AI

SEMICON Korea 2023 showcased the latest developments in high-priority areas including sustainability, smart manufacturing, advanced chip technologies, and workforce development. Keynotes by semiconductor leaders AMD, imec and Lam Research on critical chip industry trends.

In the span of a few short months earlier this year, Mentor Graphics became Siemens EDA and introduced a suite of integrated hardware-assisted verification tools, the first product launch under the new Siemens EDA brand. Jean-Marie Brunet, senior director of marketing, product management and product engineering at Siemens EDA, orchestrated the launch and connected with me for a discussion about the chip design verification space. As he pointed out, verification and validation of systems is a fast-growing and important market segment to the electronic system design ecosystem. Smith: What trends do you see in chip design? What is driving these trends? Brunet: Chip verification costs continue to grow faster than design costs because of factors such as increasing design complexity, rising computing power, surging I/O traffic activity, increasing energy consumption and the widespread use of peripherals. These dynamics are being driven by new data center networking, communications/5G, autonomous driving, artificial intelligence (AI) and machine learning (ML), and storage applications. These trends also indicate the need for more powerful verification tools and expanded verification objectives that include power and performance analysis. Hardware-assisted verification tools are perfect for meeting these demands. Smith: Chip design verification consumes the most time in a project cycle. Why is this so? Brunet: The verification of designs reaching multi-billion gates and supported by voluminous software stacks is fraught with challenges. To exhaustively check every possible state in a billion-gate design with simulation alone would require up to trillions of verification cycles. That’s why hardware-assisted verification is one of the fastest-growing technologies in EDA. Given the complexity of today’s SoC design, it’s no surprise that verification is the largest undertaking in the entire project design cycle, consuming more than 50% of it. It also has the greatest impact on quality, cost and schedule because it prevents designs from failing at first silicon. While a respin of a large design taped out at a node below 10 nanometers could cost more than $10 million, delaying delivery of a new product for a few months in a highly competitive market may cost hundreds of millions of dollars. Smith: What other challenges do engineers face trying to verify a chip design will work as intended? Brunet: Verifying an SoC design is a massive undertaking and, in parallel, verification teams are trying to streamline and optimize verification cycles. SoC design groups are tasked with completing full system-level verification prior to creating production masks by thoroughly vetting all hardware blocks, interactions between those blocks, and the software developed for the end application before the chip is built. To alleviate this enormous pressure, they are starting to adopt a shift-left methodology for early functional verification as soon as individual blocks of a SoC design become available. It helps jump-start embedded software validation before full system validation is completed to save time and allow engineers to work in parallel, not serially. While it is an effective approach, it creates the need for a complete and integrated suite of hardware-assisted verification tools to verify and validate a design’s hardware and software components. Smith: How do you define hardware-assisted verification and how does it help solve these challenges? Brunet: A typical definition of hardware-assisted verification is special purpose hardware to accelerate verification. In other words, hardware emulation and FPGA prototyping. Hardware-assisted verification is a mandatory investment as single-die or multi-die chips get larger with more complexity and more interfaces, making hardware and software code integration critical early in the design cycle. Because software performance defines a chip’s success, the need to perform software workload-based analysis is acute, not just analysis of chip functionality, but also accurate performance and power consumption in the context of real-world applications. Hardware-assisted verification is the only option when hardware and software meet. By combining emulation, desktop FPGA prototyping boards and enterprise FPGA prototyping platforms to work on the same SoC design, a verification group can assemble a complete hardware-assisted verification system for thorough and exhaustive verification and validation. Smith: Where are the big opportunities for hardware-assisted verification? Brunet: New end-user applications are coming from computing and storage, AI/ML, 5G, networking and automotive. Recently released market data from the ESD Alliance shows that in 2020, hardware-assisted verification revenues exceeded $700 million. It is reasonable to assume that revenues of $1 billion will be within reach in the next few years given the amount of chip design activity at advanced nodes below 10nm. Smith: With the design/verification and manufacturing phases of the semiconductor supply chain more closely aligning, what role does hardware-assisted verification play? Brunet: Semiconductor manufacturing and the supply chain that supports it benefits greatly from the continued innovation in verification and validation tools and methodologies. With this innovation, designs are delivered to the manufacturing flow with a much greater chance of passing first silicon with success. This reduces friction in the semiconductor supply chain since IP and chips are available when anticipated. Hardware-assisted verification is a quick-moving, highly leveraged resource that helps a design and verification team to ensure chips are manufacturable and meet the functionality, power and performance requirements for the end-product application. Jean-Marie Brunet is the senior director of product management and engineering for the Scalable Verification Solutions Division at Siemens EDA. He has served for over 20 years in application engineering, marketing, and management roles in the EDA industry, and has held IC design and design management positions at STMicroelectronics, Cadence, and Micron, among other companies. Jean-Marie holds a Master's degree in Electrical Engineering from I.S.E.N Electronic Engineering School in Lille, France. Jean-Marie Brunet can be reached at [email protected]. About Bob Smith Robert (Bob) Smith is executive director of the ESD Alliance, a SEMI Technology Community. He is responsible for the management and operations of the ESD Alliance, an international association of companies providing goods and services throughout the semiconductor design ecosystem.

