Infineon

Smart car technology is on the fast track. According to a forecast by the Consumer Technology Association, revenue for North American technology will reach $398 billion in 2019, with sales of emerging technologies related to automotive electronics alone expected to hit $17 billion, a 9 percent increase over 2018. Growth of automotive electronics in the semiconductor application market is on pace to exceed 10 percent for the first time, with a 11.9 percent annual compound growth rate from 2017 to 2022, said Peng Maorong, research manager of ITRI Industrial International. Today, automotive electronics trails only personal computers and mobile devices in driving semiconductor market revenue. For its part, Automotive World 2019, the world's largest exhibition for advanced automotive technologies, has drawn even more attention in recent years. The event consists of six exhibitions, including automotive electronics technology, auto parts, drive systems, lightweight materials, autopilot technology and car networking, and featured demonstrations of compelling technologies including an AI deep learning module (Xilinx) and high-speed car intranet technology (Israeli manufacturer Valens). Toyota is also on the cutting edge of automotive electronics with the rapid maturity of its semiconductors, AI technology and materials, and complete network technology. The carmaker is no longer just a pure-play automotive manufacturer. Instead, the automotive giant is positioning itself as a car service provider (mobility service provider) and plans to team with ride-sharing providers such as UBER and Didi and other automotive technology providers in the future.Taiwan, with its strong semiconductor industry chain and a complete ecosystem of information communication, will be a key force in the automotive market as the region looks to cross-industry and cross-border cooperation to help power the market. To help the automotive electronics industry seize the market promise of smart cars, SEMI established the Global Automotive Electronics Advisory Committee (GAAC), with members including Audi, Bosch, Denso, Ford, Honda, Nissan, Volkswagen, Amkor, Infineon, NXP, Synopsys and Wanghong. More than 30 international companies, spanning Europe, the United States, Japan and other regions are represented on the committee. The committee met for the first time this month in Taiwan to help leverage the prowess of Taiwan's microelectronics supply chain in advancing international automotive electronics, better link Taiwan to international trends, and give Taiwan a bigger voice in the emerging smart car market, and create more opportunities for resource integration across borders. To learn more about GAAC, contact Helen Chen Chen Huiyu | Email: [email protected] | Phone: (03) 560-1777 #112.Extended reading: smart car Baihua Qi will be the next wave of killer applications (on)Emmy Yi is a marketing specialist at SEMI Taiwan.

What’s next for smarter, more connected electronics manufacturing - Part 3 The fast-maturing infrastructure now enabling analysis of exponentially larger data volumes brings the microelectronics industry to an inflection point, where the winning companies will be the first to master the use of this data to solve the industry’s emerging challenges. SEMI expands its coverage of these vital issues with a Smart Manufacturing Pavilion and three days of talks SEMICON West, July 10-12 in San Francisco. While deep learning is starting to be applied to image recognition for wafer inspection, it is also being considered for sequential pattern recognition in order to evaluate equipment parameter traces. The next emerging applications will start to use those learned patterns to predict outcomes, and then use those predictions to automate process control. One early application of deep learning is IC process development. “People don’t think of research and development as the first place to automate, but it’s where applying our digitization and simulation has first had impact,” says David Fried, Coventor vice president of Computational Products. He noted that insertion is easier in the lab than in the fab. Technology at 10nm and beyond is now so complex that companies at the leading edge must use process modeling to understand the effect of process variation on their designs. Learning cycles can now be accelerated during development by simulating 10,000 digital wafers instead of running 25 actual wafers during screening, Fried says. Applying structured analysis and machine learning to the data simplifies optimization across the 500 or more interrelated process steps. Coventor has recently introduced a statistical analysis package that aids the design and analysis of process variation experiments by using large volumes of data from its models. Fried says these models are next being used to accelerate the yield ramp in manufacturing. Digital