machine learning to enhance Micron’s business, global operations and product development. Prior to joining Micron, Mr. De Backer led large-scale operations projects for more than a decade to help clients reduce inefficiencies and achieve excellence in manufacturing, procurement, supply chain and support functions.Most recently, De Backer was a partner at McKinsey Company, where he steered the semiconductor consulting practice in Southeast Asia and was one of the firm’s leading experts on applying artificial intelligence and automation techniques across operations and support functions such as finance, human resources and procurement. Additionally, Mr. De Backer consulted with high-tech global clients while working at Deloitte Consulting, Altran Europe and CSC. Mr. De Backer holds a master’s degree in business administration from INSEAD and a master’s degrees in both industrial management and electromechanical engineering from Katholieke Universiteit Leuven.De Backer is also chairman of the SEMI Southeast Asia Smart Manufacturing Chapter. For information on participating in the chapter, contact Shannen Koh at [email protected].

Thanks to developments in science and technology, artificial intelligence (AI), cloud computing, big data and other technologies have been used to establish smart healthcare systems that helps societies respond more effectively to disease outbreaks. The spread of novel coronavirus starting in late 2019 has revealed how not only traditional medicine but also Smart MedTech applications can be instrumental on the anti-epidemic front lines.To give updates on the development of Smart MedTech and how it shines during the fight against COVID-19, SEMI invited Dr. Pei-Yuan Lee, Honorary Superintendent of Show Chwan Memorial Hospital, to share with MSIG (MEMS Sensors Industry Group) and Flex-Tech members how the international community and Taiwan are bringing their best in Smart MedTech to the table and how their collective efforts are helping tackle COVID-19 challenges.Taiwan’s COVID-19 rapid screening reagents and antibody testing help curb coronavirus transmissions Taiwan’s medical community has demonstrated its prowess in responding to the COVID-19 outbreak. Using its nucleic acid extraction reagent, Taiwan Advanced Nanotech Inc. tested 128 specimens from passengers aboard the SuperStar Aquarius cruise ship in only eight hours in early February. Taiwan’s leading research institute Academia Sinica successfully synthesized the first group of monoclonal antibodies capable of recognizing the new coronavirus protein on March 8, enabling testing to be completed in 15 minutes. The College of Medicine of National Taiwan University announced on March 27 that its 30-second screening device had helped identify asymptomatic carriers. The devices detect COVID-19 in people with no symptoms if they have pulmonary infiltration and edema. It took only 14 days for Academia Sinica to successfully synthesized the first group of monoclonal antibodies capable of recognizing the new coronavirus protein. On April 22, three biomedical companies in Taiwan launched a COVID-19 test that produces results from samples of patient mucus in less than 10 minutes to greatly enhance testing speed. Once the test method is approved by the Taiwan government, it will take Taiwan’s medical strategy against COVID-19 to the next level.Artificial Intelligence: the key to upgrading traditional healthcare practicesAI is a key enabler of the transition from traditional medical practice to Smart MedTech. To help fight the COVID-19 outbreak, a National Cheng Kung University medical team developed a 30-minute coronavirus testing procedure that uses AI to read pulmonary X-ray images and automate medical records. Taiwan AI Labs leveraged AI to simulate how drug molecules combine with viruses to reduce research time by three to four years. AI ​​diagnostic technology from the Alibaba DAMO Academy (Academy for Discovery, Adventure, Momentum and Outlook) and Alibaba Cloud interprets CT images of COVID-19 patients with 96 percent accuracy in 20 seconds. AI-powered algorithms improve diagnostic test accuracy, allowing clinicians to quickly analyze scans of pulmonary lesions and quantify the severity of lung damage.Startups have also joined the fight against COVID-19. Taiwan's Internet of Things (IoT) startup iWEECARE invented the world's smallest smart thermometer patch. Heroic-Faith Medical Science launched a device that uses IoT and AI to monitor lung sounds. With Smart MedTech expected to be fertile ground for future venture investments, enterprises must find their niches in establishing new technologies in a much more systemic way. Taiwan startup Health-Faith Medical Science developed a respiratory diagnostics device that uses IoT and AI technology to monitor chest sounds in real time. Anti-epidemic technology to help fulfill smart medtech vision Many AI and big data technologies previously deployed in hospitals and healthcare systems are helping regions around the world speed their pandemic response. The United States and China have started to develop facial mask recognition systems powered by AI, while a team in the Department of Bioinformatics and Medical Engineering at Asia University has devised a facial recognition system combining IoT and AI technology with infrared thermal imaging