digital twins

2025 was a fast-paced, exciting, and impactful year for the SEMI Standards team. We developed 14 new standards on crucial topics like supply chain traceability, defect mitigation, compound semiconductor materials, and so many more. In addition, we introduced the SEMI Global Standards Summit (GSS) in North America, where we created new standardization roadmaps and continued pertinent sustainability conversations from the inaugural GSS at SEMICON Japan 2024. We’re also excited to announce that we closed out 2025 with an impactful Q4. From December 17-19, we held our SEMI International Standards Meetings during SEMICON Japan. More than 15 Task Force meetings and 5 Technical Committee meetings were held, followed by an award ceremony. The brand-new Digital Twins in Manufacturing Task Force was also established to define and standardize a digital twin framework that supports consistent and scalable implementations. We published the new SEMI T27 standard in Q4, and we celebrated several outstanding volunteers for their contributions to the SEMI Standards Program at both SEMICON West and SEMICON Europa. As we reflect on Q4, it’s apparent how important collaboration is to the success of SEMI Standards. By working together, we lay the foundation for groundbreaking innovations in microelectronics manufacturing. The SEMI Standards team would like to extend a warm and sincere thank you to everyone who donated their time and expertise to define the future of our industry. These efforts would not be possible without your commitment and support.Still, it’s never too late to join the SEMI Standards Program. Learn more about membership and how you can help influence the next phase of semiconductor manufacturing. Q4 2025 HighlightsTakeaways from the International Standards Meeting at SEMICON JapanIn Q4, the SEMI Standards team held its International Standards Meeting at SEMICON Japan, where several task forces convened to set standards for compound semiconductor materials, information and control, traceability, and more. From December 17-19 at Tokyo Big Sight, the SEMI Standards team supported these technical committees in advancing several key standards revisions, including SEMI E181, Specification for Panel FOUP for Panel Level Packaging, and SEMI E182, Specification for Panel FOUP Loadport for Panel Level Packaging. In addition, a new Maintenance Robot Communication (MRC) Task Force was established with the objective of defining communication protocols and data exchange specifications between maintenance robots and equipment.The next SEMI International Standards Meeting will take place from May 11-14 in Albany, New York, during the SEMI Advanced Semiconductor Manufacturing Conference (ASMC). Digital Twins in Manufacturing Task Force Although the terms “digital twins” and “digital twin frameworks” are becoming more prevalent in the semiconductor industry, there’s still much debate on what they cover. To develop concrete, standardized definitions for each, the SEMI Standards team established the Digital Twins in Manufacturing Task Force in Q4. After the task force defines these crucial terms, it will then create definitions for internal digital twin components outlining baseline capabilities, discovery mechanisms, prediction quality metrics, unified model interfaces, and lifecycle management. Eventually, the task force will outline a framework for Digital Twins compatible with existing guidelines like SEMI Standard E133 or ISO 23247. The SEMI Digital Twins in Manufacturing Task Force is open to industry stakeholders. To participate, join the SEMI International Standards Program or learn more. Standards Awards at SEMICON West and SEMICON Europa SEMICON West honoreesQ4 was also a time to celebrate some of the talented individuals who make a difference in the SEMI Standards Program. At SEMICON West and SEMICON Europa, we honored 25 accomplished industry leaders across the following five award categories for their commitment and participation. Merit Award winners led projects to successful completion at the task force level. SEMICON Europa honorees: Judith Wittmann, Cristina Sanna, Peter Wagner, Friedrich Passek, Frank Riedel SEMICON West honorees: Dave Dunne of Applied Materials, Kirsten Smith of UCT/ChemTrace, Tommaso Orzali of ASML, Dr. Tyler Harrison of Teledyne MEMS, and Dr. Mary Ann Maher of SoftMEMSSEMICON Europa honorees: Christian Kranert of Fraunhofer IISB, Enrica Cela of Soitec, Hans-Christian Alt of the Munich University of Applied Sciences, and Ulrich Kretzer of Freiberger Compound Materials GmbHLeadership Award winners bolstered the SEMI Standards program through member recruitment, mentoring, and training efforts. SEMICON West honorees: Michael Potts of Arcadis, David Kandiyeli of KINETICS Equipment Solutions Group, and Per Nelson of Daikin AmericaSEMICON Europa honorees: Frank Riedel and Judith Wittmann of