Test

Demand for hi-tech manufactured goods is at an all-time high and is expected to grow significantly in our new digital age, COVID-19 economy. This is especially true for semiconductor chips. Chip manufacturers have been working to meet this demand by building new factories and by optimizing processes and equipment in existing fabs. While there is much media coverage about new factories planned by leading-edge chipmakers and government investments in the semiconductor sector, greenfield fabs entail significant capital expenditures and are sometimes fraught with complex political concerns. As a result, they can take several years to complete and reach their planned production capacity. Instead, the semiconductor industry needs to optimize existing factories in order to increase productivity and yield and meet growing demand by implementing smart manufacturing solutions. Smart manufacturing solutions will inherently reduce costs with more efficient and automated processes, and those savings can be reinvested for the next wave of solutions. Chip Industry on the Bleeding Edge Semiconductor manufacturers have always been focused on bleeding-edge technology to outflank strong competition and build the best products – faster and cheaper. Today, pioneering organizations are using data to optimize manufacturing processes and equipment, a practice known as Smart Manufacturing. While there are many definitions of Smart Manufacturing, the essence is maximizing the utility of big data generated in these factories by leveraging three pillars: Sensing, Connecting, and Predicting. It is not just the digitization in manufacturing, but it is also about turning the data into actions that generate value – an effort the SEMI Smart Manufacturing Committee is driving based on the three pillars. Optimizing return on investment is the ultimate goal. SEMI Smart Manufacturing Initiative activity is based on three pillars that support the goal of increasing ROI. Making the Right Decision, Faster Smart manufacturing practices enable organizations to make the right decisions and take action faster based on insights generated from real-time and historical data. This requires data management technologies and applications that can process, analyze, and act on information instantly. It has become ever more difficult to process and discern the relevant data or signal from the vast volume of data, perform analytics or develop new ML or AI analytic tools, and then make the critical decisions to solve problems as close to real-time as possible. Who’s Responsible – IT or OT? In the past IT (Information Technology) and OT (Operations Technology) were separate entities within organizations, with IT focused on storing large amounts of data for enterprise systems and OT concentrated on using data to perform specific functions. Smart Manufacturing often demands combining IT and OT, difficult in rigid organizations that operate the two organizations independently and lack the infrastructure to implement comprehensive solutions. Success requires executive leadership sponsorship, motivated technical personnel and, most importantly, a clear deliverable on the value in implementing Smart Manufacturing. Many organizations have introduced top-level leadership positions such as a Chief Information Officer or Chief Data and Analytics Officer to address this convergence and many of these leaders are embracing Smart Manufacturing practices. The SEMI Smart Manufacturing community includes many of these leaders and therefore has highlighted the importance in the return on investment for Smart Manufacturing solutions. Read more about IT and OT convergence and note that Smart Manufacturing is synonymous with Industry 4.0. The SEMI Smart Manufacturing Initiative covers the entire supply chain. Get Smart in Smart Manufacturing While new technologies and applications are being created to deal with mountains of data, it is the underlying methodologies and practices that are key to a successful Smart Manufacturing deployment. SEMI, the trade association representing the electronics manufacturing and design supply chain, is in a perfect position to evangelize Smart Manufacturing experiences and best practices for the entire manufacturing community. The more than 30 member companies participating in the SEMI Smart Manufacturing Initiative bring more than 500 years of collective experience and knowledge to the topic. Many segments of the supply chain participate in the SEMI Smart Manufacturing Initiative including packaging, assembly, SMT and PCB assembly, test, software, data management, sensor and material suppliers. Learn How to Manufacture Smarter SEMI SMART Manufacturing is hosting two great conferences in the coming months – the Global Smart Manufacturing Conference (GSMC) and the SEMICON West Smart Manufacturing Pavilion. As a leader of the organizing committee and chair for the SEMICON West Smart Manufacturing Pavilion, I encourage people who want to learn how to implement Smart Manufacturing or expand their knowledge of Smart Manufacturing to attend these events. The GSMC will feature keynotes highlighting the value of Smart Manufacturing, offer tutorials on the three pillars, and introduce several case studies for each of the pillars. Thirty-two organizations – ranging from global cloud providers, semiconductor factory operators, leading equipment vendors and software application solution companies – will present. See the full agenda here. The SEMICON West Smart Manufacturing Pavilion will compliment GSMC by showcasing a number of use cases that highlight the value of Smart Manufacturing. Panel discussions will deep dive into the challenges of implementing these best practices and the direction smart manufacturing is taking in the coming years. Our goal for these events is for you to take this knowledge back to your companies, implement and improve on the detailed solutions highlighted at the conferences, and return next year to share your success stories with the community. See you soon, in person or virtually! About the Author Bill Pierson is VP of Semiconductors and Manufacturing at KX, leading the growth of streaming data analytics in this vertical. Bill is also a chair for the SEMICON West Smart Manufacturing Conference and an active team member of the SEMI Americas Chapter. He has extensive experience in the semiconductor industry including previous experiences at Samsung, ASML and KLA. Bill specializes in applications, analytics, and control. He lives in Austin, Texas, and when not at work can be found on the rock-climbing cliffs or at his son’s soccer matches.

