Smart Manufacturing

Nexperia became a standalone company about four years ago after our divestiture from NXP Semiconductors. Last year we started our journey towards smart manufacturing at our back-end factories in Asia by developing a roadmap to help steer us in the right direction.Our first step to creating a convincing and workable smart manufacturing roadmap was to define the very meaning of smart manufacturing to Nexperia. Since the definition of smart manufacturing varies widely, we started by looking at two different and distinct technology adaptations: Physical automation Data-driven manufacturing, or using analytics at the core to develop and adopt machine learning and artificial intelligence (AI) models It is important to find the right balance of investments between physical automation and data-driven manufacturing to steer clear of deployment inefficiencies since only connected solutions deliver full value. Our approach involved the following high-level steps. Meeting with internal management teams for their inputs and examining factory needs and maturity Meeting with other semiconductor factory operators, subcontractors and partners to review their smart manufacturing approaches and challenges Evaluating our needs and status against the Singapore Smart Industry Readiness Index model Physical AutomationEvaluating the maturity of available solutions and adaptions by the industry and our own shop floor helped simplify the thought process quite well. Logistic automation is not new. Very mature solutions, even for custom layouts and preferences, are readily available. Shop floor automation is far more difficult than logistic automation since variability is simply too high. Traditional shop floor investments were always driven from quality or OEE perspectives and not necessarily very well connected. Our approach is outside-in – deploy logistic automation first and then move to the shop floor.Data-Driven ManufacturingHow smart manufacturing becomes depends on the extent to which a factory is data-driven. Enabling data-driven manufacturing requires foundational investments to improve traceability, connectivity and real-time operations. We believe real-time awareness can drive machine-level and closed-loop process control critical for predictive, cognitive control of the shop floor.Real-Time Awareness and Traceability is at the CoreDeveloping real-time awareness requires wide-ranging manufacturing protocols. The following focus areas have helped us simplify the challenge: Connectivity Core systems for areas including MES, quality and SAP Analytics and AI Digital shop floor featuring one operator interface with real-time control systems Readiness of engineers, technicians and managers Each of these pillars has different level of complexity due to legacy equipment and systems, legacy processes and inexperience of engineers with automation. This makes deployment of data-driven operations a complex challenge. We looked at different project approaches for each of the focus areas: Core Systems – Build additional technology enablers and roll them out with prioritization planning. Analytics – Focus mainly on OEE and yield with automated root cause analysis and predictive approaches. Real-Time Control – Merge the initiative with factory-level programs to improve productivity and quality. With a strong smart manufacturing roadmap, the next challenge is to secure long-term buy-in on the plan and required investments from executive management. Visiting and otherwise connecting with peer sites that have already deployed smart manufacturing infrastructure is vital in this effort. Thanks to SEMI members, we were allowed to visit their factories with our management team for go-and-see tours since seeing is believing in the smart manufacturing journey. Our executives also met with subcontractors and vendors to better understand the value of this transformational undertaking.A long-term outlook is necessary to successfully develop a smart manufacturing roadmap, and executive commitment goes a long way to ensuring its success. We are excited about our smart manufacturing journey and believe it is a game changer for our factories.Adarsha MARPALLI is director of Factory Automation at Nexperia B.V.

D-SIMLAB Technologies, a Singapore-based provider of simulation-based business analytics and optimisation software solutions, recently joined SEMI. I spoke with Peter Lendermann, the company’s co-founder and Chief Business Development Officer, about the company’s role in the smart manufacturing movement, how customers are benefiting from D-SIMLAB solutions, and what the future holds for smart manufacturing. Ng: What is D-SIMLAB’s mission?Lendermann: Our mission is to develop, market, and deliver high-performance simulation-based decision support solutions that enable corporations to enhance their performance in a sustainable manner leading to significant cost savings. In particular, we focus on semiconductor manufacturing material flow planning and optimisation but also do business in aviation where we help customers optimise their spare parts support operations. What these two domains have in common are three important attributes: They are capital intensive, their underlying operations are