The adage “the only thing constant is change” has never been more universally applicable than this past year – across the globe, across industries, across buyers. All manner of ways in which we work and consume has changed and continues to change, driving innovation, disrupting industries, and transforming buyers’ behavior. To survive, companies must follow the old adage: to remain a constant, they must change. Overnight, we shifted to work-from-home, and, after a few days to adjust and align, we discovered surprising benefits. By working remotely, we gained time by losing our commute, and we increased exponentially the number of meetings we could hold – and the number of people we could meet with – in a typical business day. Executives, customers, and decision makers were suddenly more accessible, and we could share a ‘face-to-face’ call in far more intimate settings, allowing us to meet family and pets, which in turn deepened relationships. Beyond productivity and a healthier work-life balance, remote work obliterated any constraints of geography, enabling companies to consider employees across the country and globe, thereby expanding talent pools, creating retention opportunities, and bolstering diversity efforts. Now, despite the easing of restrictions, published studies and employee surveys (even our own annual Tell Dell survey) show that many employees want and expect to continue to work remotely at least part-time. No surprise there, but it is important to note: These changes in preference and expectation are not limited to how we work; They apply to every aspect of our lives. In 2020, with never-before-seen speed, we adopted distance learning, telehealth, online entertainment, 3D printing of PPE, online grocery/restaurant orders, and digitally-enabled deliveries and curbside pickup – and we aren’t going back. Just like employees now prefer the flexibility of work-from-home, buyers now prefer – and expect – the flexibility of shop-from-home. While these changes were in progress well before 2020, the pandemic accelerated and normalized adoption, and now buyers approach business decisions with the same preferences, expectations, and behaviors of consumers. In fact, according to Gartner, by 2025, 80% of B2B sales interactions between suppliers and buyers will occur in digital channels.[1] Buyers have already embraced online research and digital buying. They expect authentic, personal experiences and relationship-driven online interactions. Like the consumers they are at home, B2B buyers are researching online well before they engage with a person. To survive, companies must meet customers where they are and how they want to buy: online. For marketing and sales, the handoffs have changed. In marketing, our messaging and content is touching decision makers and potential customers far before they meet with a sales rep. Enabled by artificial intelligence (AI) and enhanced analytics, sales teams will need to follow the data, and be ready to respond to buyers’ needs at the exact time they realize the need. At Dell Technologies, we have not only embraced this digital transformation change, but we are also leveraging marketing automation technology to help our partners learn and activate digital marketing and selling. We are training our sales and marketing teams while also providing enablement, training and support to enable our partners to navigate the new buyer’s experience. Our teams are organized to move quickly and lead through change so, together with our partners, we can address the ever-changing needs of our customers. Are you and your team ready for this change? Do you have the digital skills needed to adapt? Are your organizations agile and open to new ways of working? Do you have the right leaders in place to lead through change? Your buyers are in the driver’s seat: They determine if, when, and how they interact with suppliers. Are you in the right place at the right time to meet your customer if, when and how they want? To remain a constant – to remain in business – you need to embrace the change in your buyer and embrace the technology available to meet your buyers where they are – online. Join me July 13 at my session Digital Leadership – Embracing the Buyer Evolution at the SEMI Innovation for a Transforming World virtual event to learn more. Senior Vice President at Dell Technologies, Cheryl Cook spearheads development and strategy for the Global Partner Marketing organization. Beyond her main global responsibilities for branding, partner program marketing, channel events, partner communications, and MDF/BDF program investments and execution, Cheryl drives long-term partner marketing strategy, together with Dell’s Global Alliances, OEM, and global and regional business teams. A vocal advocate for the partner community, Cheryl is a 20+ year partner veteran, known as an innovative, collaborative leader who creates compelling business solutions that accelerate partners’ success. [1] Gartner Press Release, Gartner Says 80% of B2B Sales Interactions Between Suppliers and Buyers Will Occur in Digital Channels by 2025, September 15 2020.