simulation also could speed development of high-mix, lower value products While digital twins are best known for their use in complex, high value products like jet engines, the simulation technology could also enable the electronic manufacturing services (EMS) sector to reduce the time, cost and risk of developing its high mix of products. “The EMS sector’s use of digital twins will be vital for it to smooth the move of CAD/CAM digital design data for so many different products into manufacturing, and to accelerate validation testing of designs and products by doing more of it in the virtual world,” says Dan Gamota, vice president of Engineering and Technical Services at Jabil. Gamota also highlights the push for traceability from the automotive and healthcare markets, where the digital models could be used to quickly assure that the design was built exactly as specified. “In the past year, traceability has evolved from just ‘nice to have’ to ‘how to achieve,’” he adds. “Companies are expecting it, but aren’t willing to accept the cost and risk of doing it alone. We need the community to discuss realistic implementations, identify the most critical elements and bring together the ecosystem partners to build baseline reference architectures for key digital building blocks. The community also needs to assure the reliable flow of data among the electronic manufacturing segments from semiconductor to OSAT to EMS.” Predictive maintenance and virtual metrology applications could mature in next few years While predictive maintenance initially seemed a likely early application of machine learning in factories, it remains a challenge for the electronics sector. “The difficulty is that it’s not clear where to get the most bang for the buck,” says Tom Ho, president of BISTel America, noting that it may make the most sense to track the failure performance of a single expensive part, like an electrostatic chuck, since predicting the failure performance of a whole complex system like an etcher is much harder. “Collecting enough data from all failure types, including especially the rare events, is difficult unless you have a long history of a lot of tools,” adds Doug Suerich, PEER Group product evangelist. “The gain from collecting performance information from many tools across the industry could be big, but many companies still need to overcome concerns around exposing their IP.” Another big opportunity for prediction is virtual metrology – predicting the wafer outcome from the process or sensor data with enough accuracy to replace the physical metrology. “Virtual metrology is improving, and since metrology can be slow and expensive, any reduction could mean a huge potential savings,” says Suerich. “But it is still seen as too scary for many companies. Two to three years from now, companies will expand the practice from lower risk areas into processes that require more confidence in the results.” Moving beyond prediction to automated control needs digital models Once the results are predicted, the model can be used to control or automatically optimize a process and enable the system to learn by itself, usually by reinforcement learning on a digital model. The model can then independently make adjustments to optimize the manufacturing process. “Automated process development is getting close now. Instead of smart guys turning the knobs, deep learning is automating the smart tuning,” says Suerich, suggesting the industry could see widespread adoption in as little as two to three years. This type of machine learning needs a good digital model, and masses of data for learning. One approach uses human experts to build a physics-based model of the clearly understood parts of the process, then turns to deep machine learning to optimize the lesser-understood variables. The alternative, the data-first approach, runs a computer algorithm to suggest the solution purely from data, without human input, and then relies on the human to evaluate the usefulness of the results. Modeling digital twins of wafers could enable automated process control, chamber matching, and fleet matching, says Fried. If every wafer had its own virtual twin with all the upstream metrology and structural information needed to make equipment control decisions, it could feed forward that information to enable the seamless transition from one step in the process to another based on understanding their complex interrelationships. This could potentially improve uniformity across wafers and equipment, and reduce the need for metrology, he argues. Moving metrology sensors into the chamber will also require model-based algorithms to enable dynamic process control in close to real time, says Fried. These algorithms will be needed to acquire, parse, and process the data at high speed, and then to choose how to adjust the controls. “There will be a model behind