complex, and operations are also heavily affected by random, i.e. unpredictable events, which makes both planning and execution of manufacturing operations very challenging. D-SIMLAB is a spin-off from the Singapore Institute of Manufacturing Technology (SIMTech) under the Agency for Science Technology and Research (A*STAR). Our head office is in Silicon Island Singapore. We also have representations in Germany and the U.S. Most of our staff are industrial and computer engineers with up to 20 years of operations experience in their respective industry domain, as well as vast data analytics and software development capability.Ng: What solutions does D-SIMLAB offer to optimise semiconductor manufacturing?Lendermann: In the three-pillar smart manufacturing framework of Connect, Sense and Predict advocated by SEMI, our focus is on Predict though we emphasise the equal importance of the subsequent Act: Our solutions can Predict, for example, WIP waves or usage-based preventive maintenance due dates. But much more value-add can be realised once some decisions with regard to how to Act can be derived from such a prediction. The ability to pro-actively adjust action plans in a timely manner is essential to overcoming challenges arising from changing customer due dates, mix profile changes, untimely production line issues, and production capacity to be shared with R D lots effectively, so that ultimately our customers can enhance capacity, reduce cycle times and improve the due-date performance of their factories.To that end, our D-SIMCON solution suite spans the full spectrum of decision-support tools required to forecast, manage and optimise material flow – from operational scheduling and dispatching, WIP forecasting and dynamic and static capacity planning all the way to specific applications for fab load mix optimisation or for the enhancement of the product/layer dedication and resist allocation in the lithography area. Our solutions are implemented in numerous 6-, 8- and 12-inch wafer fabs operated by both IDMs and foundries worldwide with capacity ranging from 40,000 to 200,000 wafers per month.Ng: What are the key enablers of D-SIMLAB’s success?Lendermann: Our success lies in deploying production-ready solutions for our customers, allowing them to extract immediate value. Our solutions enable the portrayal of many domain-specific characteristics such as queue time constraints or specific equipment behaviour, which is absolutely essential to generating operationally feasible plans or schedules in order to be able to Act in the best possible manner according to what has been Predicted. Moreover, we have modules for automatic generation, calibration and maintenance of the underlying capacity model, including resolution of data inconsistencies as well as verification and validation of the model, to allow near real-time responses to continuously changing operations. And the associated optimisation approaches focus on creating maximum possible value with as few iterations as possible and within minimum time through smart heuristics and parallel computing infrastructure – a paradigm that is as powerful as it is cost-effective.Ng: What are a few of your more notable customer successes?Lendermann: As a result of the first implementation of our novel, multi-objective based Scheduler cum Dispatcher, a tool capacity gain of 8%, a transportation capacity gain of 10%, and an operator workload reduction of 25% were concurrently realised at one of the critical equipment groups in our customer’s fab. At another set of equipment groups in the same fab, a 7% increase of lots within the critical queue time limiting area was achieved.Another use case we successfully realised is fine-tuning of Preventive Maintenance plans: Based on a seven-day lot arrival forecast at each equipment generated with our WIP Forecaster, a recommendation is made when PM would be best possible without causing too much disruption in the WIP flow. The effect of this synchronisation of the PM plan with material flow enabled a dramatic reduction of the average queue lengths at critical equipment groups and the associated cycle times without incurring any capacity loss. Reduction of average queue length as a result of synchronising preventive maintenance with material flow. Ng: What challenges has D-SIMLAB been facing in the COVID-19 world?Lendermann: Obviously, software delivery projects have become more challenging for the time being since our engineers cannot be on-site frequently. But it also turned out that more and more services can be delivered remotely, which has the nice side effect of making the services more cost-effective for customers. Overall, we are confident that our solid customer base will enable us to sail steadily through these challenging times.Ng: Where does D-SIMLAB see the technological development heading?Lendermann: In the future, enriching decision support and manufacturing execution solutions with machine learning and other AI techniques will be critical in reducing dependency on human experience. This path is essential to making manufacturing operations fully Industry 4.0-compliant. D-SIMLAB will certainly be at the forefront of this development. Bee Bee Ng is president of SEMI Southeast Asia.