SEMI spoke with Eyal Shekel, senior vice president of Service Strategy and Excellence at Tokyo Electron Limited, about the impact of artificial intelligence (AI) on smart manufacturing and how other fab solutions for smarter process tools are advancing semiconductor manufacturing.Eyal shared his views ahead of his presentation at the SEMI Fab Management Forum, 17 February, as part of the SEMI Technology Unites Global Summit, 15-19 February 2021, an online event. Join us to meet experts from Tokyo Electron and other key industry influencers. Registration is open. SEMI: AI technology is considered a key enabler for smart manufacturing. What are the latest trends? Shekel: The advent of advanced nodes and extreme complex 3D semiconductor geometry has lengthened time to market and increased costs in areas ranging from equipment development and large-scale metrology usage to monitoring yield inhibitors.AI is becoming a critical tool in the area of material informatics to determine suitable materials and processing techniques in order to meet the needs of future devices. Together with new materials and processes, the development and implementation of virtual metrology will enable accurate and almost absolute real-time monitoring of our customers’ device wafers at each stage of the manufacturing process.SEMI: What are the benefits of data analysis in the process from R D and Ramp-Up to High-Volume Manufacturing? Shekel: The new research field of materials informatics enabled by AI provides tools to guide the highly efficient discovery and optimization of production processes. For example, TEL has developed methodologies for co-optimizing processes and materials for etch rates.To monitor and manage the yield of semiconductor fabrication processes, direct metrology measurements are important. However, it is difficult to monitor all production wafers due to the time and cost involved. With deep learning AI, it is now becoming possible to predict every wafer’s metrology measurements based on production equipment data and previously processed wafer metrology variables. This enables total quality management and run-to-run control, while simultaneously reducing production costs and cycle time.SEMI: Can you tell us more about TEL Service Advantage?Shekel: TEL Service Advantage is a TEL global support organization that allows customers to select a service plan that fits their needs. Through TEL Service Advantage, we can quickly respond to customer requests and technical advancements. TEL Service Advantage provides various plans to maximize equipment maintenance efficiency for customers and productivity from equipment manufactured by TEL. TEL Service Advantage plans can be combined to meet customer needs and achieve maximum results.A key enabling element of TEL Service Advantage is TELeMetrics™. TEL analyzes equipment data from various sensors using a remote connection and, based on that analysis, provides solutions to customer-specific problems around equipment throughput and predictive maintenance.SEMI: How is AI helping during the pandemic? Can you share a success story? Shekel: The pandemic forced severe travel restrictions worldwide, making it very difficult or even impossible in many cases to visit our customers, as it is still the case today. Standard communication devices like smartphones and email helped at the beginning when TEL intensified the remote support by our Total Support Centre (TSC).TEL continued to develop its Service Advantage program quickly, and started using additional advanced tools and methodologies such as the following: Deployed AR (Augmented Reality) to remotely assist our customer and TEL engineers Secured remote connections into TEL tools to investigate parameters and logs, or to change set-up Used remote training courses that connects trainers via video conferencing systems and training tools in the factories to skill up engineers located in a different parts of the world Used AR glasses for tool start-up and troubleshooting Expanded TEL database global technology with multi-tool on languages search capabilities A key project at a customer site in Europe offers an excellent success story. Using all the approaches above, we collaborated with the local team to put a tool into production with no major delays. This was highly appreciated by the customer and very important for us.SEMI: What do you predict for the future? Shekel: Global technology infrastructure continues to develop and expand rapidly. Elements like 5G networks, IoT and advanced sensing capabilities will lead to what we call General AI, which will be based on neuro-like infrastructure. The auto learning will spread across domains and rely on internal logic and reasoning to automate many tasks that are manual today. In our industry in particular, General AI will enable workers to focus more on data analytics and future advanced R D rather than ongoing operations.SEMI: How can technology unite us? What do you expect from your participation at SEMI Technology Unites Global Summit?Shekel: Technology united us in the last 150 years. The connectivity started with telegraph and telephone and was used to exchange information over wider distances. Nowadays, video conference capabilities, AR and improving communications technology makes it much easier to unite people who are geographically dispersed. This becomes obvious and valuable especially during this pandemic period. As a fact, we are able to continue to perform all our key activities – our tool support, training and customer relationships – even if we cannot be present in person.The SEMI Technology Unites Global Summit is a great chance to stay connected to people and customers that I would normally meet at the SEMICON exhibitions.It also offers the opportunity to network with many more people who I would not be able to meet otherwise. Moreover, I can watch speeches and presentations at any time! Normally I would miss some programs since exhibitions and events took place at the same time.Eyal Shekel, senior vice president of Service Strategy and Excellence at Tokyo Electron Europe Limited, is a 27-year semiconductor industry veteran. Upon his graduation as a Mechanical Engineer from the Technion (Israel leading technical institute), he joined Applied Materials. In 1997 he moved on to Tokyo Electron (TEL) in Europe, served as the Regional Service Manager of Israel and, soon after, was appointed the company’s General Manager. Since 2005 Eyal has been part of TEL Europe senior management. He oversaw the Service and Support Operations for TEL Europe as a senior vice president until 2019. In his current role, he co-leads TEL’s Global Service Committee in Japan.The SEMI SMART Manufacturing Initiative is a global effort to promote awareness of and interest in smart manufacturing with a focus on delivering industry-recognized best-in-class programs and services to enable members to maximize product quality and productivity while reducing costs. Activities are focused on building out core capabilities to enable smart manufacturing across the microelectronics supply chain. MADEin4 is a consortium of 47 partners from 10 countries connecting the full range of supply chain – from semiconductor equipment manufacturers and system-integrating metrology companies to RTOS and key applications such as the automotive industry. The MADEin4 Project develops next generation metrology tools, machine learning methods and applications in support of Industry 4.0 high-volume manufacturing in the semiconductor manufacturing industry. Serena Brischetto is senior manager of Marketing and Communications at SEMI Europe.

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.