collecting and interpreting the metrology data,” he notes. “That’s a really rich vein for improvements in process control.” “The end goal is to collect equipment data in real time, analyze it with AI, and send back controls to optimize manufacturing processes,” Jabil’s Gamota says. “This requires a robust architecture for communication between equipment and consistent formats for data collection and analysis. But the cost and complexity of this heavy lifting is too great for any one company to do alone. We need a consensus-based architecture for ingesting, analyzing and acting on the data.” SEMI tests data transfer protocols, benchmarks best practices SEMI is launching a smart data project to identify the various data transfer protocols needed for inter-company communications. The project will feature a proof-of-concept model in a development fab to produce verifiable results so SEMI can better understand how different approaches meet member needs. SEMI’s smart manufacturing technology communities and the Fab Owners Alliance are also benchmarking current smart manufacturing practices in the microelectronics industry to help SEMI members better understand the path forward and potential return on investment. Speakers over all three days at SEMICON West addressing these issues include Active Layer Parametrics, Applied Materials, Applied Research Photonics, ASML, Bosch Rexroth, Cimetrix, Coventor, ECI Technologies, Edwards Vacuum, Final Phase Systems, GE Digital, Infineon, Jabil, Lam Research, Osaro, Otosense, PEER Group, Qualcomm, Rockwell Automation, Rudolph Technologies, Schneider Electric, Seagate, Siemens, Stanford University, TEL, TIBCO Software. See semiconwest.org. What’s next for smarter, more connected electronics manufacturing - Part 1 What’s next for smarter, more connected electronics manufacturing - Part 2 Paula Doe, SEMI

What’s next for smarter, more connected electronics manufacturing - Part 2The fast-maturing infrastructure now enabling applications for big data and artificial intelligence means disruptive change not just at individual companies but also in data connections among companies across the microelectronics manufacturing value chain. SEMI checked in with some leading players on the changes they see coming in the next several years for this article series. The trade group is expanding its programming on smart manufacturing to address these industry-wide developments at SEMICON West, July 10-12 in San Francisco.“The ramp of EUV, and the smaller geometries and smaller process margins, will drive an exponential increase in the amount of metrology data to manage,” says Neal Callan, ASML vice president, Silicon Valley. Callan notes that moving to multibeam e-beam inspection will increase data volume from megabytes per second to gigabytes per second and from thousands of data points to millions of data points. “The process is so tight and the margin so small that stochastic variation, or noise, becomes more dominant – at least it’s noise until we can learn to understand and control it. And understanding and controlling this variation will be key to delivering 5nm patterning,” he says.Single-beam e-beam inspection is already driving large increases in data as engineers extend the slow technology to broad, high-speed defect metrology applications by more intelligently instructing the system where to look for problems. Callan says ASML is now using the scanner data on wafer focus, alignment and leveling. The company is also using the computational lithography model from the design to identify the smallest process windows in the pattern that are most likely to see problems. The model then quantifies the number and significance of those instances.“The collection of all this diverse data means that tools will need to be plug-and-play so all tool data is instantly available to all systems and software,” says Doug Suerich, PEER Group product evangelist. “We need tools that can be discovered automatically by the network so it can start slurping up data immediately. The adoption of the Interface A (EDA) standard is accelerating and fabs are starting to ask for it. The proliferation of sensors also needs to self-discover. If you are going to add thousands of new sensors into a facility, you can’t afford a time-consuming integration process.”