Not long after STMicroelectronics opened its first semiconductor plant in Singapore more than 50 years ago, a facility chiefly focused on chip assembly and packaging, the company realized that it had constructed the site in an area with a blossoming chip ecosystem with a bright future. Before long, the company became the first to start a wafer fab facility in the so-called Little Red Dot. Today, our STMicroelectronics Singapore campus sports several buildings that dwarf the original site in the sprawling Ang Mo Kio Industrial Park 2. The facilities feature advanced 200mm manufacturing lines but still produce huge volumes of chips with more than 1,000 pieces of 150mm manufacturing equipment.Much of the wafer equipment dates back to the past century so is no longer supported by the manufacturers, if they’re still even in existence. Yet decades later the chipmaking gear continues to operate with a surprising reliability that far surpasses the longevity called for in its manufacturing specifications thanks to replacement parts and frequent upgrades with more sophisticated handling robots and chucks. Now, as smart manufacturing begins to establish a foothold in the semiconductor industry, Industry 4.0 technology is breathing new life into these aging workhorses.Despite its age, all of the equipment adheres to industry manufacturing standards. The gear is remotely controlled using the SECS/GEM interface protocol that was either originally integrated with the equipment controller or custom-made. We’ve also maximized its usage through advanced recipe management, advanced alarm and event handling, and secured lot identification.Crucially, we decided to systematically deploy a real-time fault detection and classification (FDC) solution using a third-party product based on what today is known as an edge computing architecture. Every piece of critical processing equipment is progressively paired with its dedicated FDC instance running on a virtual machine in the wafer fab data center, and the FDC solution monitors vital equipment parameters at high frequency – depending on the SECS/GEM capabilities of the equipment – and analyzes incoming manufacturing data in real time using classic SPC (statistical process control) algorithms and even AI-class protocols.Our use of the FDC edge solution as a sensor signal aggregator has given our equipment a second life. The solution processes real-time signals from sensors connected through a typical TCP-IP. Sensors have been the old equipment’s saving grace with their ability to de-multiply equipment capabilities and overcome fundamental shortcomings and design weaknesses. The STMicroelectronics Singapore plant first used off-the-shelf sensor nodes with built-in power amplifier and analog input nodes. While very practical and easy to implement, deploying the nodes can be costly. After developing more expertise in sensor integration using FDC, our wafer fab equipment experts decided to design an in-house solution based on the famed STM32 microcontroller. Leveraging Arduino – an open-source electronics platform with easy-to-use hardware and software – the equipment teams can now design and program a variety of in-house sensors for measurements including temperature, humidity, waterflow and pressure. The sensors are integrated with process equipment using the FDC solution. Integrating the sensors with the FDC engine on the edge computer extends the capabilities of old equipment without jeopardizing the integrity of the machines themselves. While the integration can be quick, it must be robust to ensure the reliability of the new measurements. Similarly, ever-increasing connectivity requirements present clear cybersecurity risks that must be managed upfront and each solution must be hardened to minimize security vulnerabilities. Even so, the challenges and risks pale in comparison to the benefits! Jean-Marc PHILIPPE is DIT Director at STMicroelectronics Pte Ltd. He oversees the deployment and support of Digital Solutions to enable STMicroelectronics front-end operations in Singapore and manages manufacturing productivity and automation programs at site level.

I recently spoke with Chan Pin CHONG, Executive Vice President and General Manager of Products and Solutions at Kulicke Soffa, about how smart manufacturing is driving new production efficiencies in the semiconductor industry. During our conversation, he also provided practical steps for factory operators to follow in evaluating their smart manufacturing needs in order to ensure successful implementation and discussed the potential payoffs. Based in Singapore, Kulicke Soffa is a leading global provider of ball bonding, advanced packaging, wedge bonding, and electronic assembly equipment for the semiconductor, power and automotive industries.Ng: Industry 4.0 and smart manufacturing are critical to the growth of the semiconductor industry. What does the smart manufacturing movement mean to you or Kulicke Soffa?Chong: The future of smart manufacturing is the vision of building a digital connected factory to drive new manufacturing efficiencies by combining physical and cyber technologies. Industry 4.0 integrates discrete systems and harnesses the power of large volumes of data to move towards greater automation.At K S, we define smart manufacturing across the following four key areas embedded in our roadmap for all K S products, from wire bonders and advance placement tools to pick and place machines: Interoperability – This is about machines, devices and sensors connecting to each other. In fact, the very basis of smart manufacturing is that all devices are connected. Information transparency – Through simulation, various artificial intelligence (AI) tools use contextual information to emulate the actual world. Technical assistance – Robots or machines support humans in making decisions or solving problems. Autonomous decision-making – This is our vision that robots or machines can learn from machines to make decisions on their own. Ng: Please elaborate on some of these areas and how they’re the relevant to smart manufacturing. Chong: The need for machines, devices and people to communicate with each other forms the basis of connectivity, the idea of all machines communicating with each other or a host. Connectivity protocols now in place for machine-to-machine connectivity include SEMA, SECS/GEM, SEMI-ELS and IPC-CFX. Machine technology uses various sensing technologies. For example, for a pick and place machine