cameras. At Johns Hopkins University, the Center for Systems Science and Engineering is using AI to create big data models that track global cases, people and traffic flow, and other variables for real-time data analysis that enables epidemiologists to more accurately predict COVID-19 transmission paths. Graphen, Inc., a New York-based provider of next-generation AI platforms, launched the world's first AI COVID-19 genetic evolutionary path analysis systems to gauge the virus’s transmission route and accelerate pandemic response. Both the United States and China are also using robots and drones to improve epidemic research and patient treatment. For the first confirmed case in the United States, robots were used to assist with medical care. In China, robots facilitate deliveries of disinfectants to makeshift hospitals built to expand the nation’s capacity to treat COVID-19 patients. While Taiwan’s robots are traditionally used for hospitality, transportation and disinfection purposes, future robotics research and development will focus more on medical applications that shift more work from medical staff to technology. With abundant technological resources and expertise, Taiwan can join hands with the rest of the world to combat the COVID-19 pandemic. Emerging technologies are pointing the way toward a new paradigm for healthcare community. Biotech, artificial intelligence, and robotics have given rise to new applications that increase virus screening accuracy and efficiency. This growing wave of technological defenses against the pandemic will become a long-term force for stability and strength in healthcare systems across the world.To get involved in SEMI Taiwan Smart MedTech Community, please contact Helen Chen, Outreach Manager, at [email protected] Huang and Winnie Chang are marketing and public relations specialists at SEMI Taiwan.

The seemingly simple act of commanding consumer devices by voice is a choice that nearly 118 million Americans now make every day, according to a recent report from eMarketer, the digital marketing research firm.While the voice interface is convenient for users, its implementation comes at the potential loss of individual privacy. The reason? Always-on, always-connected voice-first devices such as Amazon Alexa and Google Home require a wall plug and an internet connection to powerful cloud processors, making it possible for cloud companies — however benignly — to collect data on personal habits, location and conversation that were never intended for sharing. Move processing to the edgeTo address concerns over user privacy, device designers are attempting to do more of the audio processing within the consumer device, rather than sending users’ voices into the cloud. Moving more processing to the edge is a trend across the Internet of Things (IoT) industry, and not just for voice data but for other types of sensitive or proprietary data as well.Yet designers have realized limited success because the conventional approach to always-listening edge processing is notoriously inefficient: It digitizes and processes 100% of incoming sound data even though up to 90% of the data is irrelevant noise. This digitize-first approach wastes vast amounts of system power digitizing and analyzing the audio signal as it searches for a wake word when there isn’t even speech present, making it impractical for use in small, battery-operated devices.Workarounds don’t workTackling this power issue is critical to keeping private data secure. Unfortunately, it’s also exceptionally difficult. Design engineers have tried workarounds to decrease power consumption in an always-listening system, including duty cycling and reducing the power of each individual component in the audio signal chain that handles the data. The reality is that these kinds of approaches don’t address the root cause of the problem: too much data.To truly tackle the problem, we need to change our approach to a system solution, not a component solution. By moving to a more efficient edge architecture that intelligently minimizes the amount of data that moves through the system, we can focus the system’s energy resources on analyzing voice and not on searching for a wake word in irrelevant noise. Analyze, THEN digitize It’s time to move away from the digitize-first approach that has dominated voice wake-up device architecture since the invention of voice-first applications.Inspired by the way the human brain efficiently filters incoming information, differentiating, for example, a dog bark from a baby’s cry, an ultra-low-power analog machine learning technology is changing this paradigm. For the first time, device designers can use low-power analog machine learning to detect which data are important for further processing and analysis prior to data digitization.Leveraging an analyze-first architecture, a new analog neuromorphic semiconductor platform allows the higher-power-processing components in the system to stay asleep until voice has actually been detected, and only then does it wake them to listen for a possible wake word.Delivering a post-microphone audio chain that draws as little as 25µA of current when always-listening and collecting preroll data, this analyze-first architecture allows designers to extend battery lifetime significantly. That’s the difference between smart