Siltronic, Cristina Sanna of GlobalWafers, and Jochen Ruth of Pall CorporationHonor Award winners have demonstrated long-term dedication to advancing SEMI Standards.SEMICON West honorees: Steve Martell of Nordson Test Inspection Americas, Lucian Girlea of Nikon Precision, and Dave Huntley of PDF SolutionsSEMICON Europa honorees: Peter Wagner of SEMI Standards, Fritz Passek of Siltronic, Arnd Weber of SiCrystal GmbH, and Frank Petzold of trustsec IT solutions GmbHCorporate Device Member Award winners are participants from the user community who act as corporate representatives for the SEMI Standards Program from the device manufacturer side. Stefan Radloff of Intel was honored with this award at SEMICON West. Technical Editor Appreciation Award winners are adept at translating complex technical information into clear and precise language. Dr. Alissa M. Fitzgerald of A.M. Fitzgerald Associates became the award recipient in 2025. Workshops at SEMICON WestOn October 8, the SEMI Voltage Sag Immunity Task Force hosted its Enhancing Voltage Sag Immunity workshop to address fab downtime caused by voltage sags. The workshop convened more than 20 industry professionals to review the limitations of SEMI Standard F47. They found that while 20% of downtime instances can be attributed to three-phase events, SEMI Standard F47 does not require testing for such occurrences. As a result, the Voltage Sag Immunity Task Force is developing a draft revision of SEMI Standard F47, scheduled for balloting in March 2026. If you missed this workshop, you can access the recording and presentation here. October 8 also saw the exciting return of the Analytical Workshop, hosted by the SEMI Liquid Chemicals Committee after a multi-year hiatus. This year’s workshop addressed near-term challenges and advancements identified by the International Roadmap for Devices and Systems (IRDS). It covered chemical quality and consistency, trace metallic impurities and improvements in ICPMS instrumentation, automated instrumentation for online measurements, detection for particle precursors and sub-10nm particles in liquids and on-wafer, and organic particle precursors identification using FTIR-ATR, SERS and AFM-IR. If you missed this workshop, you can access the recording and presentation here. The 2026 call for abstracts will be announced soon. Lastly, the SEMI Standards and SEMI University teams worked together to host Semiconductor Device Manufacturing in a Cleanroom, a workshop meant to introduce best practices for overcoming contamination problems in the cleanroom. By reviewing different sources of contamination, reviewing analytical techniques for quality control, and performing cleanliness testing, the course aims to help cleanroom facilities improve production reliability and yield.New and Revised Standards Released in Q4October 2025November 2025December 2025Get InvolvedSEMI Standards development activities take place throughout the year in all major manufacturing regions. To participate, join the SEMI International Standards Program.SEMI Standards are available through individual download purchases or online via SEMIViews. Watch this video to learn more about how SEMIViews offers a cost-effective and streamlined way to access 1,110+ SEMI Standards. Sign up for a 30-day SEMIViews trial.For more information, please visit the Standards website and events page. For any questions regarding SEMI Standards activities, please contact your local SEMI Standards staff.Paul Trio is Director of Standards at SEMI.

Digital twin technology enables supply chain managers to create a virtual model of their operations, allowing them to simulate various scenarios and optimize their processes, leading to improved efficiency, resilience, and cost savings.

Handel Jones, a well-known, longtime strategic analyst and commentator covering the semiconductor industry, authored the recently published book – When AI Rules The World: China, the U.S. and the Race to Control a Smart Planet. I spoke with Jones about the fascinating read.

Charles Shi, Principal, Senior Analyst, Needham & Company, LLC., recently offered an upbeat assessment of the electronic design automation (EDA), silicon intellectual property (IP) and services industries, or what SEMI refers to as the electronic system design (ESD) ecosystem.

The increasing complexity of IC manufacturing poses a number of challenges including the mask data preparation required to enable technology improvements such as multi-beam (MB) mask writers and extreme ultraviolet (EUV) lithography. Thiago Figueiro, VP of Sales & Marketing of Aselta weighs in.

In this article, several experts weigh in on considerations for developing the smart manufacturing workforce that will help to alleviate the U.S. semiconductor manufacturing talent shortage, even as multiple, data-intensive $1 billion to $10 billion fabrication facilities come online.