AEM Holdings Ltd, a Singapore-based multinational corporation, is listed in Forbes Asia’s 200 Best Under A Billion 2019 and 2020 spotlighting small and midsized companies in the Asia-Pacific region with sales under $1 billion. AEM clinched the Singapore Business Review Technology Excellence Award 2020 for Analytics-Semiconductor and the Singapore Business Awards Enterprise Award 2019/2020. These achievements are testament to AEM’s vision and innovation and the company’s contributions to the increasingly complex testing of chips in a rapidly evolving technological world. I spoke with AEM CEO Chandran Nair, a new Regional Advisory Board (RAB) member of SEMI Southeast Asia, about the company’s intelligent test and handling solutions, its role in digital transformation, the company’s key role in the smart manufacturing movement and the growth prospects for Singapore’s electronics sector. SEMI: AEM’s application-specific, intelligent system test and handling solutions for semiconductor and electronics companies serve the advanced computing, 5G and AI markets. How do you differentiate your solutions from those offered by competitors? Nair: A key differentiation for AEM is that we work closely with our customers to develop application-specific integrated test and handling solutions that meet their needs in a scalable manner from lab to production. We offer our customers customized, full-stack test and handling solutions that give them the agility to accelerate their delivery cycles and enhance product quality. Over the years, AEM has developed and acquired world-class technologies in instrumentation, test, automation, robotics, optical inspection, high-end thermal control, and software. These technology pillars, along with our deep know-how to customize test and handling solutions using the technology pillars as a platform, enable AEM to meet the fast-changing needs of our customers faced with the challenges of testing heterogeneous and complex devices. In addition to investing in technology, AEM has also invested in delivering application-specific solutions to meet customer demand. Our recently announced acquisition of CEI with its manufacturing capabilities in Vietnam and its specialization in low-volume, high-mix manufacturing increases our geographical reach and our ability to quickly turn application-specific test and handling solutions to be deployed. We have a unique and differentiated approach that enables our customers to test high-performance computing devices, automotive devices, and mobility devices with maximum test coverage, cost-effectively, in a manufacturing environment. Our experience in serving the high-performance computing market that traditionally drives advancements in thermal control also puts us at the forefront of delivering comprehensive thermal management, vision, and deep automation and test solutions for the computing, automotive, and mobility markets. AEM also has a strong instrumentation portfolio, including high-density digital instruments and mixed-signal and protocol-aware instrumentation that is well-suited for ATE solutions for SoC, high-power devices, and CMOS image sensors. Over the last few years, we have also established leadership positions in developing and deploying application-specific test solutions for MEMS devices and offering wafer and frame probing stations suitable for R D, wafer sort, and final test. We form strong partnerships with our customers, provide them with end-to-end support in product development, and take them through the entire life cycle process from concept to mass production. Chandran Nair and Goh Meng Klang, vice president of operations, at the AEM manufacturing site in Singapore. (Photo credit: AEM) SEMI: Digital transformation is powering strong growth of advanced computing, 5G and AI. Will AEM be expanding its AEM manufacturing plants in China, Malaysia and Singapore to meet rising demand for these technologies in the coming years? Nair: In regards to manufacturing, AEM currently has manufacturing facilities in Singapore, Malaysia, the U.S., Finland, and China. With our recently announced acquisition of CEI, we will add manufacturing capability in Vietnam and Indonesia. AEM will continue to expand manufacturing appropriately to give our customers cost-effective solutions while maintaining our proven track record of delivering on time and scaling rapidly in times of crises like the pandemic or geopolitical disruptions. As for advanced technologies, the three key factors that will bring the full potential of 5G to fruition are 1) cost-effective, high-powered processing devices at the edge, 2) easy access to high-bandwidth communications, and 3) cost-effective sensor technology. Semiconductors are the primary drivers of these three key success factors. As devices become more complex and our reliance on semiconductor-powered devices in all aspects of our lives deepens exponentially to include mission-critical applications, AEM’s role is to ensure that our customers' electronic and semiconductor devices are shipped thoroughly tested, safe to use, and highly reliable. It is imperative that, as a testing company, we find innovative ways to help our customers test their products with maximum coverage and minimum cost. To do this, we are focusing our R D efforts and investments to continue building on