semiconductor wafers

Babak A. Taheri, Ph.D., the CEO of Silvaco, about the challenges of tuning and optimizing semiconductor manufacturing processes and how AI might be applied to reduce time and costs. Silvaco is a member of the ESD Alliance, a SEMI Technology Community.

Policymakers are increasing semiconductor manufacturing capacity to strengthen supply chains and meet growing demand for semiconductors through robust incentive packages totaling hundreds of billions of dollars. This global effort hinges on semiconductor manufacturing equipment (SME).

A change is underway in the manufacturing sector as the use of curvilinear shapes on photomasks grows, leading to the real possibility of curvilinear shapes in designs. It may just be the start of a revolution away from Manhattan or rectangular shapes to curvilinear shapes. Changing the physical design infrastructure to be curvilinear seems too daunting a task. Are curvilinear shapes in designs a real possibility? I turned to Aki Fujimura, CEO of D2S, a member of the ESD Alliance, a SEMI Technology Community, to further explain the shape of the future. Smith: What is the difference between Manhattan and curvilinear shapes? Fujimura: Manufactured masks and wafers are all curvilinear, even if the input CAD geometries are rectilinear (shown in Figure 1). It’s always been true that nature can’t make 90-degree turns, so sharp corners were always a matter of how closely you looked. These days, at the leading-edge nodes and their required resolutions, wafers and even masks are all visibly curvilinear as you can see in the graphic on the left in Figure 2. Since the 1980s, both chip design and chip manufacturing systems have used axis-aligned rectangles, or “Manhattan” geometries, because 1) that was sufficient to design transistors and interconnect for the most part, and 2) CPU-based computer algorithms can be made much more efficient for Manhattan geometries. Curvilinear shapes can be piecewise linear polygons of some resolution, or spline-like formats that are curvilinear at any resolution, or specific curved patterns like circles and ovals. Figure 1: All shapes on masks and wafers are curvilinear, even if the input geometries are Manhattan. Source: D2S Smith: What are the benefits of curvilinear masks? Fujimura: The manufacturing side of the semiconductor community knows that the best possible process window for wafer lithography is obtained by using curvilinear correction of mask shapes instead of Manhattan shapes. There have been numerous studies on the topic over several decades. The technique to generate purely curvilinear mask shapes is known as inverse lithography technology or ILT and is an advanced form of optical proximity correction (OPC). At a February 2020 eBeam Initiative event, Micron Technology presented a study showing process window improvement up to 85% for advanced memory designs as a result of using curvilinear ILT (shown in Figure 2). Additionally, Ryan Pearman from D2S presented a study at Photomask Japan 2019 showing that it is preferable to move toward a completely curvilinear paradigm, not only because ILT is better, but because the mask manufactured will have reduced variability. Figure 2: Micron Technology explained the benefits of curvilinear mask shapes for advanced memory at the eBeam Initiative event during 2020 SPIE Advanced Lithography Conference. Source: Micron Technology Smith: If the benefits have been known for decades, why is it happening only now? Fujimura: Several things happened at the same time. Multi-beam mask writing is now available. GPU acceleration for general computing has become mainstream. And wafer process window (resilience to manufacturing variation) is increasingly a problem for the leading-edge nodes as we are in the 5nm node, going to 3nm. Curvilinear ILT is needed much more now than before, will soon be needed for EUV lithography too, and is now possible because of multi-beam mask writing and GPU acceleration. Smith: Curvilinear mask shapes enable curvilinear design shapes too? Fujimura: Adoption of curvilinear mask shapes is the first step in targeting curvilinear shapes on wafers. Without curvilinear masks, it is difficult to target and reliably manufacture curvilinear designs. Curvilinear ILT works in the pixel-space to output the desired mask shape to maximize the process window for wafer lithography. A side effect of curvilinear ILT is that it can also take curvilinear targets as input. ILT, most likely GPU-accelerated ILT, works with rasterized input data, so the ILT algorithm itself is not affected even in runtime by having any amount of curvilinear design data. The resulting mask shapes are written in multi-beam mask writers, which write pixels with doses. They too will write curvilinear masks at the same speed as Manhattan masks. Suddenly now, curvilinear designs can be handled by chip manufacturing equally well for the first time in about 30 years. Smith: But curvilinear designs would be hard, right? There are a lot of tools that depend on the Manhattan assumption. Fujimura: Yes, you’re right. We’re not going to suddenly see chips that have curvilinear routing all over the place, or curvilinear intra-connect in standard cells or memory cells. The entire physical design infrastructure that includes place and route, timing, custom layout, parasitic extraction and design rule checking moving to curvilinear design all at once is extremely unlikely. Could portions of these problems be tackled for specific cases over time as “hot spot” solutions? With GPU-accelerated SPICE being available now, as an example, if GPU acceleration is adopted for design, the same transformation that happened in manufacturing can (gradually) happen in design too. The key question is whether it’s worth the trouble. Smith: Is it worth the trouble? Fujimura: I don’t know if it’s worth the trouble for the entire infrastructure. For hot spots, “hot” for various reasons, there are certainly benefits. Jogging a 32-bit bus by one grid is certainly much more economical space-wise with curvilinear shapes. Inside standard cells or memory cells, there are certain types of features that pack better with curvilinear designs. In general, interconnect is the limiter to chip size of course, but there are always critical areas that could use help to shrink. There are manufacturability benefits as well. In general, when something changes so drastically as this for the first time in 30 years, there’s bound to be some innovation that takes advantage of the discontinuity. Let’s see what the combined capitalistic power of the entire community might be able to come up with. The first thing is to let everyone know that curvilinear designs will be manufacturable today. Hear insights from other leading electronic system design industry CEOs at the SEMI ESD Alliance CEO Outlook on May 18, 2021, 2:00pm-3:00pm PDT. Panelists will discuss the state of the industry along with their views of the outlook for the coming years. Registration is free for SEMI members. 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.