Semiconductors play an essential role in modern society by enabling ground-breaking technological advances. The manufacture of high-volume and advanced semiconductors requires the use of fluorinated chemicals known as PFAS. Representing the voice of SEMI members, I explained the important role of these substances and their “essential use” in the semiconductor manufacturing supply chain at a Chemical Watch conference for industry and European Union decision-makers on 3rd of December 2020.In order to achieve the European Green Deal’s zero pollution ambition for a toxic-free environment, the European Commission announced in its recently published Chemicals Strategy for Sustainability its intention to restrict the use of the most harmful chemicals, except in cases where they are deemed essential for society. Per- and polyfluoroalkyl substances – known as PFAS – are the first group of chemicals facing regulatory scrutiny on this basis. This begs the question: What chemicals should be characterized as essential for society and what uses will they encompass? The key and enabling role of semiconductors in modern lifeSemiconductors are essential and ubiquitous in our lives. They are integral to enabling modern society to function – driving advancements in mobile communication technologies for the smartphones and computers that help us work more efficiently and connect us with our loved ones. These benefits have never been more evident than in 2020 with billions of people finding themselves working and studying remotely and safely from home.At the same time, technologies relying on semiconductors have been vital in the effort to combat COVID-19 – in ventilators, medical imaging devices and digital healthcare solutions. In addition, semiconductors will also enable the next leap in society to Industry 4.0 and as essential building blocks in connected and electric vehicles, artificial intelligence (AI) and quantum computing.The Commissioner for Internal Market, Thierry Breton, has highlighted the strategic importance of semiconductors in achieving European digital sovereignty (for instance, in his speech at Hannover Messe Digital Days), and the EU’s New Industrial Strategy[1] also points to the importance of semiconductors and microelectronic systems. What must also be appreciated are the cost and complexity of producing these valuable technologies. Setting up a cutting-edge fabrication plant with the hundreds of pieces of semiconductor manufacturing equipment typically required can cost around €15 billion.[2] A single semiconductor manufacturing tool typically consists of millions of articles, and a typical fab may house several hundred pieces of equipment. Furthermore, according to SEMI estimates, the fabrication of semiconductor wafers requires approximately 500 highly specialized process chemicals. In many cases, these processes, equipment and facilities rely on the unique properties offered by PFAS.“SEMI has worked diligently to highlight the strategic importance of semiconductors in achieving European digital sovereignty, and we are pleased that the critical role of microelectronics has been fully recognized by the EU and Member States. Fluorinated chemicals are essential for semiconductor manufacturing. "These specific chemicals are necessary due to their unique properties, and no alternatives are currently available that can adequately provide the functional properties required in semiconductor manufacturing. The essential use concept, therefore, must enable technological innovation, must apply across the entire supply chain, and must enable EU’s critical infrastructure and strategic objectives.” What are PFAS, and why and where are they used in semiconductor manufacturing?PFAS are a broad and highly diverse group of substances with unique properties and characteristics. The Organisation for Economic Co-operation and Development (OECD) has compiled a list of approximately 4,700 substances,[3] a handful of which are used in the semiconductor manufacturing industry. These very specific chemicals are necessary due to their unique and unparalleled properties that enable them to be used in the demanding conditions of semiconductor manufacturing.Semiconductor chemicalsAt the very core of semiconductor manufacturing is the photolithography process, where microscopic geometric patterns are transferred onto a film or substrate. Photolithography specialty formulations containing fluorinated compounds are used in various steps of this process to ensure quality and reduce the probability of defects. PFAS must be used due to their low surface tension and compatibility with other chemicals. PFAS are typically no longer present in the finished product. However, there are applications where PFAS are present in the final semiconductor device, particularly in imaging semiconductors used in cameras, displays and some medical devices, amongst others. Semiconductor manufacturing equipmentPFAS are also essential to semiconductor manufacturing equipment and factory infrastructure. The exceptional combination of their heat and chemical resistance and their chemical inertness allows fluoropolymers to be used both in equipment components (tubing, gaskets, containers, filters, etc.) and lubrication (such as various oils and greases). These same properties are also needed to ensure the functioning of the surrounding infrastructure. Finally, some fluorinated gases, which are already regulated by specific legislation,[4] are used as refrigerants and to clean the facilities.These are a handful of examples of how PFAS are used in semiconductor manufacturing. Today, there is no other way to undertake these processes or to build semiconductor manufacturing equipment without PFAS. No alternatives are currently available that can adequately provide the functional properties required. Even if alternative chemicals and technologies were discovered today, due to the extremely complex qualification process throughout the value chain, it would take another 15 years to deploy them in high-volume manufacturing. Therefore, continued access to PFAS is a prerequisite for high-volume and advanced semiconductors. Lack of continued access to PFAS could lead to an inability to produce and supply the EU with semiconductor manufacturing technology.How should we think about essential uses?Regulators have started to think about what uses of PFAS are essential and in which cases their use should be allowed. In developing this concept, there are a few aspects to keep in mind.Essential use must enable, not hinder, technological innovationFirst and foremost, the essential uses concept should enable continued technological innovation instead of acting as a hindrance. Semiconductors and manufacturing technology are constantly evolving and becoming more diverse to help meet increasing societal demands. What we see as innovative today may be commonplace in the future, while future innovations may be unimaginable today. We must therefore be careful not to accidentally limit our future potential for innovation.Essential use must apply across the entire supply chainSecondly, classifying a use as essential should apply throughout the entire supply chain. We must, for example, avoid defining semiconductors as essential while classifying the semiconductor manufacturing equipment and chemicals used to produce semiconductors as not essential. In the semiconductor manufacturing supply chain, where one manufacturer can have up to 16,000 suppliers, this risk is evident.