earbuds that run for weeks instead of hours or a battery-powered smart speaker that runs for months instead of weeks.More importantly, it’s the difference between the current always-listening devices that indiscriminately record and send all sound data to the cloud, and one that has the localized intelligence to select and send only the relevant data, reducing the user’s vulnerability to the loss of private data.Balance convenience with privacyThe trade-off between making our lives easier and keeping our personal information private is a choice that we are asked to make throughout our day in a hundred different ways. Bringing more audio processing capability to the mobile device without draining the battery is the first step toward delivering more secure voice-first solutions. But to succeed in this effort, we must shift to a bio-inspired architecture that determines which data are important and requires further processing at the earliest point in the signal chain. Once we move to the analyze-first approach, only a small fraction of the tens of zettabytes of data collected by the forthcoming generation of always-on IoT devices will require further processing in the device and in the cloud.A better balance between cloud and edge processing is a better balance between convenience and privacy, and that’s a win for everyone.About the AuthorTom Doyle is CEO and founder of Aspinity. He brings over 30 years of experience in operational excellence and executive leadership in analog and mixed-signal semiconductor technology to Aspinity. Prior to Aspinity, Tom was group director of Cadence Design Systems’ analog and mixed-signal IC business unit, where he managed the deployment of the company’s technology to the world’s foremost semiconductor companies. Previously, Tom was founder and president of the analog/mixed-signal software firm, Paragon IC solutions, where he was responsible for all operational facets of the company including sales and marketing, global partners/distributors, and engineering teams in the US and Asia. Tom holds a B.S. in Electrical Engineering from West Virginia University and an MBA from California State University, Long Beach. For more information, please visit https://www.aspinity.com/Technology.Aspinity is a member of MEMS Sensors Industry Group (MSIG), a SEMI technology community, that enables the MEMS and sensor industry to address common challenges, innovate and accelerate business results.

In the two months since the COVID-19 outbreak in January, the Chinese economy has shifted from shock to ongoing recovery under the guidance of the Chinese government. China has worked tirelessly to restore production at its chip manufacturing facilities, a core strategic industry in the region, and the effort is paying off. Operations at several fabs and OSATs – the domestic semiconductor industry’s chief growth engines – have begun to stabilize.As of mid-March, SMIC had restored its manufacturing lines to over 90% of production capacity and expects to be operating at full bore in the next few weeks, while the company’s R D line has returned to full operation. Huahong Grace reestablished normal supplies of various equipment parts and production raw materials. At Huahong Fab2, 12 new pieces of equipment went online to help increase production capacity, and production at Huahong Fab1 and Huahong Fab3 is now stable. JCET said the company's overall return rate has exceeded 90%. Meanwhile, IDM maker Silan Microelectronics' 6-inch and 8-inch lines maintained 90% production.Production lines at Huahong Group, SMIC, CanSemi, GTA Semiconductor, Samsung (Xi'an) and other mainland China chip manufacturers have been generally operating at normal capacity since the Spring Festival. Lines at YMTC, Tianma, CSOT, and BOE, all in the Coronavirus epicenter of Wuhan, have also returned to normal operations. China’s chip industry is finding its footing, and an impressive host of semiconductor companies are gearing up to participate at SEMICON China 2020, rescheduled to June 27-29. The list includes the major domestic wafer foundries such as Huahong, the major packaging and testing companies such as JCET, TFME, Huatian, and large domestic and foreign equipment companies, among them TEL, ASMPT, DISCO, ULVAC, VAT, ASML, KLA, NAURA, AMEC, Anji, CETC, Sinyang, SMEE, CAS, CANON and SPIROX.DigiTimes, a daily newspaper covering the semiconductor, electronics, computer and communications industries in Asia, interviewed SEMI China President Lung Chu in mid-March about what’s ahead for China’s semiconductor industry. Following is an English translation of the interview. DigiTimes InterviewAs China continues to ramp back up to normal activity, SEMI China is making every effort to hold SEMICON China 2020, a leading international semiconductor industry platform for promoting growth and innovation in China's semiconductor industry supply chain. SEMI China president Chu emphasized that the strong support of SEMICON China 2020 exhibitors and the Chinese government made rescheduling the event to June possible.Chu, a semiconductor industry veteran who has experienced numerous economic and industry upheavals over his career including the SARS shock in 2003, said current global economic uncertainty stems from two black swans – the global COVID-19 pandemic and how long it will take to contain