OSAT

Spend any time with Ansys’ John Lee, Rich Goldman or Marc Swinnen and you’ll hear plenty of optimism about the semiconductor industry even though they tick off a long list of looming design challenges. The need for reliable and effective electronic systems, they emphasize, is great and runs through high tech, aerospace and defense, automotive, IoT and 5G with communications being a common denominator. The three are especially bullish these days on changing market dynamics brought on by systems companies building company-specific bespoke, or custom, silicon. These systems companies are building chips with a different perspective and a fresh look at silicon design, a move away from the more traditional segment-specific silicon due to much more complexity. Ansys, a member of the ESD Alliance, a SEMI Technology Community, is a 4,100-employee company with a comprehensive portfolio of multiphysics engineering simulation software for product design, testing and operation products and services. John, Rich, Marc and I focused on Ansys’ semiconductor and electronics segment for our conversation. Smith: When did you notice the move by systems companies to build their own chips? What drives this trend? Lee: The inflection point was about three years ago when hyperscale data center and system companies recognized they needed an enterprise system design platform. They are designing bespoke silicon, driven to do this for cost efficiencies and to avoid relying on outside suppliers. They also want differentiation based on their specific platform needs so they can optimize compute power to their specific needs. Smith: What is driving the trend for multiphysics experience to ensure effective and reliable electronic systems? Lee: The increasing need for multiphysics analysis is acute. The physics of 3D IC, for example, brings in mechanical engineering with the convergence of mechanical and electrical as 3D emerges at the intersection of IC and System. As a result, physics becomes a necessity to analyze the stability of the chip in the package. Goldman: As well, the move to stacked chips, 3D IC and wafer-on-wafer requires thermal, electromagnetic and mechanical analysis in addition to the traditional analysis for function, performance and power. They all need to be analyzed together, not serially. It becomes multiphysics, not multiple physics. Smith: Two distinctly different disciplines – multiple physics and multiphysics – are needed for semiconductor design. How are they different? Why the need now? Swinnen: Multiple physics refers to the sheer breadth of physics that is now needed to analyze from the IC up to the largest system whereas multiphysics refers to the capability to analyze several physical effects concurrently, accounting for their impact on the design and interactions between various physics. Multiphysics are necessary to analyze the full context of the system environment – from nanometers to kilometers – for multi-chip packaging, chip-to-package-to-silicon and systems with multi-domain guidance. Goldman: A self-driving car, as an illustration, includes AI systems-on-chip, solid-state sensors, infotainment systems and radar/lidar detectors that must all work in the rain, the heat and the bitter cold. Smith: Why are design groups being reorganized to include expertise in mechanical and electromagnetic issues? Swinnen: Complexity has exploded, driven by a long list of technical requirements and, perhaps, mischaracterization. Goldman: Just consider the system on chip, mischaracterized by the semiconductor industry. The chip is never a system by itself. Rather, it is a complex component in a larger system and must be analyzed in that context. 3D IC is where this comes together and forces a recognition of physics outside the traditional scope of SoC design. 3D IC chips are much closer together on the board and it takes multiphysics embedded into the workflow of semiconductor design, packaging, system design and 3D IC to ensure they work reliably and efficiently. Smith: What is the solution? Goldman: It’s clear a specialized digital thread is necessary to move disparate groups with expertise in systems, physics and silicon together. Today, these groups or disciplines might not exist in the same company, whether it be a foundry, fabless or outsourced semiconductor assembly and test (OSAT) company. Lee: In order to unify the entire system design environment, a cloud-based, open and extensible heterogenous enterprise compute platform is required. It is similar to the SaaS-based business model and known as Simulation-as-a-Service (also SaaS). While vertical integration of design groups is already taking place at leading system design houses, there have also been advances in electronic design tools. These are starting to offer more comprehensive multiphysics capabilities including thermal, fluid dynamics (CFD), mechanical stress and reliability analysis in a single analysis cockpit. Today’s system designers face two platform challenges: First, they need an environment that is open enough to accept analysis results from multiple sources so that they can be overlapped and cross-analyzed. Second, the design platform must have the capacity to handle the enormous amounts of data generated by the latest 3-nanometer chips and 3D IC systems, and this implies an intimate coupling to elastic cloud computing. The days of an engineer writing Perl scripts and handing it off to someone else are gone. We believe that the industry is responding to this challenge with a new generation of design platforms that a cloud-native, open and extensible to allow heterogenous enterprise design. We are definitely at an inflection