[5]Essential use must enable critical infrastructures and the EU’s strategic objectivesFinally, we should keep Europe’s societal priorities in mind. The EU needs to be able to maintain and protect its critical infrastructures. Similarly, we should not lose sight of the EU’s strategic objectives of a green and digital Europe.Semiconductors, in conjunction with their corresponding manufacturing equipment and chemicals, are essential technologies in everyday life and the backbone of the EU’s strategic value chains. Manufacturing semiconductors is a very expensive and complex process that would not be possible without the unique properties of PFAS, making them essential to achieving the EU’s strategic objectives today – whether the European Green Deal or digital autonomy – and in the future. Therefore, we must ensure that essential uses will enable the continued use of PFAS in semiconductor manufacturing.The SEMI presentation delivered at the Chemical Watch event can be accessed here.Emir Demircan is director of Public Policy and Advocacy at SEMI Europe.[1] “The EU will also support the development of key enabling technologies that are strategically important for Europe’s industrial future. These include robotics, microelectronics, high-performance computing and data cloud infrastructure, blockchain, quantum technologies, photonics [etc.]”[2] Emerging technologies in electronic components and systems (ECS) Opportunities Ahead – A study by DECISION, 2018 for the European Commission[3] Available here[4] Regulation (EU) No 517/2014, “F-Gas Regulation”[5] SIA Nathan Associates, 2016, https://www.semiconductors.org/wp-content/uploads/2018/06/SIA-Beyond-Borders-Report-FINAL-June-7.pdf

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.

The costs of production are typically based on labor and materials and define manufacturing expenses. But is this approach accurate enough? What about the cost of poor quality and lack of efficiency in production? How is the pandemic impacting semiconductor manufacturing and what can we expect from the future?SEMI recently spoke with Dr. Eyal Kaufman, founder and CEO of QualityLine, a Kiryat Gat, Israel-based provider of smart manufacturing analytics solution, about manufacturing controls and how to select the best data source to improve product quality and yield. Kaufmann provided a snapshot of current best practices used by the company to improve manufacturing efficiencies and product quality while reducing costs. He also discussed the COVID-19 pandemic’s impact on semiconductor smart manufacturing and how artificial intelligence (AI) can help keep factory workers safe.For additional insights on smart manufacturing, join the virtual SEMI Global Smart Manufacturing Conference, October 20 - 22, 2020. Registration is open.SEMI: Real manufacturing costs are calculated based on different aspects such as failures in production, repairs, products returned, scrap of components or late deliveries. Lack of quality and efficiency in manufacturing can undermine a business. How are you helping businesses overcome these challenges?Kaufman: To increase profit margins, it is essential to identify inefficiencies and what improvements to prioritize. Once manufacturing quality and efficiency deficiencies have been measured, the next step is to continuously collect manufacturing data in order to run the final cost analysis and use the analytics to improve the manufacturing process.Smart manufacturing makes it possible to detect anomalies in automated factories, improve production performance and increase profitability. Today, automated data are collected from every machine and piece of test equipment in the factory. Still, manufacturing data collection in many industries remains manual and expensive because of the time and human resources involved. A real-time analytics system can automatically collect all data sources and select the relevant data for analysis, which today is the most accurate and effective way of measuring and resolving quality and efficiency deficiencies.Data-driven decisions made by smart manufacturing reduce costs and improve manufacturing strategies, enabling factory operators to increase product quality, drive higher production capacity and enhance product design for manufacturability. Analytics solutions monitor shop floor operations accessing vendors and subcontractors’ products criterion to run root cause analysis. All those data will reduce the return rate of faulty products and accelerate return on investment. This is why we definitely need smart manufacturing technologies!SEMI: Data accumulated during the manufacturing process includes vital information about failures, anomalies and machine usability. What data are necessary to create the best analytics solution?Kaufman: Many companies today run data mapping and automatic creation of data capture. They often wonder if they need to use testing data, sensors data or product design data, or whether they should collect feedback from their customers and vendors. The best way to create an effective manufacturing analytics system is to use data sources such as: Feedback from customers (returned units, customers complaints, etc..) Testing data from automated test equipment and manual test activities Feedback from technicians repairing faulty units Analysis of testing processes done by vendors Sensors data Data from our ERP/MES systems Artificial intelligence enables any type and size of data structure, even accumulated data, to be automatically integrated and interpreted. AI-based analytics can also establish correlations between each manufacturing stage to help factory operators quickly conduct deep diagnostic and root cause analysis for problem solving and prevention – all while leaving intact a factory’s existing process, machinery and data output. Machine learning evaluates how a factory runs its