“We are now seeing that engineers are greedy for more data – if they can get the data, it’s becoming a need-to-have,” adds Tom Ho, BISTel America president. “Getting more data from more sensors, from the sensors on the tool that are not being fully utilized, and from untapped data sources like vibration is another big coming opportunity.” Process complexity drives demand for feed-forward between silos with computational models ASML co-optimizes its scanner process with etch and reticle process steps. Source: ASML In addition to the drive for trace-back of data, the increasing complexity of interrelated processes is also driving demand for feed-forward of data. “Feed-forward is becoming more important,” notes Ho. He points to the example of 3D NAND features, now getting so deep that identifying the layer being measured is a challenge unless the signal at the step before can be recognized. “We need partnerships with our peers to understand how to take advantage of the sensors they use, integrate them with our data, and then feed-forward corrections to the other systems,” concurs Callan. “To drive the best CD uniformity and overlay, we need to co-optimize litho and etch,” agrees Henk Niesing, ASML director of product management. He notes that the company is working with etcher makers to measure the overlay and CD, decompose the finger prints, and then use models to steer automated control that best adjusts both the scanner and the etcher. ASML is also working with Zeiss on co-optimization between the scanner and the reticle to make even higher-order corrections by locally modifying the reticle.These higher-order corrections, applied on each exposed field, drive the need for even more data, and at higher speed but without higher cost, notes Jan Mulkens, ASML senior fellow. These corrections increase demand for computational metrology, which combines various metrology sources with physics and deep learning models trained on real data to predict and control process results in real time. “We’re working on computational metrology to ideally use all the knobs we have in the fab,” he says. So far this effort has largely involved linking data between two companies. More consistent data formats would enable data exchange to be extended to more companies. “The software versions also need to be managed for upgrades so they still match after one party updates the system on its tool,” notes Niesing. Speakers on these issues of smart manufacturing and data handling at SEMICON West include Active Layer Parametrics, Applied Materials, Applied Research Photonics, ASML, Cimetrix, Coventor, ECI Technologies, Edwards Vacuum, Final Phase Systems, GE Digital, Infineon, Jabil, Lam Research, Osaro, Otosense, PEER Group, Rockwell Automation, Rudolph Technologies, Schneider Electric, Seagate, Seimens, Stanford University, TEL, TIBCO Software. See semiconwest.org.What’s next for smarter, more connected electronics manufacturing - Part 1What’s next for smarter, more connected electronics manufacturing - Part 3Paul Doe, SEMI

What’s next for smarter, more connected electronics manufacturing - Part 1The fast-maturing infrastructure now enabling applications for big data and artificial intelligence means disruptive change not just at individual companies but also in data connections among companies across the microelectronics manufacturing value chain. SEMI expands its smart manufacturing program with a Smart Manufacturing Pavilion with displays and three full days of talks to address these industry-wide developments at SEMICON West, July 10-12 in San Francisco.Autonomous autos’ demand for zero-defect systems and 100 percent traceability back to the manufacturing data for each die is driving a push to traceability across the chip sector. “Far more chips are being used by the automotive sector, and its very different requirements are driving demand for traceability,” says Tom Ho, president of BISTel America. “Our chipmaker customers are looking for traceability solutions and the trend is the same in backend packaging and assembly – automotive applications are driving the sector to traceability.”Traceability is also driven by the growth of systems in a package as fabless chipmakers look to connect back to the packaging companies’ fault analysis labs and die interconnect history to diagnose and fix the cases where known-good die are failing in the system, adds Mike Plisinski, CEO of Rudolph Technologies. Plisinski adds that makers of consumer products like phones that can also see harsh conditions are demanding higher quality and traceability as well. The electronic manufacturing services (EMS) sector also must establish an architecture for traceability to collect critical manufacturing-related data and to interface with OSATs and semiconductor fabs. The reason is that EMS companies are adding traditional OSAT processes such as assembly of products with bare die and complex optics modules requiring clean rooms. “A unified sand-to-smart-phone smart manufacturing roadmap should be established,” says Dan Gamota, vice president of Engineering and Technology Services at Jabil. “We need to identify protocols for manufacturing data communications that can be adopted across the supply chain.”To enable smart manufacturing, vendors need to collaborate on getting their production equipment to interoperate and support factory analytics and data management systems. Source: SEMI One big challenge, of course, is