it, and the sharp drop in oil prices triggered by the recent geopolitical dispute between Russia and Saudi Arabia. In China, the government responded with strict containment actions and promoted public awareness of self-isolation, resulting in effective domestic containment as of mid-March. As a major oil consumer, China sees the lower prices as relatively favorable to its economy. Those dynamics should allow China to recover sooner than many other regions, and it could emerge even stronger once the pandemic is contained, despite the current slump in global semiconductor demand, Chu said. Once the epidemic has passed, China is in a position of "turning crisis into opportunity," and the semiconductor industry will recover from the trough, he said. Companies in semiconductor supply-chain sectors face various challenges in restoring normal operations. IC design companies experienced relatively low impact since employees can work from home and most companies are located in major cities in China, where epidemic prevention control is strict. For most chip manufacturers, production has not stopped but is hampered by manpower shortages from restrictions on employees returning to work. IC packaging and testing companies are suffering bigger impacts because of the more labor-intensive nature of their operations. However, all companies in the supply chain will be affected by the decline in demand for electronic products and ICs in 2020. As the COVID-19 threat recedes in China, the region remains unwavering in its commitment to semiconductors as a strategic industry with its continuing efforts to evolve sustainable and reliable localized supply chains, Chu said. Investments in “new Infrastructure” for 5G, the Internet of Things (IoT), data centers, as well as public health services should help drive semiconductor demand for smart applications and devices associated with the new infrastructures as are all powered by ICs, benefiting companies in the global supply chain. The COVID-19 outbreak triggered a slowdown in new factory construction after the Chinese government implemented restrictions on the flow of people resulting in a worker shortage. SEMI has revised downward its forecast of wafer equipment spending in China to just a 3% increase this year.Market analysts revised downward forecasts for 2020 annual global semiconductor revenue growth from 7-10% to 0-5%, while some expect negative growth. The recent COVID-19 outbreaks in Europe, the United States and other regions have created more uncertainty. Declining end-user demand for electronics will drive down spending on upstream equipment for both memory and logic IC device makers. For Chu and his SEMI China staff, the postponement of SEMICON China 2020 has been a “major challenge,” he said. “It is a huge project to communicate and coordinate with the government and to reconfirm with exhibitors and industry leaders.”As a leading industry platform, SEMICON China attracts a large number of global customers and suppliers each year. The major China domestic suppliers, leading foundries and OSATs have confirmed their attendance in SEMICON China 2020. Most key foreign suppliers are planning to staff the event with local teams in case some executives are unable to enter China by June due to travel restrictions if the COVID-19 virus has not been brought under control in the United States, Europe and other regions. To assure the success of the concurrent Forums, SEMI has prepared multiple contingency plans, including live broadcast, video and slide presentations. SEMI will also hold the grand opening session at a larger venue than last year’s event to accommodate more attendees with more sitting distance apart. SEMI will follow government guidelines to implement appropriate public health and safety measures during SEMICON China. "Ensuring the welfare of all exhibitors and guests and providing a safe exhibition environment is SEMI’s top priority," Chu said.Cherry Sun is a marketing manager at SEMI China.

VTT Technical Research Centre of Finland Ltd (VTT) has its sights set high. As a leading global research and development firm , VTT is out to produce bio-interfacing and biodegradable flexible hybrid electronics (FHE) devices that help tackle some of the world’s greatest challenges including environmental degradation and food scarcity.SEMI’s Maria Vetrano interviewed Antti Vasara, president and CEO of VTT Technical Research Centre of Finland, to preview his February 25 keynote, Beyond Flexible Hybrid Electronics: Biodegradable Electronics and Interfacing Bio+Electronics, at FLEX|MEMS Sensors Technical Congress (MSTC) 2020, February 24-27 at the DoubleTree by Hilton in San Jose, California. Join us at FLEX|MSTC to meet Antti and other industry influencers driving innovation in flexible hybrid electronics (FHE) and MEMS sensors. Register now to connect with him at FLEX|MSTC or visit him on LinkedIn.SEMI: What is body-interfacing electronics and what is your vision for bio-interfacing and biodegradable electronics?Vasara: Body-interfacing electronics have existed for decades. Developed in the 1970s, the wireless heart rate monitor is a good example. While continuous heart monitoring with a compact, inexpensive wearable device is widely accessible technology, other bodily parameters, such as cholesterol levels or biomarkers, are