point in electronic design today, but the electronic industry has faced these before an we are confident it will master these challenges as well. About Rich Goldman Rich Goldman is director of marketing for the Electronics and Semiconductor Business Unit of Ansys. He holds a Bachelor of Science degree from Syracuse University and an MBA and Master of Science degree in Engineering Management. Moscow Institute of Electronic Technology (MIET)’s first honorary professor, he is also the recipient of honorary PhD degrees from Russian-Armenian (Slavnoic) University and State Engineering University of Armenia for contributions to the advancement of Armenia’s high-tech education and economic ecosystem. Rich served on EDAC’s board of directors. About John Lee John Lee is general manager and vice president of the Ansys Electronics and Semiconductor Business Unit. Lee co-founded and served as CEO of Gear Design Solutions (now Ansys), developer of the first purpose-built big data platform for integrated circuit design. He cofounded two other startups (Mojave Design and Performance Signal Integrity), which successfully exited into companies now part of Synopsys. He holds undergraduate and graduate degrees from Carnegie Mellon University. About Marc Swinnen Marc Swinnen is director of product marketing for the Electronics and Semiconductor Division of Ansys. He holds Master degrees in Electronic Engineering and Industrial Management from KU Leuven, Belgium, as well as an MBA from San Jose State University. 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 SEMI Smart Manufacturing Americas Chapter, a key driver of the Global Smart Manufacturing Initiative, accelerates awareness of digital and data-driven strategies and implementations to help speed adoption of smart manufacturing. In 2021, the Chapter will focus on expanding its work across the industry to include academic and research initiatives. The semiconductor industry saw an unprecedented focus on improving digital monitoring of manufacturing activity in 2020, partially due to COVID-19. The Americas Chapter shared case studies on new tools and techniques for social distancing in fabs, aides for remote maintenance, and tips for remote workers. The Chapter also introduced its three pillars of Sensing, Connecting and Predicting and offered related programs. The Global Smart Manufacturing Conference (GSMC) highlighted the significance of universities and research institutions in the development of smart manufacturing with their focus on joint research for broad dissemination. To help drive smart manufacturing advances, at GSMC several offered non-proprietary tutorials on topic including the following: Integrating sensors for acquisition – CEA-Leti Applying new AI and ML tools and strategies to manufacturing – Binghamton University Digital tools for planning, qualifying and management and scheduling in fabs – MINES Saint-Étienne. Adding AI tools to robot work in a smart factory – KAIST Institutes By continuously highlighting the activities of these and other institutions through presentations, interviews, articles and blog posts, we will draw more attention to what is on the horizon for smart manufacturing in 2021. The SEMI Smart Manufacturing Americas Chapter also plans to elevate activities important to the Outsourced Semiconductor Assembly and Test (OSAT), Surface-Mount Technology (SMT) and Printed Circuit Board Assembly (PCBA) segments of the industry including programs on inspection, traceability and the SEMI SMT-ELS Standard for SMT automation. Thurston Taylor, marketing expert at Tokyo Electron and Vice Chair of the Americas Chapter, notes that “With increasingly more demanding requirements for bump, assembly and test, smart manufacturing and applied data science are necessary to achieve back-end goals now and in the future.” Also, many companies are implementing smart manufacturing applications and assessing various strategies to increase their smart manufacturing capabilities. Members of the Americas Chapter plan to review and develop self-assessment documents and maturity models that apply to front-end wafer fabs all the way through packaging and assembly facilities. “Moving forward it is imperative for all of us to up the intensity on specific ROI vectors such as quality, cost, productivity, sustainability and safety leveraging our smart manufacturing SEMI framework of Sensing, Connecting and Predicting,” said noted Bobby Mitra, worldwide director of Smart Manufacturing at Texas Instruments and Americas Chapter Chair. “By offering special flagship events, invited talks, ROI case-studies and ROI criteria in maturity models, we’ll bring high value to the smart manufacturing industry.” Chapter members also will begin mapping the skills needed to implement and support increasingly digital manufacturing capabilities, including any new skill sets, to help companies develop their hiring, training and management strategies. The mapping effort aims to support companies in building a strong pipeline of employees who can efficiently manage and operate smart manufacturing facilities. For its part, the Americas Chapter’s Go Green Subcommittee will focus on applying smart manufacturing technology to reducing the electronic industry’s carbon footprint by accurately tracking energy waste improving overall fab efficiency. Stay tuned for details on activities planned for our chapters in Europe, China, Japan, Korea, Southeast Asia and Taiwan. To learn more about each chapter and how to get involved, please visit the SEMI Smart Manufacturing Hub and sign up for our newsletter. Ayo Kajopaiye is senior project coordinator, Collaborative Technology Platforms, at SEMI.