Connecting product development to manufacturing to the field in the semiconductor equipment industry by becoming a Model-Based Enterprise Manufacturers across many industries, including the semiconductor equipment industry, are facing pressure to dramatically reduce product development cycle and production ramp times while also enhancing product quality and reliability. This challenge is complicated when multiple configurations are deployed and then maintained, enhanced and upgraded in the field. Buzzwords like digital thread, digital twin, smart manufacturing, Industry 4.0, and digital supply networks point toward a fusion of process, technology, data, and talent that promise the game-changing outcomes needed to address these challenges. Yet, there remains uncertainty about how these various elements come together into a cohesive approach across the product lifecycle. One such approach involves establishing a Model-Based Enterprise (MBE), with alignment across organizational silos, processes, and technologies. Too often, however, an effort to transform to an MBE is frustrated by “random acts of digital” that pursue implementation of certain digital technologies but fall far short of delivering value. What is needed instead is a deeper understanding of the characteristics of a true MBE and the tools and approaches to transform the organization, processes, and data to an MBE and thrive in the marketplace. Elements of a Model-Based Enterprise Modeling in engineering is not new, but what’s emerging are MBEs that comprise digital models connected upstream and downstream over the entire product lifecycle, from a product’s conception and development through its production and end market installation and use. At the heart of such MBEs are digital threads—integrated sets of processes executed within an interconnected technology ecosystem that drive the end-to-end product lifecycle and provide MBE data traceability front to back. A digital thread in the MBE environment includes all of the process, data, and system capabilities that enable digital representations of the product lifecycle stages, or digital twins, of which there are three primary types: The product digital twin is a virtual or simulated representation of the product and each of its components and configurations. While most manufacturers manage engineering models with CAD/CAE solutions, just 15% use product digital twins. Leaders in this space have seized a competitive advantage in product development and accelerated engineering. Yet, becoming a true MBE requires more than product digital twins. The process digital twin is a model of the manufacturing equipment, processes, and the workforce required to carry out related operations. The process digital twin represents the operation of the physical factory floor and its assets, complete with workflows and instructions that describe how the manufacturing processes are performed. A process digital twin relies on data from the product digital twin and allows the enterprise to build according to a product plan and predict what may happen on the factory floor. About 5% of enterprises use process digital twins. After production, a service digital twin represents the installation, use, maintenance, and repair of each product operating in the end market. The service digital twin is informed by product and process digital twins to facilitate adjustments and enhancements based on real-world data. Less than 5% of manufacturers use service digital twins, which is perhaps expected due to their reliance on the existence of the product and process digital twins. When underlying data (e.g., models, specifications, and configurations) are standardized and integrated across a digital thread, an enterprise has the capacity to monitor and refine a product over the span of the thread while also injecting insights and improvements back into the thread. The result is that engineering and manufacturing and end customer usage feedback is continuous and efficient, achieving in weeks what once took months. Visibility into materials, costs, suppliers, and more enable the enterprise to pivot and keep production moving, even when dealing with unforeseen challenges. Real-time monitoring that synthesizes live data also helps reveal performance insights and end market issues (e.g., installation issues, quality issues, etc.) that allow improvements to the offerings and operations of the enterprise. While the manufacturing and product development benefits of an MBE may be clear, the path to becoming an MBE and achieving these benefits can be challenging. Figure 1. Representative MBE end-to-end digital thread that connects product development, manufacturing, and the field (Source: Deloitte Development LLC, 2021) Accelerating Transformation New and emerging manufacturers have an opportunity to build toward their MBE vision without the historic data constraints legacy systems can impose. For more established manufacturers, such is more typical in the semiconductor equipment space, legacy technology and processes can present obstacles to an MBE transformation path. Stakeholders who have invested time and resources implementing certain enterprise platforms (e.g., CAD, PLM, ALM, MES, ERP, etc.) often look for how these can be used to enable a digital thread and digital twins over the enterprise. This limiting view frustrates a broader, more holistic opportunity to transform to an MBE and thrive in the marketplace. There is thereby a dual imperative to define a modernized and scalable end-to-end technology architecture for managing the MBE product data while also establishing a capabilities implementation roadmap that rapidly leads to MBE