diagnosed every time we see a doctor. Establishing a baseline using multiple measurements — before symptoms develop is actually much more effective.That’s where bio-interfacing comes in. Bio-interfacing devices will continuously measure and analyze complex biogenic substances such as sweat, breath, blood and urine. A smart patch for continuous sweat monitoring, for example, would overcome several challenges: supporting electronics functionality in liquid environments, managing the transport of harvested samples to and from the sensor, managing potential contamination, and disposing of samples after measurement.While FHE in principle delivers the right building blocks and is an ideal form factor for a wearable sweat analytics patch, flexible circuits are not ready for out-of-the box interaction with biological matrices. Hence, our mission at VTT is to anticipate and develop the upscaling process know-how required for FHE devices that either interface with biological systems — or that must themselves biodegrade.We’re also focusing on biodegradable electronics because environmentally conscious end-users and manufacturing companies want biodegradable versions of energy-autonomous, label- or sticker-like Internet of Things (IoT) sensors. Typically used for packaging, logistics, environmental monitoring and medical diagnostics applications, these sensors — which have a lifetime of a few days, weeks or months — have become very popular. Unless they are biodegradable, however, they just add to landfill.SEMI: What approaches is VTT using to develop bio-interfacing and biodegradable electronics?Vasara: In our Business Finland-funded ECOtronics project, we are working with our partners to create recyclable and compostable electronics and optics that use renewable resources. For example, devices developed using substrate materials like paper, cardboard or VTT’s in-house-developed nanocellulose films and biopolymer films for environmental monitoring or skin patches can be easily recycled or even biodegrade naturally. Where possible, we use roll-to-roll printing to generate the device circuitry, and on a component level, we have optimized our assembly process towards bare-die component bonding to reduce the overall footprint of non-biodegradable waste per device.SEMI: What use cases do you find most promising and why?Vasara: A prominent example of a single-use test that generates a large amount of waste is the digital pregnancy test. When breaking it down into components, you will find a rigid circuit board with microprocessor, a couple of coin cell batteries, a liquid crystal display, a LED light source and photodiode, and a large chunk of plastic packaging around it. The materials and battery capacity of such a device would be sufficient to run hundreds of pregnancy tests – actually technical overkill.By using printed circuits on biodegradable substrates, bare-die assembled components (ASIC, LED light sources, photo diodes, thin film batteries as power sources) and device packaging composed of biodegradable plastics, we can completely redefine the environmental footprint of single-use tests. We are currently developing a toolbox for our customers to turn their existing conventional test into an ecotronic form factor.Another exciting use case is a sweat sensor that we developed collaboratively with Ali Javey, Ph.D., professor of Electrical Engineering and Computer Sciences, UC Berkeley, and the co-director of Berkeley Sensor and Actuator Center (BSAC). Together with his team, we created a wearable electrochemical sensor for continuous sweat analysis during exercise. With the UC Berkeley group providing the chemistry to monitor N+, K+ ion and hydration levels in sweat over the duration of several hours, VTT delivered the underlying sensor platform, featuring the printed sensor electrodes and sweat harvesting microfluidic channels for fluid management and transport. It’s exciting to see what we can achieve by combining techniques from different disciplines, in this case electrochemistry, printing, packaging and microelectronics.SEMI: How can industry enable the development/manufacture of flexible FHE devices? Where does VTT fit into the ecosystem?Vasara: As many FHE devices target large-volume markets, scalability of manufacturing is key: How can I get from one device (= working prototype) to a handful of devices (= feasibility study), to thousands (= pilot manufacturing), to a million (= mass manufacturing) without compromising the quality of the system’s performance and reliability?Access to upscaling infrastructure is essential for the development of novel FHE devices and methods, but infrastructure is expensive. That’s where our establishment of a roll-to-roll pilot printing line to bridge the gap between laboratory R D and mass manufacturing has proved invaluable. We can provide a unique worldwide upscaling infrastructure for advanced FHE devices, with a strong focus on large-area roll-to-roll processes and hybrid assembly. This service removes our customers’ burden of high infrastructure investment in early development stages and it allows us to guide customers along their development path, from prototype to mass production.Watch our video: VTT pilot manufacturing for diagnostics and wearablesSEMI: Is there anything else that device manufacturers need to know in