OSATs (outsourced assembly and test companies) currently handle the bulk of assembly and test activity for the worldwide semiconductor industry. These companies’ factories have a manual operation legacy: Decision-making is manual. Materials and WIP (work in process) movement is manual. Practically everything in these factories is done manually. In addition, OSAT factory environments typically present many physical constraints with respect to equipment layout, material carriers and storage. All of these constraints present challenges when trying to automate material handling in these factories. OSATs also operate with far smaller gross and operating profit margins than IDMs, yet the percentage of worldwide semiconductor product handled by OSATs is currently increasing from year to year while the IDM share is decreasing. The combination of increased business volume with lower margins encourages OSATs to automate their factories, but there are challenges that must be overcome. Technical challenges abound OSATs face many technical challenges when trying to automate production. First, installed legacy equipment in these factories is typically 25 to 30 years old. This older equipment was simply not designed to accommodate automated materials handlers. For example, access doors on older equipment make automated WIP delivery and pickup nearly impossible without significant modifications to the equipment. Second, these factories are not equipped with the infrastructure needed to support automation. To start with, most of this older equipment is not SECS/GEM compliant. (SECS/GEM is the semiconductor industry's standard equipment interface protocol for equipment-to-host data communications.) This capability must either be retrofitted to the existing equipment or some other means of extracting required data from the equipment – getting it from the PLCs controlling the equipment, for example – must be employed. Similarly, the WIP carriers currently in use – wafer carriers, trays, magazines, and the like – are not designed for automation. In contrast to the semiconductor wafer fab industry, it seems that almost every company in the OSAT domain has a different idea concerning what a carrier should look like. In particular, there’s no such thing as the standard 300mm FOUP (Front Opening Unified Pod), which carries wafers from one tool to the next inside of semiconductor fabs. The variations in carrier shapes, configurations, and even gripping handles in the OSAT domain thwarts progress in OSAT factory automation. How do you design a materials-handling robot with the grippers and flexibility needed to adapt to all of these different carriers? It’s a difficult question and an expensive proposition. OSAT facilities themselves are designed for human-based materials handling, not automated materials handling, simply because they were designed at a time when automation was not contemplated. As a result, the equipment in these facilities is packed very closely together (to reduce floor space costs), as shown in Figure 1. Figure 1: Equipment in a test facility is often tightly packed, which impedes the adoption of automated materials handling. It’s very difficult to add automated materials handling equipment at floor level or even at ceiling level in these OSAT factories, as is frequently done inside of a semiconductor wafer fab. You will not see AGVs (automated guided vehicles) moving around inside of legacy OSAT factories because there’s simply no room for them to move around. Tackling the challenges So, what can be done to handle these all of challenges? You must start by understanding the nature of the operations taking place inside of the factory. As stated above, most of these operations are currently performed manually. All of the decisions and the materials transport is performed by humans. There’s simply no way to transition from a fully manual operation to a fully automated operation in one jump. It’s too far a reach. A significant amount of work is needed just to reach the level where automated decision making is possible. Key systems must be added to enable this level of automation. Many companies tried and failed to automate assembly and test in OSAT facilities about 25 years ago. They failed because the required data could not be extracted from the equipment in use and, therefore, there was no data to drive good decision-making. Too many required systems were simply lacking. For example, when AGVs were added, one or two operators had to walk along with the AGV to tell it what to do. There was no benefit from the automation in this example. There was no successful path to automation at the time. Standards needed One of the major obstacles to automating