how to format this diverse data so it can be linked and used by various supply chain stakeholders. “Smart data needs to be contextual and it needs data standards across the supply chain so it’s easy to link from the front end to the back end, follow common lot IDs front and back end, and have a way to map streaming data from sensors to a discrete lot ID,” notes Ho. New approaches to metrology, analysis and test that increasingly exploit machine learning on simulations will also be needed to help predict which die and connections that test well now may fail in the future as conditions change.Another issue is how to securely share the needed data across companies without jeopardizing IP. “On the equipment side we collect data across customers on how the tool is running to improve the equipment,” notes Neal Callan, ASML VP Silicon Valley. “Next we need to integrate performance and reliability data that today is not as well shared.”The other big hurdle is how to pay for data sharing. “The challenge is that the final manufacturers reap the benefit of traceability, but since they expect their suppliers to deliver good die, they don’t want to pay more for it,” notes Plisinski. He suggests that over the next two to three years, traceability and predictive fault prevention will become the norm as the automotive sector is compelled to invest in it to assure safety. Meanwhile, fabless companies will face so much complexity in integrating different die from different suppliers in SiP that they will no longer be able to afford to simply use the cheapest supplier, potentially driving a fundamental shift in relations and division of labor among fabless chipmakers, OSATs and fabs. Standards extend across supply chainSEMI member committees are collaborating to build the infrastructure to enable these developments. Standards committees are updating standards for higher bandwidth data exchange and extending semiconductor-like vertical and two-way horizontal equipment communication standards to flow shops to enable assembly players to optimize and trace back results across players. The SMT/PCBA community is integrating its smart manufacturing work into SEMI standards, and the SEMI A1 standard was a key reference document in the development of the Japan Robotics Association’s Equipment Link Protocol.Speakers addressing these issues at SEMICON West include Active Layer Parametrics, Applied Materials, Applied Research Photonics, ASML, Bosch Rexroth, Cimetrix, Coventor, ECI Technologies, Edwards Vacuum, Final Phase Systems, GE Digital, Infineon, Jabil, Lam Research, Osaro, Otosense, PEER Group, Qualcomm, Rockwell Automation, Rudolph Technologies, Schneider Electric, Seagate, Siemens, Stanford University, TEL, TIBCO Software. See semiconwest.org.What’s next for smarter, more connected electronics manufacturing - Part 2What’s next for smarter, more connected electronics manufacturing - Part 3Paula Doe, SEMI

The fast-growing automotive semiconductor market means big change for the IC supply chain. Beyond the obvious demands for reliability and traceability, the sector is moving towards simpler and lower-cost solutions while facing the daunting challenge of automating driving in a complex world. The need for simpler and cheaper automotive intelligence will likely drive acquisitions to build complete platform solutions that are easier to integrate. This demand has already spawned a market for pre-configured test cars to save developers time and money, and is driving LiDAR (Light Detection And RADAR) towards lower-cost, solid state solutions. “The growth of the automotive electronics market provides a great opportunity for the IC supply chain to differentiate on specialty processes and quality for the high-volume automotive business with its long design cycles,” says Scott Jones, principal, strategy, at KPMG, who will speak in the automotive program at SEMICON West. “This differentiation is a chance to reduce chip suppliers’ dependence on scaling volume for the mobile phone world with its short-cycle volatility of winning and losing sockets.” He notes that increasing demand for automotive ICs is also reinvigorating the eight-inch supply chain and spurring opportunity for specialty products such as compound semiconductor devices for power efficiency. Supplying the automotive market also means addressing automotive reliability requirements, which can be 10 times more stringent than for consumer devices. At the same time, the industry must sustain fast-paced development cycles required for the volume and diversity of low-cost IoT devices, manage the segmented supply chain for both those markets, and still spread development costs. Another big challenge for the supply chain will be to automate testing and update vast amounts of embedded software in these automotive devices. “The more complete solution a company can put together, the more