order to succeed?Vasara: In my eyes, the success of FHE devices eventually depends on several factors: It requires a high degree of automation, well-optimized processes, reliable supply chains, and perhaps most importantly, clear standards and rules for designers to guarantee flawless interoperability of all the different elements on a flexible and hybrid circuit. Let us not forget – we are trying to marry electronics with printing, biology, packaging, microfluidics, injection molding and other fields of expertise.We recently finalized the compilation of a set of design rules for publication in our state-of-the-art overview of printed and hybrid electronics manufacturing methods. You can download the overview, PrintoCent Handbook, for free.SEMI: What would you like FLEX|MSTC attendees to take away from your presentation?Vasara: The latest technologies and innovations in microelectronics, MEMS, printing, materials, and biosensors provide us a toolbox for true innovation in the FHE space. Now we need cross-disciplinary thinking and daring steps to combine different manufacturing methods and skill-sets. The ideal cross-disciplinary team might include: The printing engineer who knows how to design contact pads for a bare-die IC assembly The biologist who knows about the thermal and mechanical stress in a printing environment to design processes for bio-functionalization of surfaces The electronics engineer who knows how to optimize a circuit powered with an enzymatic biofuel cell The number of sensors deployed on (or inside) our body, in our drinking water, in our cars, on our fields, in our pets, and everyday products will surely grow. Let us make sure they leave the smallest environmental footprint possible.Antti Vasara, Ph.D. has been the president and CEO of VTT Ltd since 2015. VTT is a visionary research, development and innovation partner with over 2000 people and a turnover exceeding 250M EURO. Vasara is president of EARTO (European Association of Research and Technology Organisations) and is chairman of the board of Palta (Finnish Service Sector Employers). In addition, he is a non-executive director of Elisa Oyj (largest communications operator in Finland) and a board member at EK (Finnish Confederation of Industries).He has served on several high-profile groups on industrial and innovation policy of the European Commission, in addition to several groups in Finland on artificial intelligence and research policy. Previously, Vasara spent close to 25 years in private industry, working at Nokia, Tieto, SmartTrust and McKinsey Company. Earlier in his career, he was a researcher in optical communications with 20+ peer-reviewed articles and one international patent. Vasara holds a Doctor of Science (Technology) degree from Aalto University in Finland.For more information about VTT’s work in bio-interfacing and biodegradable FHE devices, visit VTT Research. FLEX|MSTC is organized MEMS Sensors Industry Group (MSIG) and FlexTech, SEMI technology communities focused on the growth of MEMS sensors and the flexible electronics supply chain, respectively.Maria Vetrano is a public relations consultant at SEMI.

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.

The microelectronics industry is entering the era of Cloud Engineering Simulation to slash the costs and risks of new technology development and speed time-to-market in spaces like semiconductors, MEMS sensors, RF front ends, biomedical and driverless cars. In the run-up to SEMICON Europa, 12-15 November, 2019, in Munich, Germany, SEMI spoke with Ian Campbell, CEO of OnScale, about the new paradigm of Cloud Engineering Simulation. Campbell shared his views ahead of the SMART Design Forum, 14 November, 2019, 14:30 to 17:00, in Hall B1, TechARENA 1 at SEMICON Europa. Registration is open. Join the forum to meet experts from OnScale and other key industry influencers. Attendance is free of charge for all SEMICON Europa visitors.SEMI: How did your adventure with OnScale start?Campbell: I’m an engineer. When I was still in high school, I took a night class at Nashville Tech to learn AutoCAD R14, and I’ve been designing and engineering things ever since. I was introduced to Desktop Simulation in my bachelors of mechanical engineering program and used many types of simulation tools for massive design studies at the Aerospace Systems Design Lab at Georgia Tech. I’m a simulation junkie.I started my first Silicon Valley high-tech company, NextInput, in 2012 with Dr. Ryan Diestelhorst (now VP of Strategy at OnScale), to commercialize new ForceTouch and 3D Touch technologies based on our patented MEMS force sensors. At NextInput, we bought hundreds of thousands of dollars of engineering software, but were always frustrated by slow, inaccurate engineering simulation results. We dreamed about running massive simulations on Cloud Supercomputers and creating true Digital Prototypes that could replace costly, time-consuming, and risky physical prototypes.When I got the chance to join the team that became OnScale in 2017, I jumped at the opportunity. At OnScale, we took engineering simulation solvers that had been developed for the U.S. military to run on U.S. Department of Defense and DARPA supercomputers and built a cloud supercomputer platform on Amazon Web Services to run the solvers. The net-net is the world’s first