MEMS inertial sensors

Inertial sensors have continued to underpin the success of wearables in increasingly important ways. Propelled by evolutionary advancements in inertial sensors, wearables have strayed from their humble beginnings in simple activity and wellness, which defined the user experience over the past decade. What started with the simple act of telling people their daily step count has morphed to provide deeper insights into swim stroke and run cadence, all the way to mapping out a person’s off-piste ski route. Layered on top of this foundation of inertial sensors, we’ve fused optical, temperature and other sensor technology to provide clinical-grade healthcare snapshots available previously only by visiting the doctor’s office.Inertial sensors today are again leading the way in improving health and wellness. Instead of humans, however, this time the patients are machines. In fact, the health of critical assets – whether factory-based equipment, windmills, train bogies or aircraft – has been assessed through sophisticated analysis of their vibration signatures for many years. The sensors used for these applications have depended on piezoelectric technology because their vibration amplitude signals are very small and difficult to detect and because of the importance of understanding their spectral content over a wide bandwidth. When it comes to noise and bandwidth, bulk piezoceramics have had a major advantage over electrostatic MEMS technology – until recently.Using bulky expensive piezoelectric sensors for condition-based monitoring has been akin to going to the doctor’s office to have an MRI. The equipment required (sensors, receivers) is expensive and requires highly trained specialists to operate the machine and to interpret the information. For this reason, only mission-critical assets are instrumented. For nearly all other equipment, we tend to use inefficient schedule-based maintenance approaches to cover the gap of not having continuous data. Condition-based monitoring leverages real-time sensing of critical machine parameters to reduce system downtime and improve efficiency. Evolving machine healthMEMS started to democratize machine health several years ago, when suppliers began switching from piezoelectrics to capacitive MEMS. While the performance was still not on par with piezoelectric sensors, MEMS technology could already capture a wide array of faults. One example, the ADXL001, started making its way into Integrated Electronics Piezo-Electric (IEPE) and 4-20 mA sensors, which form the backbone of the vibration monitoring market. Although the bandwidth and noise of the sensor did not allow for very early detection and prescriptive monitoring, it did allow the tracking of faults as they progressed and became more imminent.Other digital accelerometers started finding their way into new wireless prototype systems with the goal to simplify and increase deployment to a greater population of assets. The thinking was that self-contained digital wireless sensor nodes could be deployed more economically and quickly, and that these digital sensors would bring the power of computing to the edge node.Unfortunately, even the lowest-noise MEMS products did not have the bandwidth needed to diagnose and predict faults early enough to influence how and when machines are maintained most economically. Instead, such devices were used to detect imminent failure to prevent irreparable harm. As we all know, however, the earlier the doctor spots a problem, the better the probable outcome. That’s because early detection increases the likelihood that the doctor will have access to the full spectrum of treatment options available to fix the problem.Inertial MEMS is blazing a new frontier with the introduction of next-generation capacitive MEMS such as the ADXL100x portfolio. Offering ultra-low noise density and high-frequency response, these newer capacitive MEMS devices fit the bill. With 3dB bandwidths up to 25 kHz and flat response curves within 0.4dB all the way to 10kHz, these accelerometers demonstrate compelling enabling characteristics such as better DC performance, improved robustness, lifetime stability, linearity, and of course, cost, making capacitive MEMS a better choice than piezoelectrics.With high-bandwidth capacitive MEMS much easier to use and deploy – as well as more affordable – the market is starting to respond. Condition monitoring equipment and instrumentation is becoming more accessible to a larger base of manufacturers. In turn, a wealth of data is being created and mined to develop better and timelier predictive and prescriptive maintenance approaches that rely heavily on machine learning and artificial intelligence (AI).It’s worth paying attention to the sizable condition-based monitoring market. Estimated at $3.5 billion and growing, condition-based monitoring reduces downtime and increases equipment utilization in quantifiable ways. And it’s not just manufacturers who stand to benefit. More sustainable and efficient industrial processes, safer trains that crisscross continents at ever increasing speeds, autonomous cars and trucks that know what’s happening under the hood as well as on the road, and modern infrastructure to support our evolving lives show us that condition-based monitoring has something for everyone.Learn more about Analog Devices’ condition-based monitoring signal-chain options that help customers on the journey from sensor to solution. View ADI’s whole portfolio of condition-based monitoring solutions online or download Next-Generation Condition-Based Monitoring brochure.Tzeno Galchev is product marketing manager in the Inertial Sensor Technology Group at Analog Devices Inc. He oversees the strategic marketing and product definition of the inertial sensor component portfolio. He received B.S. degrees in both Electrical and Computer Engineering in 2004, and M.S. and Ph.D. degrees in Electrical Engineering in 2006 and 2010 respectively from the University of Michigan, Ann Arbor. He has over 30 publications in the area of MEMS, holds multiple patents, and is a frequent lecturer and speaker on topics related to MEMS, energy harvesting and sensors.Analog Devices is a longtime 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.