the automakers will gravitate to it. They want simplicity,” Jones suggests. Smaller players will need to differentiate with IP and acquire other IP provider to build a broader platform, or be acquired and folded into an all-in-one solution.AutonomouStuff helps accelerate and simplify development of autonomous driving solutionsAutonomouStuff is helping to speed development of these platforms. The company has grown from a sensor distributor into a supplier in the emerging niche of vehicles preconfigured with key interfaces for sensors and controls. These interfaces can then be customized by integrating different components for developers to test their applications. AutonomouStuff offers developers a lineup of vehicle models pre-configured with the interfaces needed to add desired chips, sensors and software to develop their autonomous vehicle systems. Source: AutonomouStuff.“Whether they’re major chipmakers or AI software startups, they don’t have a year to build their own vehicle platforms themselves for developing autonomous vehicle systems,” says Wolfgang Juchmann, VP sales and business development at AutonomouStuff. Juchmann, a SEMICON West speaker, will bring a demonstration vehicle to the show. “In four to six weeks we can prepare a custom test car with selected sensors, enabling users to start testing their computer platforms and software. It’s faster and more cost-effective for us to supply the car with the needed interfaces.” He notes that developers are using some 300 AutonomouStuff vehicles in the field. AutonomouStuff customers are starting to transition from testing on a single car or two to testing on mini-fleets with 50 to 100 vehicles. Beyond sensors and pre-configured vehicles, the next step will be to add more data intelligence services to help with capabilities like tagging the data for training, Juchmann says. AutonomouStuff already offers hardware to support Baidu’s Apollo open-source software stack and data set. The company was recently acquired by the Swedish holding company Hexagon to help support expansion.CMOS silicon LiDAR nears automotive qualificationInnovations in the hyper-competitive LiDAR market, where burgeoning demand is driving the race to develop various types of solid-state devices, may also help reduce the cost of autonomous vehicles. Among the roughly 40 LiDAR suppliers, at least one – Quanergy – is taking advantage of 45nm and 32nm foundry CMOS volume production. The company uses voltage through the semiconductor stack to change the refractive index, controlling the phases of optical beams and the resulting interference patterns of light exiting the chip to quickly steer the laser beam without the need for moving parts, much like the phased array radar its team developed earlier. Solid state LiDAR image with object recognition software. Source: QuanergySo far, most of the small LiDAR units have shipped to the security, industrial automation, drone, robots and 3D mapping markets. However, Quanergy CEO Louay Eldada, another SEMICON speaker, says the company is also winning automotive designs and expects automotive shipments to take off early next year, once automotive certification testing is completed. “We can get design wins because standard CMOS production at TSMC makes us a known entity,” says Eldada. To prevent component misalignment, the company produces its own specialized packaging to secure the laser, phase control ASIC, optical phased-array emitter, detector array, and receiver readout ASIC at its plant in Silicon Valley or the facility of its automotive partner Sensata. Through its software business, Quanergy offers an artificial intelligence (AI) perception program for object recognition and LiDAR tracking. The solution uses the people-tracker software the company acquired from Raytheon.SEMICON West this year expands to three full days of automotive electronics programming and features a Smart Transportation Pavilion. Other companies with experts who will speak as part of the program include XPT/NIO, Infineon, McKinsey, Voyage, GM Cruise, Bosch, Deepen AI, Airbus A3, Nvidia, Excelfore, Byton, Macronix, SK Hynix, SAP, Xilinx, Achronics, California Fuel Cell Partnership, Velodyne, Lam Research, KLA-Tencor, SCREEN, Rockwell, Versum Materials, TechSearch International, Entegris, ASE, Amazon, Continental and Wind River. www.semiconwest.orgPaul Doe, SEMI