assembly and test in OSAT facilities is a lack of standards for carriers, robotics, layout, and facilities. Many front-end standards exist. The SEMI-E82, SEMI-E84, and SEMI-E88 standards designed for semiconductor fab front ends might apply, but they need to be adapted to requirements for OSAT back-end facilities. In addition, OSATs have special needs that may demand new standards. This is a real opportunity for SEMI and its constituents. An architecture for full assembly and test automation involves four layers, as shown in Figure 2. Figure 2: Full automation for assembly and test involves four layers. Starting with the data layer at the top of Figure 2, a fully automated facility needs to have database systems in place that can supply all of the data needed for making smart scheduling and dispatch decisions. These databases then feed smart, automated scheduling and dispatch applications in the logic layer. The scheduling and dispatch applications then send control commands to the automated transport and materials controllers and the automated equipment handlers in the control layer. You need to start at the top of the diagram to put all of this automation in place. The automated equipment and equipment controllers need commands from the scheduling and dispatch applications, which in turn need data from the databases to make smart decisions. So it’s the data layer and the systems that feed data to this layer that constitute the starting point for the journey to full automation. A significant amount of simulation is needed to develop optimal facility workflows. These simulations are driven by data extracted from the databases. One of the frequently ignored facets of automation is the need for backup plans. For example, what is the backup plan when an AGV fails and cannot deliver material as scheduled? Simulation helps create contingency plans for such events. A case study Applied Materials has worked with assembly and test factories in deploying full automation. Towards this objective, the factories have worked on many modifications (physical and systems) to enable this automation. For example, a die-attach machine was retrofitted for automation by removing all of its equipment doors so that an AGV could load the machine and extract completed work. Additional modifications permitted the mounting of multiple magazines on the die-attach machine’s input and output to provide the buffering needed to smooth the flow of work through the machine. Finally, simple instrumentation and networking was added to the machine to aid in making WIP delivery and pickup decisions. These machine modifications addressed only the bottlenecks in this particular machine, but even these simple modifications helped to reduce the incidence of manual handling errors, such as the misalignment of magazines or trays. Modifications like these also reduce the need for human operators, which in turn reduces operating costs. Such types of incremental enhancements in automation capability have been implemented by leading-edge companies over the past few years. Conclusion Deploying full automation for assembly and test is not only feasible, it’s necessary for future profitability. OSATs must address the challenges of rising manufacturing volumes and thin margins by reducing manufacturing errors and increasing quality. (The quality requirement is increasingly driven by the automotive industry.) Trailblazing deployments have shown that it’s possible to automate these manufacturing lines successfully. While IDMs have a longer history for manufacturing automation, OSATs are now traveling along the same path due to their rising share of worldwide manufacturing volumes. On that path, they’ll need to develop experience and new standards tailored to their unique needs. Shekar Krishnaswamy is a senior manager at Applied Materials responsible for business development and pre-sales of factory automation products and solutions. He has over 27 years of experience in all aspects of semiconductor manufacturing including wafer fab manufacturing, bump, assembly and test. His specific areas of expertise are traditional industrial engineering methods as well as systems-related methodologies such as modeling, scheduling, dispatching and factory automation. Prior to Applied Materials, Shekar held senior technical and management positions at IBM, Motorola and AMD, including management of corporate operations research departments supporting factory and service groups. Shekar has a bachelor’s degree in mechanical engineering and a master’s degree in industrial engineering and operations research. Note: SEMI has a Smart Manufacturing Technology Community. For more information or to get involved, click here.