database and puts all the information generated into an analytics solution that provides the know-how to continuously improve factory efficiency.SEMI: How do you select the best data source to improve manufacturing quality and yield? Kaufman: The accuracy and integrity of data accumulated in our manufacturing process is key to controlling and improving yield and quality while reducing manufacturing costs. Smart manufacturing is a technology-driven approach that uses digital and remote connected machinery to monitor the production process. The goal is to identify anomalies in manufacturing processes and leverage analytics to improve process yield and product quality.To select the relevant data, we collect each type and source of data that can improve the efficiency of a real manufacturing cell: Test data from Automated Testing Equipment Test data from Manual Testing Processes Analyses of repairing processes (failed units during the manufacturing process and units that were returned from customers) Once the data structure is collected, the next step is to turn it into actionable information in the manufacturing process. QualityLine smart manufacturing solutions provide a complete one-stop solution to interpret any manufacturing data structure. Our advanced manufacturing analytics solution detects quality and yield anomalies to reveal production line inefficiencies and opportunities to improve manufacturing quality and efficiency.SEMI: How would you describe your approach?Kaufman: Industry 4.0 in manufacturing claims to be the fourth generation of the industrial revolution. Advanced technologies like manufacturing intelligence and machine learning can efficiently achieve zero defects on manufacturing lines. Digital factories leverage technologies and methodologies including: Big data Self-optimization Self-configuration Self-diagnosis Cognitive and machine learning Smart manufacturing technologies enhance the manufacturing process by continuously collecting and analyzing data in real-time to achieve and maintain high quality performance. The goal is to achieve a significant increase in efficiency and yield while reducing waste and inefficiency.Until now, there has been no viable way to integrate all saved manufacturing data into a unified database. QualityLine advanced manufacturing analytics make it possible for any factory to become digital without installing new hardware, which can be expensive and require not only the extensive integration of existing data but investments in training. Our user-friendly solution integrates manufacturing data for industries with zero automation by first collecting and analyzing data from any type of manual test procedure and then integrated it into manufacturing analytics to improve efficiency.SEMI: Why are Pass/Fail criteria insufficient for controlling manufacturing yield and quality?Kaufman: Managing a mass manufacturing process is always a challenge because hundreds of tasks must be successfully completed before products can ship to customers. At QualityLine, we establish a test process for each stage of the production flow, from the incoming raw material to the final stage prior to the delivery of finished goods to the client. To prevent unexpected downtime incidents, waste and defective products, we collect and interpret every type of relevant data and turn it into meaningful information, setting up the following capabilities: Collection and interpretation of test and process data of each single unit and from each process and plant Automatic detection of quality and yield problems Accurate and quick root cause analysis process Automatic alerts to abnormal issues Prediction process potential and level of failures Measurement of key performance indicators Many manufacturers base their test criteria of each parameter on one key indicator – Pass or Fail. If the test result shows a Pass, then the unit is ready to move on to the next manufacturing stage. If the test result shows Fail, then the unit is sent to a technician for further analysis.A simple Pass or Fail criteria for product quality is far from sufficient since it provides little or no information about edge cases, where one or more of the technical parameters of the unit under test is only within its allowed tolerance. Edge cases may lead to unit failure during operation such as in extreme environments (cold, heat, humidity, electrical overload, impact, etc.). In fact, when running a mass manufacturing line, it is impossible to continuously digest all the detailed information collected from testing stations. Data is analyzed in detail only when a critical quality problem emerges and further analysis is required to understand the root cause.Information overload and the disregard of important parameters makes it hard to control the process and improve quality and yield. New technologies make fast and scalable data integration possible so data can be collected in real time to detect quality issues early, identify complex process disruptions to avoid delivery delays and ensure the best possible product for customers. Only by accurately analyzing data as actionable information can factory operators control the manufacturing quality process.SEMI: How has COVID-19 impacted the smart manufacturing market? How has your technology helped factories remain online?Kaufman: Smart manufacturing is playing a significant role by helping manufacturers overcome COVID-19 challenges such as workforce reductions, social distancing, drops in sales for some specific products and extreme pressure to cut operational costs.Manufacturing leaders turned to us for a solution to the challenges of maintaining efficient factory operations with a limited workforce and reduced number of operating hours. Filling factory orders with fewer people on the floor is a struggle. Digital factory technologies enable remote monitoring of operations to increase efficiency and capacity. We are helping our clients improve efficiency while reducing costs. Our remote monitoring technology can provide the operational visibility to floor managers and engineering teams who cannot go physically to the factories due to safety restrictions. With our advanced manufacturing analytics, they have full end-to-end visibility and can remotely diagnose and solve production line issues. During this critical time, we are proud to be improving remote monitoring solutions to help the industry withstand the pandemic. Some of our clients would have closed their factories otherwise. We’ve been working to integrate manufacturing data in factories that were previously unautomated to drive high automation levels. Integrating processes with existing factory data, regardless