such as SMT platform on K S Hybrid, the algorithm to recognize and align processes is part of the sensor needed in each machine before to can process and add thousands of components to the substrate or panel. In a wire bonder, the ultrasonics or EFO signal can provide some form of sensing technology for a machine to detect process conditions. Importantly, these sensing technologies can be used to collect feedback for process improvements.One example of how K S machines are connected to the host is our use of an intermediate server or host named KNeXt to connects to all assembly equipment in the fab. The equipment can then, in turn, connect to an external secured cloud or K S Global Cloud.Ng: What are the objectives for smart manufacturing?Chong: The ultimate goal is to achieve higher factory productivity or better OEE (Overall Equipment Effectiveness) by improving machine yields, productivity and efficiency. The key is to leverage AI, 5G, the Internet of Things (Iot) and other industry 4.0 technologies to drive automation and process improvements. Ultimately, each factory must meet productivity, yield and cost goals. Smart manufacturing enables factory operators to meet these goals. That is the focus of smart manufacturing.Ng: What is the biggest potential benefit of smart manufacturing?Chong: Smart manufacturing uses data to predict outcomes of a process step or machine operation. Once data is available in the global cloud, analytics can start to build data sets to run statistical modelling and examine factory operation trends. We can also use the data to identify past machine behaviors in order anticipate outcomes, including undesirable ones that we can then prevent.In the SMT example, if we can systematically examine days or weeks of historical performance, we can plot some statistical variations in the process specifically to a pick or placer or a robot and anticipate or avoid problems. However, all sensors must be in place in the bond head or the robot so that we can detect changes or variations in the robot’s movements.Kulicke Soffa smart manufacturing facility Ng: What are some recent factory improvements smart manufacturing has enabled? Chong: Kulicke Soffa has contributed to the hierarchical architecture of the smart factory and key technologies. COVID-19 is driving demand for greater factory connectivity, and K S offers solutions that are key to remote management and full control of smart equipment from a central control and embedding Internet of Things (IoT), big data, cloud computing and sensors in manufacturing. Using these technologies, a small smart factory can be remotely operated and managed.With COVID-19 limiting air travel around the world and access to support engineers, the need has grown for remote machine access to reduce the downtime per machine. Remote factory access enables off-site engineers to remotely identify and diagnose machine problems.Ng: What are barriers to faster adoption of smart factories?Chong: While most smart factories are capable of network connectivity and data collection, a key challenge is the lack of a business model for smart factories and smart equipment. Most factories must justify major capital investments by demonstrating ROI (Return of investments) potential. Capital improvements for every factory usually take several years to implement and are based on a complex business model. Factory connectivity requires substantial investments and years to implement. The same is true of the cloud infrastructure buildouts necessary to generate big data and meaningful analytics. The executive mandate for factory management to install capability usually calls for specific business targets in the planning stage.Another longstanding barrier to entry is the lack of compatibility of existing tools with new factory protocols, raising the question of whether the cost of replacing legacy tools justifies the need for a smart factory. If new factory investment is required for the latest tools to support the production of new products, the ROI will be much easier to justify.Ng: How is AI is important in smart manufacturing?Chong: AI interprets and learn from data to perform tasks and meet specific goals. Good examples of AI implementations include Amazon’s Siri and Alexa voice-command devices and self-driving cars being developed by Google and Tesla.At K S, over the years we’ve implemented AI in our smart wire bonders to reduce human intervention in our ProCu-7, PSP-2, ProCu Loop 2, Pro Bump and overhang processes.Thanks to AI, with senses of signals from the bonder, we can reduce the amount of parameters that an engineer or technician have to do trial and error. With on bonder metrology, PBI, loop height, wire sway features, AI allows us to measure process efficiency and provide feedback.Over several years of AI development, we have leveraged the technology to monitor machines and provide real-time performance feedback in order to provide better closed loop control such as short tail recovery in our bonder process. We can also use the data to predict machine behavior, monitor its health and track maintenance. Ultimately, AI enables fabs to improve manufacturing efficiency, productivity, yields and device quality.Ng: What’s an example of how AI has solved your manufacturing equipment problems?Chong: We’ve used AI to set RPM (real time monitor) limits, identify defective P-parts and monitor various conditions such as wire size and capillaries. These types of cases can arise in any manufacturing environment as humans make process mistakes or use the wrong part for a machine. With AI, we can prevent these problems and reduce the risk of further material lost from the wire bonding process.Ng: What advice do you have for factories looking to implement smart manufacturing systems?Chong: To build a smart factory, start by focusing on a clear set of business objectives and how smart manufacturing will help minimize or eliminate current factory inefficiencies. In other words, start with the end in mind – the problems that needs to be solved and the business goals – and identify the information you need to demonstrate ROI. Do you need to resolve, automate or improve processes or just to be more efficient? Before investing millions or billions of dollars to build a smart factory, identify those clear goals upfront. Then map out the particulars of implementation to avoid major problems around standards, protocols and connectivity.Bee Bee Ng is president of SEMI Southeast Asia.