our key technology pillars to ensure that we stay ahead of the curve when it comes to test and handling solutions. We prepare our customers to test increasingly complex devices manufactured on the latest process node. SEMI: During your career you’ve driven projects in test and automation and more recently robotics solutions for ports, logistics warehouses and transport. With robotics and automation a key part of Industry 4.0, what role do AEM solutions play in powering the smart manufacturing movement? Nair: The smart manufacturing movement is powered by semiconductors, software and increasingly by artificial intelligence (AI). Test is at the heart of the process of ensuring that semiconductor and electronics devices reach the consumer well-tested for reliability. With our vision of enabling A Zero Failure World, AEM addresses the necessity for safe, highly reliable devices. The semiconductor companies themselves are adopting smart manufacturing methods. AEM’s tools are Industry 4.0-ready, and we continue to invest in machine learning and data analytics, which are integral to the future of test. Our tools are automated and feature embedded sensors to provide our customers with data about tool usage, the state of a machine’s health, and more. Our tools are connected to our customers’ manufacturing automation platforms. Additionally, we continue to invest in our ability to better slice and dice test data to understand trends and patterns to help our customers analyze data and make decisions faster. SEMI: You also have experience heading autonomous vehicle projects. With the COVID-19 pandemic hastening digital transformation, do you see an acceleration in the development of fully autonomous vehicles and smart manufacturing? Research and development efforts for autonomous vehicles (AV) continue at a fast pace worldwide. With shutdowns and restricted movement rules globally, the pandemic has hastened digital transformation in many ways. The delivery of goods and services is transforming, and AV will surely play a part, especially in secure environments for autonomous transport. The pandemic has accelerated the development of autonomous vehicles and smart manufacturing technology in automation-friendly environments like factories and ports. SEMI: At the recent Global Technology Summit hosted by SEMI, you spoke about testing innovations to meet the demands of highly complex devices. Please elaborate on innovative testing solutions versus traditional testing? Nair: AEM offers a disruptive and differentiated solution, one that is driving a paradigm shift to asynchronous, modular, highly parallel, smart testing solutions. ​ The traditional approach of ATEs to test increasingly complex devices on advanced nodes has reached a point of diminishing returns as it gets exponentially more expensive to increase test coverage to acceptable levels. Additionally, as devices get more complex and companies are rapidly adopting heterogeneous packaging technologies, the realization that System Level Test (SLT) is necessary is forcing a rethink of the entire test process. AEM’s provides asynchronous, modular, highly parallel test cell solutions that enable each test cell to run SLT, final test, or burn-in all in one system and its ability to handle hundreds of test cells independently with each test cell testing multiple devices. Our solutions suddenly make comprehensive testing of every complex device cost-effective. Freeing us from legacy ATE allows AEM to provide these innovative solutions to our customers. AEM engineering and manufacturing teams in Singapore at work on semiconductor test and handling systems for global deployment at world-class semiconductor facilities. (Photo credit: AEM) SEMI: Singapore seems to be in the sweet spot of digital transformation. Singapore’s industrial production grew 8.6% year-over-year in January 2021, an expansion driven mainly by a surge in sectors including electronics, and more growth is seen in the year ahead. Digital technologies such as 5G technology and cloud computing together with continued demand for work-from-home equipment is behind this growth. What are the growth prospects for the region’s electronics sector? Nair: Singapore is well-poised to benefit from the current digital transformation accelerated by the adoption of these technologies during the pandemic. Being a safe, well-governed country with strong IP protection, excellent infrastructure, and the rule of law, Singapore is in a great position to play a central role in cloud-based services, 5G, and the semiconductor industry. Singapore’s semiconductor sector output is at a record high, and the prospects for renewed growth in the region are very good. SEMI: As a new Regional Advisory Board member of SEMI Southeast Asia, how is your industry experience relevant to the scope of this role? What opportunities lie ahead for the region? Nair: I am honored to represent AEM in the SEMI’s Southeast Asia RAB. The SEMI RAB can influence policymakers with ideas and information on the current and future needs of the industry. I also believe that SEMI Southeast Asia can cultivate a strong innovative semiconductor ecosystem that helps regional and global growth. I look forward to working with other very experienced and accomplished board members. Bee Bee Ng is president of SEMI Southeast Asia.