maturity. To be successful in your MBE transformation, four core functional capabilities that enable a digital thread must be considered: digital engineering, industrial simulation, manufacturing execution, and real-time monitoring. Addressing each with optimized tools allows a manufacturer to rapidly move from strategy to reality. Recognizing the complexity of addressing these functional needs, Deloitte has developed preconfigured solutions to help expedite and enhance transformation across each of these core areas. Design with D-PLM Simulate with D-Sim Execute with D-MES Monitor with D-IoT Accelerates product and application lifecycle management transformations with a multi-phased approach, including a phased, multi-year PLM/ALM roadmap and business case. Facilitates the ability to test and refine processes in a virtual environment, rapidly revealing the most efficient and effective industrial processes more quickly than is possible in a real-world environment. Integrates pre-defined processes related to production planning, execution, tracking and tracing, quality management, data collection, and visualization, with integrations to PLM and ERP. Delivers fast implementation of IoT capabilities that connect, collect, and analyze a broad scope of production data to drive quicker returns for high-impact areas while cultivating digital adoption. While many enterprises have various initiatives in model-based systems and manufacturing, few have tied them together with an end-to-end digital thread and set of data standards over the entire product life cycle. The foregoing preconfigured solutions can help enterprises transform to a true MBE that can typically achieve: 15% – 20% better development efficiency 30% – 50% faster time to market 8% – 20% product cost reduction 10% – 30% cost of quality reduction With such improvement potential, this could be the right time to map out and accelerate your MBE transformation to support your evolving business models and products. Deloitte Consulting LLP Co-Authors Kevin Prendeville Principal, Product Strategy Lifecycle Management [email protected] Vijay Santhanam Managing Director, Product Strategy Lifecycle Management [email protected] Kenneth Norton Senior Manager, Product Strategy Lifecycle Management [email protected] Dan Hamling Specialist Master, Technology Semiconductor [email protected] As used in this document, “Deloitte” means Deloitte Consulting LLP, a subsidiary of Deloitte LLP. Please see www.deloitte.com/us/about for a detailed description of the legal structure of Deloitte USA LLP, Deloitte LLP and their respective subsidiaries. Certain services may not be available to attest clients under the rules and regulations of public accounting. This publication contains general information only and Deloitte is not, by means of this publication, rendering accounting, business, financial, investment, legal, tax, or other professional advice or services. This publication is not a substitute for such professional advice or services, nor should it be used as a basis for any decision or action that may affect your business. Before making any decision or taking any action that may affect your business, you should consult a qualified professional advisor. Deloitte shall not be responsible for any loss sustained by any person who relies on this publication. Copyright © 2021 Deloitte Development LLC. All rights reserved.

Semiconductor fabs have been getting smarter and smarter over the past 30 years. It’s a natural evolution – the direct outcome of numerous continuous-improvement efforts. The really important difference on the road to smarter fabs, the one change that’s enabling the Industry 4.0 revolution, is the concept of a cyber-physical system or digital twin. If you don’t have a thorough, detailed, high-fidelity digital twin of your entire fab operation, then you cannot have “Smart Manufacturing.” That’s really the definition of a smart site. A digital twin is simply a requirement for all smart factories of the future. One caveat: No matter what you build today from a smart perspective, your digital twin’s fidelity will improve over the next 20 years. A factory’s digital twin has two facets: the operational aspect and the yield aspect. Each of these two facets places different requirements on a database including the types of data, the frequency of data generated, the retention of data, and even the AI/ML techniques used to analyze the data. A combination of these data requirements are needed to create a digital twin – the virtual representation of your entire factory operation, whether it’s on the wafer-fab front end or the assembly and test back end. What’s most important here is that facility-wide data sets and databases must be able to communicate with each other using refined summary statistics to create a practical digital twin. For example, a lot of information is collected on the yield side to feed the deep-learning models needed to manage processes. However, the factory scheduler, driven largely by the smart operational database, needs only summary statistics from the yield database to be able to act in the next moment or over the next 24 hours. Figure 1 illustrates the needs of and the interaction between a smart operational and a yield database. Figure 1: The Operational and Yield databases in a Smart Factory need to exchange summary statistics. Today, we find that although these databases generally speak to each other in smart factories, they’re still not sufficiently connected to permit the use and analysis of data needed to realize the full potential of a smart factory. That level of interconnectedness is still in the future. Some solution providers have