Teck Khiong, WOI, senior manager of Factory Integration at Infineon Technologies Asia Pacific Pte Ltd, recently shared with me how the Infineon backend plant in Singapore has benefited from its journey to qualify for the lighthouse certification.WOI is driving Infinion smart manufacturing projects with a strong focus in the area of connect and control using IoT (Internet of Things) and analytics technologies. Ng: How did the Infineon backend plant in Singapore distinguish itself to qualify for lighthouse certification? WOI: The Infineon Singapore backend manufacturing plant is proud to be a Lighthouse Certified Smart Manufacturing site as part of the World Economic Forum’s (WEF) Fourth Industrial Revolution platform. Our Industry 4.0 (I4.0) implementation reduces labor costs by 30% and improves capital efficiency by 15%. We drove this successful digital transformation continuously investing in our people development and digital backbone.Of the many initiatives under our I4.0 Smart Factory platform, five were selected for WEF Lighthouse submission and certification. Digital foundation with integrated connectivity and workflow execution We implemented an Internet of Things (IoT) framework to connect machines to manufacturing system more than two years ago. The digitization of our Work-in-Progress (WIP) management systems provides full traceability and gives us better control of the four Ms (Man-Machine-Method-Material). Material handling and process automation We progressively deployed automated solutions starting six years ago using autonomous transport, robotic material management systems and automation of packing processes. This eliminated non-value touches in areas of WIP storage and retrieval. Advanced algorithms enabled WIP scheduling and dispatching As our product mix and volume grew in complexity, our advanced algorithms has enabled us to increase our machine uptime, thus reducing idle and set-up time. Manufacturing control tower Our control tower provides a real-time pulse of the entire manufacturing process, from machine efficiency to quality. The tower also improves data integrity and collaborative information sharing while issuing early-warning alerts that enable exception management and timely decisions. Running a global virtual factory Our Global Production Network deployments allows us to connect and manage a growing contract-manufacturing network in real time, with the same transparency, traceability and control as if the manufacturers are our internal sites.About Teck Khiong, WOITeck Khiong, WOI graduated from Loughborough University in the UK with a Master of Science degree in Computer Integrated Manufacturing (CIM). For more than 20 years he has delivered manufacturing IT solutions to global backend (assembly and test) semiconductor manufacturing, ranging from equipment, factory, process control, material handling automation and manufacturing execution systems (MES).

Making Strides TogetherKnowledge is power – especially when it is shared. This principle formed the foundation for Micron’s Go and See virtual visit of its Singapore manufacturing plant on 26 August 2020 as 27 companies including GLOBALFOUNDRIES, ST Microelectronics, Infineon, TEL, ViTrox , IBM, HP and UTAC joined the first-of-a-kind virtual factory visit. The chip industry powerhouses gathered to see how Micron’s Lighthouse frontend wafer fabrication facility leverages Fourth Industrial Revolution technologies to drive new production and cost efficiencies.They saw clear markers of a transformed organisation and spoke with working-level staff, managers and front-line employees. Company representatives also met virtually with Micron management teams from organisations that led its digital transformation – from pilot programs to integration at scale – to realise significant financial and operational benefits. The mix of technologies they deployed to make it all happen included artificial intelligence (AI), big data analytics and the Industrial Internet-of-Things (IIoT).Micron’s Singapore-based fab facility earned Lighthouse certification earlier this year from the World Economic Forum’s Global Lighthouse Network. The Go and See tour was co-sponsored by SEMI Southeast Asia and McKinsey Company.Transformation is CrucialBy embracing Lighthouse principles, semiconductor sectors and companies can accelerate their digital transformation to boost operational and financial efficiency while helping increase productivity across the electronics supply chain. It will take time for Southeast Asia semiconductor manufacturers to transform to digital operations, though we’re seeing growing interest in Industry 4.0 practices as they begin to understand that the deployment of new technologies and applications will help them better understand real-world benefits of smart manufacturing use cases and solutions. SEMI believes shining the spotlight on companies like Micron can illuminate the way forward for other companies to help drive the industry’s digital transformation. We look forward to seeing companies build on this momentum as they start to leverage leading-edge technologies to improve efficiencies and promote sustainability.Bee Bee Ng is president of SEMI Southeast Asia.

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.