A Communication ProblemAs the industry ventures towards a more connected world, the semiconductor test community is facing increasingly stringent performance, quality and reliability targets, particularly in the high-stakes automotive, communications, and medical sectors. It is, therefore, important for device makers to know how their components will perform before their products hit the road, reach for the skies, or get placed inside the body. Access to test data is critical to mitigating failure risks. Yet many challenges are associated with accessing test and manufacturing data. One hurdle is that component suppliers are often reluctant to provide test data for fear of revealing sensitive information about their design and/or manufacturing IP. With customers sourcing their components from multiple vendors, IP leakage is a valid concern and, consequently, a barrier to access. Certainly, these issues can be negotiated contractually, but only after striking the delicate balance between access and cost. Beyond access, the quality of test data itself – which can be fragmented and even corrupted – is not always assured. As a device moves through the typical product flow (i.e., fab to sort to assembly to test), it inevitably changes hands (e.g., from foundry to OSATs). As a result, information about the device can become a patchwork of data where formats vary and certain fields, at times, may get overwritten. These potential gaps in test data flow underscore the need for consistent communications of manufacturing information from one process or stakeholder to the next. While standardization could help, it is currently lacking in many of these critical data-flow chains in the manufacturing, test, and assembly areas. An Industry Alliance Aimed at Solving Test Industry ProblemsEfforts to establish standardized solutions to these test industry issues are under way by the SEMI Collaborative Alliance for Semiconductor Test (CAST) Special Interest Group. CAST activities are currently structured around establishing standards on data formats, communication protocols, and chip traceability.Rich Interactive Test Database (RITdb)While Standard Test Data Format (STDF) is widely used in the semiconductor industry, it does not directly support the new use models in today’s test environment, such as real-time or pseudo real-time queries, adaptive test and streaming access. The STDF V4 record format is not extendible and, because the standard itself can be imprecise, it tends to result in many interpretations. These limitations become apparent when there is a need for more efficient and flexible format to manage “big test data.”The RITdb group has been working on the next-generation format following STDF to allow more flexibility in data types and support for adaptive test. The group aims to provide a standards-driven data environment for semiconductor test including simple standards-based data capture, transport and relationship model for eTest, probe, and final test data. Its work also seeks to support equipment configuration management and operational performance data. More importantly, RITdb enables a real-time streaming model that provides the ability to collect and monitor data/systems from sand to landfill.Real Time Adaptive Test (Courtesy HIR)Work by the RITdb group will ultimately be developed into SEMI Standards. The SEMI Standard spec will be in MS Word while the database itself in a different format. A spec editor will help ensure it is used correctly. The group also plans to expand the spec beyond probe and final test. Meanwhile, the group is working to streamline RITdb and implement different extensions (e.g., tester log, streaming). Additional work will be needed on probe maps and test cases (i.e., be able to run verifiers to validate the spec).Tester Event Messaging for Semiconductors (TEMS)Today, semiconductor testing continues to see a surging demand for real-time data analysis, real-time ATE input and control of the test flow to improve test yield, throughput, efficiency, and product quality. At the same time, test equipment and test operations around the world use a diverse range of data formats, specifications, and interface requirements that drive up customer service and application engineering costs for ATE vendors, OSAT companies, IDM test operations, software providers, and handler equipment. A common ATE hardware and software communications interface would help reduce the cost, time and complexity of integrating ATE equipment into data-intensive test operations.Overview of Test Cell CommunicationThe TEMS group was chartered to develop a standardized ATE data messaging system based on industry-standard internet communication protocols between a test cell host and a server. The standard will be limited to ATE data messaging, using RITdb entity types as applicable, standard data format, and control requirements. It will have no impact on other test communication interfaces such as those involving handlers, probers, test instrumentation, and other systems covered by existing standards (e.g., SEMI E30, E4, E5, STDF). The group is developing a set of standards to define a vendor-neutral way to collect test cell data. The primary spec defines the model while a subordinate spec defines the transport layer to maintain consistency with prior standards.Chip ID TraceabilityChip ID Traceability is the most recent group formed under CAST. The group’s formation came on the heels of the 2017 CAST Workshop that focused on Component System Level Test. SLT is widely considered a burden that most chip manufacturers prefer to avoid, but it is essential to achieving lower DPPM (Defective Parts Per Million) goals at system level. The cost to develop and maintain SLT equipment in-house and at OSATS is significant. SLT test engineering requires different skills than regular ATE test engineering. The engineers must understand the final application environment and the data flow that is subjected to the component. Defect causes need to be isolated and communicated back