created what is essentially a “smart learning warehouse” (“database” has become too limited a term here). This warehouse collects, analyzes and learns from the extensive amount of information that a fab generates. Game-changing, more holistic applications become possible when this information can be combined in new and informative ways. As it turns out, a data source is just a data source, but users in different factory areas need to extract different information from these common data sources. They need different applications and portals – in other words “views” – that are adapted and adjusted for each area’s needs. Aren’t we smart enough? Some people think that 300mm fabs are already smart. That’s true. They are. But, they could be a lot smarter. No 300mm fab in use today has attained the full, utopian vision of what a smart factory can deliver over the next 10 years. When you finally integrate all of the disparate databases in a fab – when you’re able to use all of those different data sources as one common data source – that’s when your Smart Factory will have the ability to self-optimize its future actions and react quickly to real-time events. The largest semiconductor manufacturers tend to develop these smart factory applications on their own. The remaining semiconductor fabs need to work together with other fabs and their solution providers to develop these smart factory applications. Why now? Why is everyone talking about “Smart” now? It’s because the semiconductor industry has helped to create all of the enabling technology: the compute power, the networking and networking standards, and even the industry’s maturation into a multi-tiered organization of solution providers. We’ve reached the point where we can collect data from a widespread sensor network along with tool-health data and we can then warehouse this data so that it can be applied to more intelligent decision-making. While there may be one or two sensors on a tool today, in the future there will be many such sensors connected over an IoT network or networks that provide mountains of data to the warehouse. All of this data will feed into the digital-twin version of the fab. One of the biggest changes on the horizon made possible by all of this accessible data is advanced scheduling. Despite all of the automation advancements made over the past 25 years, including robotic handling, it’s still hard to decide “where, what, and when?” for every single lot in the factory. Today, no factory in the world is more complex than a semiconductor fab. Optimizing a semiconductor manufacturing process is the most complex manufacturing-optimization task in the world. Do it for ROI ROI is the chief reason for having a digital twin. Once you can make a truly smart, holistic schedule of the fabs operations — not a dispatch or rule-based dispatch list — then you can create an operationally smart factory. Rule-based dispatching systems primarily focus on tools and tool-centric views. Although they incorporate knowledge from current WIP and tool conditions to make decisions better than simple dispatch systems, smart factories are not just about tools and the current WIP at them. Smart factories use the status of every tool and lot in the factory to make fab-centric optimizations instead of tool-specific optimizations. Once you have a digital twin, you’re optimizing for global functions such as line linearity and on-time delivery. These functions are not just about the moment. The transition to a smart factory thus represents a huge philosophical change. When you know exactly what’s going to happen in a factory over the next 12 hours for every single lot, every single wafer carrier, and every single entrance port of every tool in the factory, then you suddenly have control over the factory’s idle time. You know when you can optimally perform PM (preventive maintenance). You know how to best redirect material or labor resources to maximize output. You can create a smart schedule for every maintenance person in the factory that comprehends each person’s skill set and tool downtime so that there’s no negative impact on the factory’s productivity. You can only do all of this when you know the future. Figure 2 illustrates the opportunity. Imagine that a factory contains 1,500 tools. Use of these tools is scheduled for the next twelve hours. The information depicted in Figure 2 encompasses process changes from one chemistry to another, implant changes, reticle changes, and the status of every single consumable for all 1,500 tools. The white spaces that appear between processes in Figure 2 represent opportunities to intelligently schedule events such as maintenance to maximize factory productivity. Figure 2: Smart scheduling permits factory-wide optimization to maximize productivity. Once you have a schedule, you need to translate that schedule into actions or movement. It’s not easy to do this and most material-control systems today make overly simplistic decisions based on modeled assumptions and typical cases rather than the actual time each lot needs to be at a precise location, which can only come from a schedule. Once the data from all of the tools is connected, a smart scheduling system can use the digital twin to make far better process decisions. The larger the factory (or more complex the factory), the more important it is to make smarter decisions. Note: SEMI has a Smart Manufacturing Technology Community. For more information or to get involved, click here. If you would like to discuss Smart Manufacturing more with John directly, he can be contacted at [email protected]. John Behnke is general manager of the Final Phase Systems product line at INFICON.