Gursharan Singh, Micron’s senior vice president of Global Assembly and Test, spoke with us about the progress of Micron’s new facility in Penang, the company’s smart manufacturing advancements, its ongoing initiatives to hire and develop talent, and its support of the greater Malaysian community during the COVID-19 pandemic. Micron to Open Center of Excellence in PenangMicron’s 52.6-acre Center of Excellence for SSD assembly and test in Batu Kawan Industrial Park in Penang is slated to open in early 2021. Micron is investing RM1.5 billion over the next five years and has committed to adding 1,000 team members.“In parallel to the building’s construction, we have built a temporary site in Seberang Prai where nearly 1,000 of our team members have already set up the production line for SSD,” Singh said. “Once the new plant is ready, this operation will be moved to Batu Kawan, giving us the advantage to ramp up production and hit the ground running without the lag of waiting for the operationalization of a new facility.”Malaysia to Gain From Micron’s Global Manufacturing NetworkMicron’s commitment to Malaysia extends beyond business investments. As an industry powerhouse, Micron’s Malaysia operations will tap into its global expertise and best practices.“Malaysia is in a unique position to benefit due to its close proximity with our NAND Center of Excellence in Singapore,” Singh said. “We are learning from our factory in Singapore, which implements the latest advances in smart manufacturing, as we develop the facility in Batu Kawan. Those lessons will be used to ensure that new technologies are deployed cost-effectively and push the envelope to get them to the next level.”On the talent front, Micron is creating a pipeline of local Malaysian talent from a young age. This means driving multiple STEM initiatives targeting local primary and secondary schools and includes a Women in Science and Engineering Program we’re offering at 39 of Penang’s secondary schools. We’re also creating internships for engineering degree holders through the company’s Industry Student Engagement Program (ISEP) and continuing a training program for young diploma holders held in conjunction with Penang Skills Development Centre (PSDC) to give them skills that are required by the industry.Our workforce development initiative also gives Micron an opportunity to work with young talent new to the industry so they can learn and undergo in-depth industry training from more experienced peers."We use our global network of expertise to train young workers and give them the opportunity to learn and participate in this start-up-like environment,” Singh said. “We have already hired nearly 40 new college graduates from Universiti Sains Malaysia (USM). Our game plan is to continue on this path by hiring a higher percentage of local graduates and giving them access to our facilities to learn our technology and advance our Malaysia facility. More than that, we hope our collaboration with local universities can extend further into high-impact research initiatives that benefit the wider community."Micron’s Commitment to Malaysia’s Communities During the COVID-19 PandemicMicron is investing in the greater Malaysian community as the country fights the current COVID-19 pandemic. Malaysia is one of five countries prioritized to receive grants from Micron’s $35 million global relief fund. The company recently announced a RM2.6 million donation from the Micron Foundation that will help the three groups most in need – front-line workers and hospitals, children and the elderly in charitable homes, and underprivileged families in Muar and Penang near its facilities. The goal is to quickly distribute aid such as medical and personal protective equipment, food and household items, and financial assistance.In addition, Micron is supporting its Malaysian employees by making a one-time assistance payment of RM1,300 to 94% of its workforce based in Muar and Penang. This is the percentage of the workforce meeting the eligibility criteria.Designated as an essential services provider by the Malaysian government, Micron continues to maintain its local operations. Micron products built in Malaysia are critical to helping the world effectively cope with COVID-19. Our technology enables advanced medical devices for treatment, data centers and supercomputers used by scientists to find new solutions, and e-learning and videoconferencing capabilities that connect the world during this period of restricted movement.Sangeeta Rajgopal is Head of Country Communications Marketing, Singapore Malaysia Global Communications Marketing, Micron