International Women’s Day (IWD) is a global day celebrating the social, economic, cultural and political achievements of women. The day is not only the centerpiece of the movement for women’s rights but a unique opportunity to recognize the contributions of women to the semiconductor industry. The first International Women’s Day took place in 1911 when more than a million people in Austria, Denmark, Germany and Switzerland marched to demand equal rights for women including the right to vote and to protest employment sex discrimination. In 1977, the United Nations General Assembly invited member states to proclaim March 8 the UN Day for women's rights and world peace. In recent years, organizations and companies worldwide have sought to use IWD to celebrate the contributions of women to our homes, families, workplaces and communities. The IWD theme for 2021 is Choose to Challenge – a call to draw attention to women’s inequality. It’s also an excellent opportunity for all SEMI members to choose to challenge deep-rooted thinking and behavior in order to grow diversity and collectively commit to increasing the representation of women and women-owned businesses in the semiconductor industry. The double-edged challenge for the chip industry is to grow the ranks of women while retaining those now in the workforce. One in four women are considering leaving their workplaces or downshifting their careers due to work-life challenges stemming from COVID-19, SEMI noted in a recent blog highlighting the Women in the Workplace 2020 study by McKinsey Company and LeanIn.org. One in four! In 2021 it’s important for us to recognize and work to reverse this trend by taking time to encourage, support and celebrate women in the face of COVID-19. A shining example of the enormous contributions to semiconductor industry by women is Dr. Suvi Haukka, a pioneer of atomic layer deposition (ALD) technology. Thirty years ago, Dr. Haukka spied a small note on a university noticeboard that led to her pursuit of a long and highly distinguished career in our industry. The note was a job opportunity with ASM International to research ALD, a role she landed. Upon joining ASM, Dr. Haukka investigated the use of ALD for catalysis applications to modify porous high-surface area materials used in oil refining and polymerization. What was initially a niche application to modify the surfaces of microporous substances and silicon solar cells evolved over time to become a critical materials technology and manufacturing method for coating semiconductor wafers. Working systematically in the lab, Dr. Haukka and her coworkers made fundamental materials and manufacturing process discoveries that advanced ALD material science and manufacturing technologies. An accomplished inventor and technical contributor, Dr. Suvi Haukka was named ASM’s very first Fellow of the Technical Staff in 2018. “Being named an ASM Fellow was a huge moment that made me very, very proud,” Dr. Haukka said. “I have spent my entire professional career working with ALD, and I have been very fortunate to work with many talented colleagues at ASM. “Together we have dedicated ourselves to introducing ALD as a standard means of manufacturing in the semiconductor industry. I believe the award is in recognition of all the valuable work we’ve done over the years.” Dr. Haukka is ASM’s most prolific inventor with more than 100 patents to her name. Her remarkable contributions to the development of ALD chemistry and semiconductor manufacturing process technologies over her three-decade career have made her a highly respected, internationally recognized researcher in the semiconductor manufacturing industry. Bill Olson is the corporate responsibility and conflict materials lead at ASM International N.V. in Phoenix, Arizona. He graduated from the University of Wisconsin-Madison with a Ph.D. in Inorganic Chemistry. Bill has 23 U.S. patents and has published more than 40 technical articles. He can be reached via LinkedIn at www.linkedin.com/in/williamolson.

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.

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