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.

Despite market saturation and stagnation saddling many business sectors, MEMS remains a shining star in the semiconductor industry. Opportunities in automotive, consumer electronics, mobile, medical are rising. What is supporting this industry growth? Who are the big players on the horizon?SEMI spoke with Dimitrios Damianos, Technology Market Analyst, Photonics, Sensing and Display division at Yole Développement, about MEMS market dynamics and future trends. Damianos shared his views ahead of his presentation at SEMI MEMS Imaging Sensors Summit, 25-27 September, 2019, at the WTC in Grenoble, France. Join us at the event to meet experts from Yole and many other key industry influencers. Registration is open.SEMI: MEMS and sensors is one of the healthiest industries not only in Europe but globally. Despite a global economic slowdown, the MEMS and sensors is still growing. What is fueling this growth?Damianos: The value of the global MEMS and sensor market will almost double from $48 billion in 2018 to $93 billion in 2024. In 2018 the MEMS and sensor market represented more than 10% of the total IC market, as more and more MEMS devices and sensors, such as MEMS, image sensors, and RF filters, are integrated in end products in consumer and automotive. In particular, the value of the MEMS-only market reached $11.6 billion in 2018, with consumer applications accounting for more than 60% of the total market. From 2019 to 2024 the MEMS market will grow 8.3% annually in value driven by pressure (for TPMS), RF (for V2X 5G communications), inertial (for ADAS) and future MEMS (such as pMUT for ultrasonic fingerprint) (Source: Status of the MEMS Industry report, Yole Développement, 2019). SEMI: How are MEMS shaping the semiconductor industry today? Damianos: MEMS have a make-smarter enabling capability. They are providing context for new applications and services in transportation, mobility, health, and security. Large companies such as Alibaba and Google are considering MEMS as a critical element in their business solution domains covering the upcoming smart home, smart campus, smart city and smart industry applications. MEMS have key features that correspond to these companies’ criteria for accuracy, small size (without performance degradation), low power and always on (e.g. microphones). Furthermore, with the advent of sensor fusion and edge computing, more sensor data can be processed, maximizing the qualitative and useful information about us and our surroundings. This has a huge impact in all markets, especially consumer.SEMI: MEMS foundries performed well thanks to the boom in industrial and medical applications. Who are the big players right now?Damianos: During 2018, all foundries saw their revenue increase. STMicroelectronics, Teledyne Dalsa, Silex, IMT, Micralyne and Philips Innovation Service are important MEMS foundry players that offer services for various MEMS devices used in medical and industrial markets, among others. On one hand, medical applications were driven mostly by microfluidics, flowmeters, pressure and inertial MEMS. On the other hand, industrial applications were driven by inkjet heads, microbolometers and pressure MEMS. The market prospect, however, is huge for RF MEMS and oscillators that will be used in next-generation 5G infrastructure. SEMI: What is the current status of MEMS for automotive applications? What are the related market drivers? Damianos: In automotive applications, accelerometers and pressure sensors still account for the lion’s share in units. Pressure sensors will grow at more than 8% with Tire Pressure Monitoring System (TPMS) implemented in Chinese vehicles in the near future. After 2019 and 2020, with the new Chinese standard, GB 2614, TPMS will become compulsory: 100% of all new vehicles will have TPMS. Also, automotive MEMS could grow quicker than the corresponding car market (currently at approximately 3%). The reason is a higher number of many different MEMS devices that are being integrated in cars, such as MEMS inertial measurement