Automotive original equipment manufacturers (OEMs) and their direct suppliers of parts and systems share a vision: Next-generation vehicles will be more electric, autonomous and connected. At a market size of more than $1 trillion, automotive is steadily becoming a high-tech market as cars morph into advanced technology platforms with partially or fully autonomous features. Call them semiconductors on wheels. Big players such as Google and many carmakers are investing heavily in chip advances to help drive increases in silicon content in automobiles.At SEMICON Europa, Pierrick Boulay, Solid State Lighting and Lighting Systems analyst at Yole Développement, will provide a market update on autonomous automobile trends including the state of sensors, radars, cameras and LiDARs as the industry works to increase the level of autonomy and electrification.Autonomous vehicle design can only thrive with the development of an industry standard for chip and device traceability across the supply chain. The importance of chip traceability to the automotive industry is reflected in its central role in driving a chip traceability standard.According to Heidi Hoffman, senior director of technology communities marketing at SEMI, “chip traceability is one of the next big things for the technology industry. The benefits are enormous, and the upsides – including yield enhancements, counterfeiting safeguards, and support for new applications – are plentiful. But the implementation challenges of chip traceability are also big and will require considerable effort to overcome. The biggest hurdle of all? We need to transcend industry fears by demonstrating that we can secure IP when it is shared across the hardware supply chain.” The Importance of Standards, Data Collection and Collaboration Across the Supply ChainThe automotive industry has long embraced tracing the sources of defects. Now, as the automotive and semiconductor supply chains increasingly overlap, traceability has taken on greater importance in the semiconductor industry. SEMI committees, task forces and events such as the Smart Transportation Forum at SEMICON Europa are ideal platforms for collaborating to develop new standards and best practices for the automotive industry.Earlier this year, German luxury automobile maker Audi AG became the first automotive original equipment manufacturer (OEM) to join SEMI as member, strengthening alignment across automotive supply-chain segments. At SEMICON Europa, the SMART Transportation Forum and Pavilion, staged by the SEMI Global Automotive Advisory Council (GAAC) and bolstered by the Electronic System Design Alliance, a SEMI Strategic Association Partner, will gather key stakeholders across the automotive value chain, from design and semiconductor equipment to materials and carmakers, to explore innovation opportunities in automotive electronics. SEMI Global Automotive Advisory Council (GAAC) “If the industry wants to reach the goal of zero defects, a new collaborative approach is necessary,” observed Antoine Amade, senior regional director EMEA at Entegris. At SEMICON Europa, Amade will present new ways to collaborate in reducing chip defectivity and meet other challenges in the automotive industry.More than half of semiconductor failures on the automotive assembly line today (so-called 0km failures) are traced to semiconductor fab defectivity. “The increasing semiconductor content in automobiles – driven by growth in ADAS, electrification and autonomy – has put a growing focus on the quality and reliability of these devices and their implications for consumer safety and satisfaction,” said Oreste Donzella, senior vice president and CMO at KLA.The smart manufacturing (Industry 4.0) revolution is already spurring higher performance and great efficiencies throughout the supply chain and will also be crucial to driving innovation in automotive. Smart manufacturing makes possible significant improvements in factory key performance indicators (KPI) for cycle time, on-time delivery, overall equipment effectiveness, cost and product quality.“These KPI gains are key to meeting quality levels the automotive industry must reach to support the deployment of autonomous driving vehicles,” said John R. Behnke, general manager of Final Phase Systems at INFICON. In his talk at SEMICON Europa, Behnke will provide an overview of existing, in-progress, and future smart manufacturing solutions for the semiconductor industry and their impact on the automotive supply chain. The SMART Transportation Forum, 13 November, 2019 (9:30-15:30 at ICM Munich, room 14c) at SEMICON Europa is the premier platform for key stakeholders to connect, collaborate and innovate across the automotive value chain. Automotive and semiconductor industry experts will offer insights into trends in design, semiconductor equipment and materials, and automotive innovation and the roadmap to 2030. The SMART Transportation Forum will also showcase innovations in imaging, sensing, artificial intelligence (AI), smart manufacturing and L5 mobility.Other SEMICON Europa highlights: Advanced Packaging Conference: Packaging and Test Challenges Towards High Reliability (12-13 November 2019) 23rd Fab Management Forum: Game Changers for Semiconductor Operations(11-12 November 2019) Strategic Materials Conference: Strategic Materials Enabling Industry Roadmaps(12-13 November 2019) SEMICON Europa registration is open for visitors and exhibitors. For more details, please visit the SEMICON Europa website and connect with SEMI Europe on Twitter or LinkedIn @SEMIEurope (use #SEMICONEuropa).Learn more about the SEMI chip traceability standard – SEMI T23 - Specification for Single Device Traceability for the Supply Chain – and SEMI Technology Communities.Serena Brischetto is a marketing and communications manager at SEMI Europe.