of customer’s protocols or automation level, is our great technology advantage.SEMI: How will manufacturing and its supply chains look after COVID-19?Kaufman: Smart manufacturing is currently a necessity. We collect and analyze data not only to improve quality but to reduce client returns of faulty products by 50% and reduce waste by 22%, both critical points. Manufacturing challenges will continue to accelerate advancements in technology and improve efficiency, safety and productivity as more factory operators incorporate real-time data analytics and artificial intelligence (AI). SEMI: Will suppliers continue to explore new avenues for smart manufacturing technologies and what are their growth opportunities?Kaufman: Yes, definitely. The sector has already changed, with COVID-19 bringing both opportunities and challenges. Industry leaders are facing new pressure, with sudden materials shortages, drops in demand and worker unavailability. The growth opportunities for manufacturing are likely to be digital, as already evident in the immediate response to the crisis. Industry 4.0 solutions will be crucial to increase end-to-end supply-chain transparency, automation and data integration. QualityLine manufacturing analytics have improved key manufacturing performance metrics. For example, based on customer feedback, we’ve increased production yield by 30%, saving some of our customers millions of dollars. Improvements like this can help suppliers withstand pandemics.Dr. Eyal Kaufman, Founder and CEO at QualityLine, has senior management experience and over 25 years of expertise in business development, marketing, finance, operations, engineering and quality management at leading industrial companies. Prior to QualityLine, he served as VP of Mobileye, Cardo Systems, and Medisim Ltd., as well as CEO of OnTheGo Systems. Eyal holds a Ph.D. from California Intercontinental University, an MBA from City University of New York and a BSc. from the Technion in Israel.The SEMI SMART Manufacturing Initiative is a global effort to promote awareness and interest about smart manufacturing with focus on delivering industry-recognized best-in-class programs and services to enable members to maximize product quality, productivity and cost improvements through smart manufacturing. Activities are focused on building out core capabilities to enable smart manufacturing across the microelectronics supply chain.MADEin4 is a consortium of 47 partners from 10 countries connecting the full range of supply chain: from semiconductor equipment manufacturers and system-integrating metrology companies to RTOS and key applications such as the automotive industry. The MADEin4 Project develops next generation metrology tools, machine learning methods and applications in support of Industry 4.0 high volume manufacturing in the semiconductor manufacturing industry.Serena Brischetto is a senior manager of marketing and communications at SEMI Europe.

If you bought a new car recently, you must have noticed that it warns you if one of its functions needs your attention. It even alerts the factory if repairs or major adjustments are needed. Wouldn’t it be nice to have similar capabilities for our bodies that will call for a “service” before we end up in an emergency room – or worse? The United States invests almost 18 percent of its Gross Domestic Product (GDP) in healthcare. Such a significant part of our economy deserves our industry’s attention – and it gets it. SEMI’s recent Smart MedTech webinar series tells not only patients and healthcare providers how electronic products can impact their lives, but also offers device makers plenty of ideas for developing new solutions.SEMI Gets SmartIn addition to working on many important topics with more than 2,200 member companies across the semiconductor supply chain, SEMI focuses on special areas: Smart Mobility (as covered here), Smart MedTech (covered below), Smart Manufacturing, and Smart Data. Smart MedTech was the topic of four recent webinars, organized by Melissa Grupen-Shemansky, executive director Nano-Bio Materials Consortium (NBMC), and Chief Technology Officer, SEMI. NBMC’s mission is to enable flexible, wearable human performance monitoring. In her introduction, she emphasized that healthcare will shift from today’s provider-centric approach to a personalized care model, with the following characteristics: Outcome-based Decentralized, not limited to geographies Specific to your personal health and medical needs With a team of providers, connected like never before To achieve all these characteristics, microelectronics will be an essential contributor. That is why SEMI and member companies are working on platforms to fund and commercialize R D as well as to educate potential users and beneficiaries. Grupen-Shemansky engaged a series of experts and organized four webinars to address this broad and complex field, and outline their contributions to meeting the above criteria. They have been recorded and are available to SEMI members. Call your SEMI contacts to find out where and how you can access slides and recordings of more than a dozen presentations.From Biomarkers to BioChemical Sensors Physiological RelevancyTo monitor a human body’s performance, researchers have to first understand which biomarkers indicate specific conditions of the body, then learn how to capture and process the data. Grupen-Shemansky moderated this August 5th session. Christina Davis from UC Davis, Jennifer Martin, and Sean Harshman from the Air Force Research Lab (AFRL), and Kenneth Ward from Pacific Diabetes Technologies presented their ongoing efforts in this field.Davis talked about the challenges of analyzing exhaled breath, which contains 99% water and 1% biomarkers. She showed a hand-held analyzer her team has developed (Figure 1). She also elaborated on how to interpret the captured data and, if needed, decide which follow-up treatments are advised.Figure 1: Palm-sized µCON exhaled breath micro-condenser used to analyze biomarkers. (Courtesy: UC Davis) AFRL’s Martin and Harshman outlined how ongoing and future minimally invasive techniques are being used to monitor airmen, and give them advice for self-treatment to maximize their performance. The Pacific Diabetes Technologies speaker, Ward, showed how to use minimally invasive, subcutaneous (=under the skin) oxygen sensors to detect hemorrhage (= blood loss) and control it.En Route Care (ERC) and Point of Care (POC) DiagnosticsTreating injuries right away and correctly shortens not only a patient’s suffering, but also improves his or her chances for a full recovery. AFRL’s Matthew Dalton moderated this August 12th session. Derek