to the vendor or ATE test engineer for corrective action. Mapping such SLT failures back to the ATE production tests is a big, labor-intensive challenge.Component traceability is a big concern. Most newer technologies have ECID (Electronic Chip Identification). However, many product types representing significant volumes do not provide ID traceability. Without component-level traceability, it is extremely difficult to analyze failures and drive corrective action. Additionally, there is basic manufacturing data, including chip ID, that is needed across the supply chain, but this is often blocked and difficult to obtain from suppliers. Such data analysis is difficult across "silos" due to sharing/security barriers. Die-level Identification Traceability (I T) ModelThe Chip ID Traceability group was chartered to develop a standardized approach for enabling traceable die-level identification (ID) throughout the IC manufacturing, test, and assembly processes to the point of use in the final system. The approach defines the use of a simple, unique identifier that IC suppliers and board-level manufacturers can use to communicate about a specific device for the purposes of performance or failure analysis. The identifier will enable suppliers and customers to communicate specific component information and, with NDAs (non-disclosure agreements) in place, send manufacturing data back and forward through the supply chain for data analysis. The group is developing a standardized model focusing on key concepts, behaviors, and requirements for enabling die ID and traceability. The model defines minimum chip ID and traceability for new design and manufacturing implementation as well as for backwards compatibility with existing methods. The resulting standard would apply to different chip configurations ranging from single integrated circuits to multi-chip/3D structures. It can be adapted for use with a range of technologies, ranging from legacy systems to the latest in electronic chip identification (ECID). A copy of the draft proposal can be downloaded here. The Chip ID Traceability group is soliciting feedback to the document. Please contact Paul Trio at SEMI ([email protected]).

Since 2010, 474 companies worldwide have poured $51 billion into developing artificial intelligence (AI) devices, with the bulk of these investments targeting autonomous driving and in-vehicle experiences, according to a McKinsey Company report. With the extraordinary growth potential of AI and automotive electronics, it’s no surprise that IHS Market predicts the Advance Driver Assistance Systems (ADAS) market will reach $67.43 billion by 2025. By 2040, the market research firm expects 33 million autonomous vehicles enabled by AI to be on the road worldwide. Lured by the immense business opportunity, more semiconductor manufacturers are jumping into the automotive market knowing that autonomous driving ICs will face far more stringent reliability requirements than traditional devices. Testing, then, will be crucial for level 5 autonomous driving to materialize since a fully autonomous system will need to rival the behind-the-wheel performance of a human driver even in extreme road conditions like snow and iceWith testing vital to the development of chips for autonomous driving, SEMI Taiwan recently convened experts from IC design and testing-related fields to facilitate cross-discipline collaboration and help inspire innovative solutions to current testing challenges. The early February AI IC and Automotive IC Test Seminar is part of a series of SEMI Taiwan events focused on hot topics including like AI, IoT, smart automotive, smart data and smart MedTech. Following are a key takeaways from the seminar.Paradigm Shift Needed in Automotive Electronics Testing StrategiesDesigners of automotive electronics need to transform their test strategies to match the technical rigors of autonomous driving. The traditional process of build, test, and then fix-for-compliance must change in the era of self-driving vehicles. Adding AI to already electronically complex automotive systems will dramatically increase the number of ICs and sensors in vehicles. Traditional component testing for points of failure is far less rigorous than vetting devices under the countless driving scenarios where they could fail. Testing, therefore, must be holistic. Starting in the development phase of their own electronics systems, automotive electronics designers must work closely with component and other technology suppliers to ensure that designs are tightly integrated and exhaustively tested for interoperability and points of failure under any conditions a human driver would face. Wafer-level Test is A TrendThe cost and time for IC testing have steadily increased to meet the relentless scaling requirements of highly integrated advanced technologies, placing immense pressure on current wafer-level packaging and testing methodologies to maintain cost efficiencies, chip yields and time-to-market speed. The challenges will intensify with the multiple-component parallel testing required for autonomous vehicles. Demands on automotive electronics manufacturers to maintain DDPM quality levels key to smart functionalities, powertrain operation, safety and reliability will also complicate current IC testing methodologies. Nearly 300 professionals from IC design and related fields gathered at the SEMI Taiwan forum to tackle the challenges of autonomous vehicle testing Beyond TechnologyTo fulfill the promise of autonomous automobiles and other AI applications, industry, academia, and government in Taiwan must work together to solve underlying technical challenges, create profitable business models and develop a strong programming and system integration workforce. Taiwan's strong semiconductor manufacturing industry and advanced IC testing capabilities put it in the pole position to help drive the development of advanced automotive electronics essential for autonomous vehicles.Emmy Yi is a senior marketing specialist at SEMI Taiwan.