Imagine a world where there are chips in about everything we touch on a daily basis. It is not hard to do with semiconductors already at the core of many leading-edge electronic devices. These sophisticated chips are hidden from sight, but their functions are vitally significant to our daily lives.Manufactured in multibillion-dollar facilities, the production process of chips is one of the riskiest, costliest, and most technically complex feats in business. Consider the difficulties of managing contaminants during device manufacturing: A single speck of dust on a lens could cause the entire output of the plant to be scrapped.For years, these exotic fabrication facilities, called fabs, have been packing more efficiency into ever smaller chips. As new technologies continue to emerge, chip manufacturers face constant pressure to continually refine and improve their operations to meet the challenge of rising device performance and yield goals. Fab managers must optimize tool performance, improve fabrication techniques, safely handle toxic materials and design better integration flows. Layer on top of those requirements customer demand for greater innovation and quality of service, it can be difficult for manufacturers to handle everything on their own while consistently meeting necessary requirements.Align for CollaborationWith the help of the Fab Owners Alliance (FOA), a SEMI technology community, manufacturers and their suppliers don’t have to travel this road alone. Membership in this international group allows semiconductor and MEMS fab managers and industry suppliers to come together to solve common non-competitive manufacturing issues and improve business results.Founded in 2004, the group consists of 25+ device manufacturers (DMs) with over 120 semiconductor manufacturing facilities and 60+ solution providers (SPs) who supply equipment and services. Through quarterly meetings, study teams, benchmarking surveys, case studies and online forums, FOA successfully provides a collaborative, non-competitive platform to the fab management and operations community. FOA members enjoying an engaging discussion and networking event during the recent Q1 2019 Collaborative Forum at the Double Tree Resort in Scottsdale, Arizona One of the most popular FOA platforms is the annual Collaborative Forum early in the year. The goal is to bring together DMs and SPs from around the world for an open dialogue under one roof. For two days, they share success stories and discuss issues facing their fabs and the industry in general and develop collective strategies to address them.The success stories are particularly engaging as they accentuate the value and benefits of FOA membership. Presented as case studies, these stories outline how the DMs and SPs work together to improve fab efficiency and increase yields. Often, the ideas for the case studies are conceived during networking events, fab tours and programs organized by the FOA.The case studies shared at the 2019 Collaborative Forum, held at the Double Tree Resort in Scottsdale, Arizona, February 13-14, 2019, illustrate the power of collaboration within the FOA. Following are a few examples.Scheduling System Implementation Broadcom was facing a steep ramp when it decided to engage with FPS, an INFICON product line. In addition, the manual decision making, and limited real-time visibility of factory data was negatively impacting their production in its 150mm and 200mm environment. By deploying an integrated Smart Manufacturing software solution and its digital twin, FPS was able to retrofit Broadcom’s manual factory with automated decision-making capabilities.This solution offered many benefits. Constraint tool utilization increased by more than 15 percent. The automated WIP management system also eliminated many manual wafer handling issues such as lost lots, WIP storage constraints, building transfers, and time spent looking for lots. Pushing Tool Performance BoundariesAs tools in the 200mm space are hard to find, GLOBALFOUNDRIES is always looking to squeeze every wafer out of its existing resources. To drive continuous improvement and increase equipment throughput, GLOBALFOUNDRIES leveraged MAX’s knowledge with Machine Rate Models. Together, they were able to employ a modelling technique that helped them model key toolsets and develop actions to increase intrinsic machine rate performance.Based on this knowledge, 10 capacity constraints were selected, and speed models were developed for all of them. This win-win collaboration allowed GLOBALFOUNDRIES to find some real opportunities that translated into CAPEX and cost savings. On average, the companies identified a 12 percent potential improvement opportunity per toolset and created engineering task force teams to prioritize and drive the improvements.Simplifying the Chamber Matching Process Using Trace AnalyticsThe collaboration between NXP and BISTel resulted from a shared vision of achieving Smart Manufacturing using analytic solutions enabled by artificial intelligence and other advanced technologies. Chamber matching is critical in identifying process variation to ensure manufacturing quality. Traditional tools like Fault Detection Classification (FDC) often do not provide clear enough insights to pinpoint the issues and require extensive time to collect data from each chamber.Through several use cases, NXP and BISTel successfully illustrated the effectiveness of using a trace analytic solution to quickly and accurately quantify and monitor chamber-to-chamber mismatches as well as changes within a chamber over time. The full trace analyses of all parameters allowed NXP to generate better FDC models to more quickly detect similar issues in the future. In addition, NXP was able to identify the cause of a parametric shift by comparing performance of the same chamber between two different time periods. All in all, the trace analytics solution brought together and analyzed the process data efficiently, thereby reducing analysis time from days to minutes.Eagleview Inspection of SiC and Transparent Wafers X-FAB challenged Microtronic to develop a new capability for its high-throughput recipe-less macro defect inspection systems. Microtronic’s EagleView machine vision macro defect inspection system is well known for its versatility in the semiconductor industry due to its wide deployment as well as its recognition as winner of the 2017 Best of West Award at SEMICON West. But X-FAB’s requirements to inspect and image transparent wafer substrates were novel. After working closely to understand X-FAB’s needs, Microtronic made extensive hardware and software enhancements to enable high-throughput macro inspection of Silicon Carbide (SiC) and other transparent wafer substrates.Get InvolvedThe FOA meetings are held at device manufacturing sites twice a year. The next meeting will be graciously hosted by MACOM in Lowell, Massachusetts, May 22-23, 2019. The DMs and SPs will meet again at SEMICON West at the Moscone Center in San Francisco on July 11, 2019.To attend these meeting and be part of this high-impact group, please email us at [email protected]. For more information about FOA, please visit our website.Nishita Rao is a marketing manager at SEMI.