M. Sorensen from AFRL, Zheng Yan from the University of Missouri-Columbia, Melinda Eaton from the Virtual Health Program Management Office at the U.S. Department of Defense (DoD), and Azar Alizadeh from General Electric (GE) Research outlined their contributions to achieving instant and professional care.AFRL’s Sorensen described the many challenges a Critical Care Air Transport Team (CCATT) deals with when performing their work inside a noisy, dark, hot, or cold, shaking airplane, discussed their equipment and personnel constraints, and explained how difficult it is, even for experienced doctors, to perform emergency surgeries under these conditions.Professor Yan takes low cost very seriously and demonstrated how he and his students have developed on-skin wearable sensors that can be manufactured by using only pencil and paper.Eaton outlined the DoD’s strategy for assuring its medical force is ready to support soldiers. Then she discussed a broad range of the DoD’s traditional health management responsibilities and added that Covid-19 is now an important factor.Alizadeh addressed how GE microelectronic solutions improve the efficiency of care, reduce medical errors and length of hospital stays as well as improve workflows of caregivers. In addition to GE’s well-known, large/stationary medical equipment and communications infrastructure (Figure 2), Alizadeh showed that GE is also providing skin patches and other wearable sensors to capture data.Figure 2: The Future of Monitoring: In 2017, Mercy Hospital served 800,000 patients with telemedicine including those with chronic diseases. Patient:doctor ratio: US average 300:1. Mercy = 1100:1. (Courtesy: GE) Human Wearables Enabling Rapid Decision Making in the Integrated Care ContinuumAs Figure 2 above shows, microelectronic equipment can improve patient care and efficiency of medical personnel, but only if sufficient data can be captured timely and accurately – increasing the importance of wearables. AFRL’s Jeremy Ward moderated this August 17th session. Christopher Scully from the U.S. Food and Drug Administration (FDA), Ashleigh Coker from the AFRL’s Sensors Directorate, Ted Harmer from the AFRL’s Airman Systems Directorate, and AFRL’s Regina Shia presented for Oxana Pantchenko from NextFlex how they develop wearables jointly. Scully introduced the FDA’s organization and its responsibilities, described the high-value accurate data can provide, warned about the damage false alarms and equipment failures can cause, and explained the regulatory role the FDA plays in this context.AFRL’s Coker highlighted the essential role sensors play in modern warfare with several examples, described her directorate’s operations and showed their warfighter-centric design process (Figure 3).Figure 3: Warfighter-centric design process steps and the need to engage multiple heads/perspectives in this process. (Courtesy of AFRL) AFRL’s Harmer addressed the importance of good communications architecture and protocols to capture and compute data to assure efficient cooperation between land/air/sea/space-based forces.NextFlex’ Pantchenko prepared a presentation about standards-compliant wearable electroencephalography (EEG), electromyography (EMG), and electrooculography (EOG) devices, jointly developed with AFRL and several other companies. It was delivered by AFRL’s Regina Shia.Automation, Augmentation and AINatalie Wisniewski, Founder of Profusa, Inc. a and consultant in Wearables and Digital Health, moderated the fourth webinar, held on August 26. She emphasized SEMI’s role in this context, then introduced the speakers: Michael Kirby from Colorado State University, Kevin Zhao from Harmonize Health, Mary Clare McCorry from armi/biofab USA, and Andreas Caduff from ETH Zuerich.Professor Kirby outlined several mathematical principles that need to be applied to get meaningful results when analyzing data. He emphasized that genetic factors influence if an individual is susceptible, tolerant, or even resistant to certain pathogens and warned that bacteria can develop resistance to today’s antibiotics.Zhao from Harmonize talked about the importance of predictive analytics in remote care, how to filter out false alarms, and how to deliver the best available care cost-effectively. In closing, he emphasized that computers and algorithms are not replacing clinical staff.McCorry outlined how biofab USA, a program of armi, uses sensors and automation to grow replacement tissue and organs (Figure 4). She explained how they use engineering principles and life sciences to make guide cells grow into replacement tissue. The company’s plan is to expand the currently lab-based capabilities into an industrial scale tissue foundry.Figure 4: Growing ear cartilage in the lab. (Courtesy: armi/biolab USA) SummaryMcCorry summarized her presentation, and actually the entire webinar series, with these statements: The human body is a 3D, highly complex, dynamic, and multi-faceted biological construct Skin lends itself well as an interface between body and wearable sensors Connecting physiology (e.g. vital signs), behavior, and external factors is important for getting good results Verification, validation, and FDA involvement are important for making methods and devices successful Sensors, communication computing (AI/ML) are complementing, not replacing, medical personnel Today’s methods and devices will be outperformed by tomorrow’s solutions – stay up to date Personal CommentsSummarizing eight hours of presentations in a few pages requires a very high and lossy compression factor – please understand. I suggest you call on your SEMI contact to get access to these previous and following webinar recordings. Excellent contacts across the electronics supply chain enable SEMI to win experts in many areas to convey valuable information in these webinars.I am impressed that the USA military, specifically the AFRL, invests so much effort in medical support for airmen/women. They demonstrate that only healthy and fit personnel can take full advantage of the sophisticated weapon systems at their disposal if/when they are called upon to deploy them.This Smart MedTech webinar series confirms what many medical experts told me during exams and/or before and after surgeries: The human body is a masterpiece of bioengineering. These webinars also reminded me of what I learned at a brain-health class at Stanford University: Our brains only need about 20 Watts to perform computing and memory tasks that fairly quickly approximate the results of today’s computers – a benchmark for computer architects and AI/ML experts.Republished with permission from 3D InCites.

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.