Device manufacturers continue to invest. Spending in cloud data center (compute, networking and storage), automotive (content per car increases), industrial (on content, factory automation, and positive macro trends), and consumer (gaming) end-markets is particularly strong. We see capital expenditure growth in 2018 and early indications pointing to sustainable spending into 2019. We also expect 14 percent increase (YoY) for fab equipment spending in 2018, up from the February forecast of 9 percent, and expect 9 percent increase in 2019, adjusted from the February forecast of 5 percent. 92 future facilities/lines with various probabilities are scheduled to start production in 2018 or later. Fab investment is just one indicator of how growing demand in areas such as from Artificial Intelligence (AI), cloud/data storage, automotive and Internet of Things (IoT) is driving unprecedented spending in the semiconductor industry. Below are a few highlights* of recent SEMI FabView insights. Details of each project can be found in FabView online 24/7 or World Fab Forecast report (Excel format). Infineon’s new 300mm Fab in Austria - Infineon is planning a new 300mm thin wafer Fab for Power Devices in Villach, Austria. Rumors on Toshiba’s new Fab plans - More 3D NAND fabs in the future at Toshiba are feasible. The timing will depend on market conditions, and our forecast will adjust accordingly. Vanguard's possible 300mm foundry fab - Vanguard's management said it might buy or build a 300mm fab in the near future as all 200mm fabs are essentially full. Powerchip plans to build new memory fab in Taiwan - Powerchip is investing more in expansions since Memory pricing is holding up. Rohm announced to build a new SiC fab in Fukuoka Japan - Rohm announced its plans to build a new SiC fab. Micron is building a new fab in Singapore - Micron broke ground in a ceremony for a new fab in Singapore on April 4, 2018. Bosch had groundbreaking ceremony of their 300mm fab in Dresden end April 2018 - Investment of 1 billion Euro. This is the biggest single investment in Bosch’s 130-year history. SEMI FabView, a mobile-friendly, interactive version of SEMI’s popular World Fab Forecast, delivers on-demand fab information such as fab spending and capacity for over 1,100 facilities, including over 82 planned facilities worldwide, across a wide range of product segments including Power, GPU, Memory, Foundry, MEMS and Sensors fabs. Fab data include region, start of construction, operation, construction and equipment spending, capacity, wafer sizes, product types and geometries. SEMI FabView subscribers receive forecast model updates through SEMI’s World Fab Database. Click here for a trial to experience SEMI FabView first hand. *Actual updates provide more detail Christian G. Dieseldorff and Clark Tseng, Industry Research Statistics Group, SEMI.

Christian G. Dieseldorff, Industry Research Statistics Group, SEMI (June 12, 2018)The semiconductor industry is nearing a third consecutive year of record equipment spending with projected growth of 14 percent (YOY) in 2018 and 9 percent in 2019, a mark that would extend the streak to a historic fourth consecutive growth year, according to the latest update of the World Fab Forecast report published by SEMI. The industry last saw four consecutive years of equipment spending growth in the mid 1990s.Korea and China are leading the growth, with Samsung dominating global spending and ascendant China on a fast, steep rise, surging ahead of all other markets. See figure 1.Figure 1: equipment spending by region (includes new and refurbished)Samsung is expected to reduce equipment investments in 2018. Despite the ebb, the company still accounts for a dominant 70 percent of all investment in Korea. At the same time, SK Hynix is increasing its equipment spending in Korea.China’s equipment spending is forecast to jump a whopping 65 percent in 2018 and 57 percent in 2019. Notably, 58 percent of investments in China in 2018 and 56 percent in 2019 stem from companies with headquarters in other regions such as Intel, SK Hynix, TSMC, Samsung, and GLOBALFOUNDRIES. Domestic, Chinese-owned companies – backed by large government initiatives – are building an impressive number of new fabs that will start equipping in 2018. The companies will double their equipment investments in 2018 and again in 2019.Meanwhile, other regions are also ramping up investments. Japan is beefing up equipment spending by 60 percent in 2018, with the largest increases by Toshiba, Sony, Renesas and Micron.The Europe and Mideastern region will boost investments by 12 percent in 2018, with Intel, GLOBALFOUNDRIES, Infineon and ST Microelectronics as the largest contributors. Southeast Asia will increase investments by more than 30 percent in 2018, although total spending is proportionately smaller than in other regions owing to its size. The main contributors are Micron, Infineon and GLOBALFOUNDRIES, though companies including OSRAM and ams are also increasing investments.The SEMI World Fab Forecast, which also includes information on other companies, covers data and predictions through the end of 2019, including milestones, detailed investments by quarter, product types, technology nodes and capacities down to fab and project level.Learn more about the SEMI fab databases at:www.semi.org/en/MarketInfo/FabDatabase and www.youtube.com/user/SEMImktstats.