units (IMUs), TPMS, environmental MEMS for gas and particle monitoring in-cabin and microphones for hands-free voice commands.SEMI: After years of decline, the inkjet heads industry is growing again. What other segments are benefiting from MEMS technology applications? Can you name two examples?Damianos: RF MEMS (BAW filters) is also benefiting from applications in smartphones and will continue to benefit with the arrival of 5G. 5G means additional high frequency sub-6 GHz bands that can only be addressed by BAW filters. Moreover, new infrastructure approach using active antennas will create an expanding market for BAW.Another segment is inertial sensors. Inertial MEMS already have a high potential in wellness and fitness wearables and are gaining support for medical wearable applications to monitor patient activity, with the aim to prevent seizure in cases of epilepsy and other mental disorders. Compared to other types of sensors, MEMS is the golden technology for inertial sensors integrated into medical wearables. They are used for rehabilitation systems, activity trackers and assistance living/fall detection. Specifically, the IMU market will continue to grow for consumer and automotive applications as their price and form factor continue to shrink and they replace traditional standalone MEMS accelerometers and gyroscopes. However, the inertial sensor market will mostly grow for smartphone applications (mostly 6DOF, with 9DOF volumes being comparatively low).SEMI: Give us one prediction about the opportunities offered by the MEMS technology. Damianos: Sensor fusion is becoming more and more relevant since billions of MEMS sensors are made every year. The upcoming 5G revolution will make connectivity easier than ever, creating exponentially more data. To make these data meaningful, data processing is mandatory. Big data is an industry born of recent advancements in AI and machine learning, built upon and fueled by a wealth of new data from ever-expanding sensor applications. An upcoming trend is edge computing, with sensors and MEMS driving a new age of technology. Sensors are digitizing the human experience, and as the real and virtual worlds move closer together, it will be sensors that bind them, enabling new experiences for users everywhere. Running AI at the edge, coupled with sensor fusion, will open new applications for MEMS in audio, motion, olfactometry, and imaging. We also expect that new MEMS devices (microspeakers, ultrasonic fingerprint, pMUT) and piezoelectric MEMS technology could rejuvenate the MEMS market. SEMI: What are your expectations for SEMI MEMS Imaging Sensors Summit and why would you invite your peers to attend? Damianos: SEMI is organizing another very successful event, gathering experts from the Imaging and MEMS industries. We are at a turning point of innovation, with many technological advancements in AI, IoT, AR/VR, biometrics, and other areas where Imaging and MEMS technologies are paramount. Yole is excited to hear the thoughts of many high-profile experts on existing activities and future prospects within their organizations. If you are too, then it is an event that you shouldn’t miss!Dimitrios Damianos, Ph.D. is a Technology and Market Analyst in the Photonics, Sensing and Display division at Yole Développement (Yole). Damianos is a member of a Yole team that produces technology and market reports on the imaging industry including photonics and sensors. Damianos holds a MSc degree in Photonics from the University of Patras (Greece). After his research on theoretical and experimental quantum optics and laser light generation, Dimitrios pursued a Ph.D. in optical and electrical characterization of dielectric materials on silicon with applications in photovoltaics and image sensors, as well as SOI for microelectronics at Grenoble’s university (France). He has also authored and co-authored several scientific papers in international peer-reviewed journals. Learn more! Join the webinar on 5th September 2019. Registration is open! Serena Brischetto is a marketing and communications manager at SEMI Europe.