on-demand, infinitely scalable Cloud Engineering Simulation platform. Now, we routinely run massive multi-billion degree of freedom simulations for Fortune 100 companies, including many from the semiconductor and MEMS industries. Since our business model is to charge per core-hour for simulations, the incredible capability we built is cost-effective and available to small startups as well. SEMI: How is the semiconductor design ecosystem evolving? How is Cloud Engineering Simulation applied to semiconductor and design industries?Campbell: The entire industry is experiencing a massive acceleration in product launch cycles and increased competition. New markets like IoT and 5G are reducing semi/MEMS product cycles from years to months. That, in turn, puts enormous pressure on semiconductor and MEMS designers. Missing a key product introduction like a flagship smartphone launch can literally make or break a company.A reliance on traditional engineering methods – schematic capture and layout of a chip, taping out (physically prototyping the chip), performing engineering validation on an e-bench, qualifying the chip (or not qualifying it and going back to the drawing board), and finally launching mass production – is no longer sustainable from a competitive perspective.Instead, market-leading firms are turning to Cloud Engineering Simulation and Digital Prototypes to explore massive design spaces, find optimum designs that beat the competition in every KPI (size, power, performance), and digitally qualify designs before ever cutting silicon, ensuring that designs are robust over their intended operating environments and performance envelopes. Large thermal analysis of a chip on a circuit board executed quickly on the OnScale Cloud Simulation Platform SEMI: Can you give us an example? Campbell: A great example is thermal analysis. Thermal effects have always had huge impacts on MEMS device performance and, more recently, they are beginning to impact performance of next-gen semiconductors, especially GaN power electronics for electric vehicles (EVs).Conducting a full system-level thermal analysis of something like an EV power management system – a power IC in a package, on a board, in an enclosure, under various loading conditions – has been a challenge from a simulation complexity perspective (degrees of freedom) and from a parametric sweep perspective (running hundreds or thousands of simulations to optimize chip placement, routing, etc.). To run these sets of simulations using legacy desktop simulation would take weeks, perhaps even a month or more. To run these massive simulations in parallel on cloud supercomputers using OnScale takes days or even hours.Our customers routinely run very large simulation studies on OnScale Cloud for thermal simulations, RF filter simulations, MEMS simulations, packaging simulations (what we call Digital Qualification), and many more use cases.SEMI: What’s one of your strategic objectives for 2020? Campbell: For 2020, we’re doubling down on MEMS and semi simulation capabilities. We will be launching additional solver capabilities like EM that will be critical in our strategic markets like 5G. We will also be launching a Cloud API so that engineers can integrate OnScale directly into their existing engineering workflows (e.g. MATLAB or EDA/CAD tools) with just a few Python commands.SEMI: Can you share one prediction for the future of semiconductor design solutions? share?Campbell: I think we will continue to see MEMS and semi designers push the envelope and bring smaller, more performant, more cost-effective solutions to market. I’d like to see more highly cost-effective flexible semi/MEMS designs come to market to enable next-gen IoT and IIoT applications. I’d also like to see more biomedical applications – biomems, microfluidics, and labs on a chip for all sorts of life-enhancing applications.SEMI: What are your expectations regarding the SMART Design Forum at SEMICON Europa 2019 in Munich? Campbell: I’m looking forward to getting back to my roots in MEMS/semi design and chatting with other designers about the future of engineering and the future of semi! Ian Campbell is a twice venture-backed Silicon Valley CEO and expert in MEMS sensors, semiconductor technology, and engineering software. Most recently, Ian co-founded OnScale, a Cloud Engineering Simulation startup backed by Intel Capital and Google’s Gradient Ventures. OnScale is revolutionizing engineering by combining world-class multiphysics solvers with Cloud supercomputers, machine learning, and artificial intelligence. Prior to co-founding OnScale, Campbell served as founder and CEO of NextInput, where he led the startup through multiple rounds of funding – totaling $12 million and an additional $4 million in research contracts with government and industry partners – and built a world-class team of engineers and scientists who developed 3D Touch and ForceTouch technologies for smartphones, wearables, industrial, and automotive interface applications. He also secured the first major smartphone OEM design wins in Asia. Campbell earned his B.S. in mechanical engineering from Middle Tennessee State University, and his MSAE in aerospace engineering and MBA from Georgia Institute of Technology.Serena Brischetto is senior manager, marketing and communications, at SEMI Europe.