With Southeast Asia’s semiconductor industry expected to grow up to 12 percent this year, the stakes at SEMICON Southeast Asia were high. The challenge: to drive industry connection, collaboration and innovation across a broad range of technologies to accelerate growth in the electronics manufacturing supply chain.SEMICON Southeast Asia 2018 delivered.The region's premier gathering of the global electronics manufacturing supply chain, SEMICON Southeast Asia drew an event record of more than 7,500 visitors and over 300 exhibitors to its debut at the Malaysia International Trade and Exhibition Centre (MITEC) in Kuala Lumpur. The Market Trends Briefing, an event favourite, offered insights into the latest trends and developments on forward-thinking topics as diverse as the machine as an integral part of human society (NXP Semiconductors Singapore) and intelligent robots (Festo Robotics). Key industry topics including semiconductor fab investments (SEMI) and drivers and applications for Fan-Out Wafer-Level Packaging (TechSearch International) also highlighted the briefing. 2018 Year to Date Statistics from the Market Trends Briefing For the first time, SEMICON Southeast Asia convened policy makers and industry leaders in a panel – the CXO Speaks session – that provided insights into how the region can strengthen its manufacturing ecosystem, capture new opportunities in IoT, and build a resilient and growing electronics industry. The panelists agreed that the Southeast Asia semiconductor market will continue to grow exponentially in the digital era, and that regional players must not only collaborate to sustain this growth momentum but build a strong talent pipeline to continue to drive IoT innovation.With connection clearly critical to the industry’s growth, the event’s Business-Matching sessions and industry VIP networking brought business leaders together to find new partners and opportunities.Themed ‘Think Smart, Make Smart,’ SEMICON Southeast Asia featured few devices smarter and more innovative than Festo’s AirJelly, a radio-controlled airborne jellyfish. The first indoor flying object with peristaltic drive mimics the movement of a real jellyfish – except in the air. The device’s eight tentacles adapt to its environment, just like its 500-million-year-old sea-roaming cousin. A lithium-ion battery, an electric motor and a bit of helium are its wings, allowing it to take flight.The ‘World of IoT,’ a show-within-a-show, highlighted enabling applications and technologies for the IoT revolution. This interactive experience was helmed by seven Malaysian technology start-ups that showcased present and near-future consumer technologies such as autonomous vehicles, smart AI devices and virtual reality applications enabled by semiconductor innovations.In an effort to attract STEM talent to the industry, SEMICON Southeast Asia for the first time staged a panel with 11 experts from the public sector and seven from the private sector to discuss strategies for encouraging young graduates to pursue engineering careers and building a talent pipeline. For their part, the SEMICON Southeast Asia university programme and the Electronics Talent Career Fair focused on helping to build the global semiconductor industry as it faces a worker shortage.At SEMICON Southeast Asia’s Technology Innovation Forum, thought leaders from across the industry answered the question: What does Smart Manufacturing mean to the electronics manufacturing supply chain? While presenters from GLOBALFOUNDRIES, Amkor, PricewaterhouseCoopers, Infineon, Lam, IBM, Omron, and OSRAM looked at Smart Manufacturing from very different positions in the supply chain, they shared common issues with data sharing and data protection, and decision-making methodologies when monitoring a huge influx of sensor data. Samivel Krishnamoorthy, Director of Digital Manufacturing Industrialization at OSRAM, closed the session with a real-world look at the work necessary to transition a cluster of production lines with different systems to Smart Manufacturing capable lines following common systems and data handling techniques. OSRAM embraces SEMI Standards for use in conventional silicon front-end manufacturing in for Osram’s LED production. Krishnamoorthy detailed an exceptional analysis process to benchmark and adapt best practices to complex, multi-stakeholder technology production environments.Those looking for a highly influential audience from every segment of the global microelectronics manufacturing supply chain found it as SEMICON Southeast Asia. Technology and business leaders from segments including semiconductors, LEDs, MEMS, printed/flexible electronics, and other adjacent industries were a powerful presence at the event.Held for the first time in Kuala Lumpur, the event remained true to its mission to connect electronics industry innovators and thought leaders from business, academia and research from both region and all over the world. SEMICON Southeast Asia 2019 will once again be held at MITEC.Kai Fai Ng is President, SEMI Southeast Asia.