Self-driving cars have been all the rage in both the trade and popular press in recent years. I prefer the term “autonomous vehicles,” which more broadly captures the possibilities, encompassing not only small passenger vehicles but mass transit and industrial vehicles as well. Depending on who’s talking, we will all be riding in fully autonomous vehicles in five to 25 years.The five-year estimates come from startups eager to raise venture capital while the 25-year estimates stem from Tier 1 automotive suppliers who tend to be more conservative in outlook. Regardless of the timeframe, a multitude of investors – national governments, venture capitalists and companies – are dedicating significant capital and effort to make autonomous vehicles a reality.I must admit that I did not fully grasp the enthusiasm for self-driving cars until last year. First, I’ve always enjoyed driving, unless I’m in stop-and-go traffic, so I couldn’t imagine relinquishing the task. Second, I’ve deliberately arranged my life to spend minimal time in my car. However, traffic has become much heavier in my metropolitan area (Boston), and I know that many people in cities around the world face longer commutes and waste more time in gridlock.What is the solution to this problem that is only getting worse? I had an epiphany while walking through Shinigawa Station in Tokyo, one of the busiest train stations in the world. Dense streams of people crisscrossed the station on their individual paths, managing to avoid collisions without the aid of traffic controls. Evidently, humans have an innate collision-avoidance ability that makes traffic controls for pedestrian crowds unnecessary. If autonomous vehicles could achieve the same excellence in collision-avoidance, we could potentially reduce or eliminate traffic controls for vehicular traffic, providing a huge gain in transportation efficiency and relief from gridlock.Sensors as core building blocksNew and improved sensors, many based on micro-electromechanical systems (MEMS) technology, are key to achieving this vision. While MEMS inertial sensors (such as accelerometers and gyros) are already integral to the core safety systems in conventional vehicles, they are also essential to improved self-navigation in autonomous vehicles.The challenge for MEMS suppliers is to deliver inertial sensors that meet the requirements for self-navigation systems, which are different and more demanding than for safety systems.Pinpointing a vehicle’s position requires “dead reckoning” based on inertial sensor signals as a supplement to GPS input. Undesirable drift in the inertial sensor signals due to mechanical quadrature, temperature sensitivity and noise can quickly add up to a large error in position that may result in a collision. To meet the more rigorous requirements for autonomous vehicles, suppliers must design MEMS inertial sensors that are substantially more precise and resistant to drift. This requires design software that is both extremely accurate and fast, as well as increasingly precise and reliable manufacturing capabilities.Other MEMS-based devices, such as micromirrors and micro ultrasound transducers (MUTs), are also promising options for implementing vision and range-finding systems in autonomous vehicles. These sensing systems are needed for building electronic versions of the human collision-avoidance abilities that I witnessed in Shinigawa Station – and it is these systems that autonomous vehicles must emulate.When will self-driving cars become a reality? Aside from the provocative question that got you to read this far, I don’t have a definitive answer. It will undoubtedly occur in phases, ranging from the driver-augmentation systems available in today’s cars to the full autonomy and ubiquity that will allow reduction of traffic controls in 20 years or more. It is clear that the ultimate goals for autonomous vehicles are highly worthwhile, and that achieving those goals will require better-performing and more diverse MEMS sensors. Stephen (Steve) Breit, Ph.D. is Senior Director, MEMS Business, at Coventor, a Lam Research Company. Steve has been responsible for overseeing development and delivery of Coventor’s industry-leading software tools for MEMS design automation since joining Coventor in 2000. Steve holds numerous patents on software systems and methods for MEMS design automation and virtual fabrication. He holds a Ph.D. in Ocean Engineering from MIT and a B.S. in Naval Architecture and Marine Engineering from Webb Institute.For more information, visit: https://www.coventor.com