Technology advancements seem to be coming at us fast and furiously. Every time you turn around, another company is introducing a breakthrough product with claims of far-reaching implications on how we live and work. But how often do consumers really experience disruptive innovation, like the kind that smartphones and cloud computing have had on our lives? Instead of astounding people, many new products that hit the market today are merely upgraded versions of their predecessor – perhaps offering smaller footprints with faster processors, more attractive packaging, or add-on features. These upgrades tend to underwhelm customers, offering no compelling reason to justify their accompanying price hikes.What consumers want is disruptive technology that truly enhances their lives, whether at work, at home or at play. And that’s exactly what product manufacturers want to deliver. So what’s holding them back?The Limits of Traditional BatteriesThe challenge doesn’t lie in envisioning exciting new offerings. Vendors are great at that. Rather, when it comes to consumer-focused, electronics-based products, the culprit is often conventional, rigid and thick batteries that limit what can be designed around them.But it doesn’t have to be this way.Advances in flexible and thin batteries can spark a whole new level of product differentiation. Even though such batteries have been available now for a few years, they are still a foreign concept to many product designers accustomed to conventional off-the-shelf energy storage that is fixed in rigidity and shape. It’s hard for some people to believe that batteries can fold and flex while maintaining their performance and safety. As a result, they design products around rigid battery parameters. The Promise of FlexibilityFortunately, flexible battery technology is available today, even for high-volume production.While the allure of flexible battery technology is strong, we find ourselves having to reassure manufacturers that flexible batteries are every bit as dependable as their rigid progenitors. Our testing shows that performance-integrity in flexible batteries is strong. They can be flexed, bent and even rolled in any direction without deteriorating performance. For instance, we tested a flexible battery by bending it 10,000 times to prove that it has essentially the same capacity as a non-bent battery. This flexibility gives designers and engineers a new level of freedom in hardware design: Manufacturers can now place batteries in spaces not possible or practical before. Take smartwatches, for instance. Instead of locating batteries in only the head case, engineers can embed a flexible, thin battery in the strap band to increase accessible energy or lengthen battery life. As market demand grows for wearables and hearables, smart apparel and other personal battery-powered products, consumers want more natural-feeling experiences. Unlike fixed off-the-shelf energy solutions offered in a limited range of form factors and capacities, flexible batteries can support customization by size, thickness and capacity, enabling development of products that are smaller, lighter and more comfortable.Rigid batteries are problematic on a whole other level, and that’s safety. Electrolyte advancements ensure flexible batteries are safer. The latest gel-polymer electrolyte is safer than liquid electrolyte because it does not contain liquid that would leak if the battery is pierced or penetrated – yet it still delivers the same high level of ionic conductivity. This is a great advantage for manufacturers of wearables in medical devices, sports equipment and fabrics, industrial applications, and consumer electronics. Knowing that their devices contain safer components not only brings peace of mind to manufacturers and consumers but also increases both adoption and usage rates. Staying competitive in any technology-driven market requires a steady stream of innovation. To rise above the pack, companies must fearlessly embrace advancements that will differentiate them in the marketplace. Your choice of battery is critical to your hardware design – especially if consumers will be in direct contact with the battery. The performance and enhanced safety inherent in next-generation flexible batteries can free you to create disruptive products that deliver a compelling user experience. To learn more about flexible batteries, visit Jenax.EJ Shin delivered an engaging presentation at 2019FLEX Japan (May 22-23, 2019, in Shinagawa, Tokyo), where she discussed Jenax’s flexible and customizable rechargeable battery, a technology that allows batteries to integrate seamlessly into a new generation of medical devices.FLEX Japan is a hosted by FlexTech and MEMS Sensors Industry Group, SEMI technology communities.EJ Shin is Global Director at Jenax Inc., a company that pioneered the next-generation flexible, thin battery that can be bent and rolled in any direction. She has been with Jenax since the company initiated its battery development. EJ helps device and wearable companies leverage Jenax’s customized battery solution for their innovative products. Earlier, she held communications consulting positions at Fleishman Hillard and G20 Summit in Korea. EJ holds an MBA from Yonsei University, South Korea, and a B.A. in International Relations from Tufts University, U.S.