ROI

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.

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.

I recently spoke with Chan Pin CHONG, Executive Vice President and General Manager of Products and Solutions at Kulicke Soffa, about how smart manufacturing is driving new production efficiencies in the semiconductor industry. During our conversation, he also provided practical steps for factory operators to follow in evaluating their smart manufacturing needs in order to ensure successful implementation and discussed the potential payoffs. Based in Singapore, Kulicke Soffa is a leading global provider of ball bonding, advanced packaging, wedge bonding, and electronic assembly equipment for the semiconductor, power and automotive industries.Ng: Industry 4.0 and smart manufacturing are critical to the growth of the semiconductor industry. What does the smart manufacturing movement mean to you or Kulicke Soffa?Chong: The future of smart manufacturing is the vision of building a digital connected factory to drive new manufacturing efficiencies by combining physical and cyber technologies. Industry 4.0 integrates discrete systems and harnesses the power of large volumes of data to move towards greater automation.At K S, we define smart manufacturing across the following four key areas embedded in our roadmap for all K S products, from wire bonders and advance placement tools to pick and place machines: Interoperability – This is about machines, devices and sensors connecting to each other. In fact, the very basis of smart manufacturing is that all devices are connected. Information transparency – Through simulation, various artificial intelligence (AI) tools use contextual information to emulate the actual world. Technical assistance – Robots or machines support humans in making decisions or solving problems. Autonomous decision-making – This is our vision that robots or machines can learn from machines to make decisions on their own. Ng: Please elaborate on some of these areas and how they’re the relevant to smart manufacturing. Chong: The need for machines, devices and people to communicate with each other forms the basis of connectivity, the idea of all machines communicating with each other or a host. Connectivity protocols now in place for machine-to-machine connectivity include SEMA, SECS/GEM, SEMI-ELS and IPC-CFX. Machine technology uses various sensing technologies. For example, for a pick and place machine such as SMT platform on K S Hybrid, the algorithm to recognize and align processes is part of the sensor needed in each machine before to can process and add thousands of components to the substrate or panel. In a wire bonder, the ultrasonics or EFO signal can provide some form of sensing technology for a machine to detect process conditions. Importantly, these sensing technologies can be used to collect feedback for process improvements.One example of how K S machines are connected to the host is our use of an intermediate server or host named KNeXt to connects to all assembly equipment in the fab. The equipment can then, in turn, connect to an external secured cloud or K S Global Cloud.Ng: What are the objectives for smart manufacturing?Chong: The ultimate goal is to achieve higher factory productivity or better OEE (Overall Equipment Effectiveness) by improving machine yields, productivity and efficiency. The key is to leverage AI, 5G, the Internet of Things (Iot) and other industry 4.0 technologies to drive automation and process improvements. Ultimately, each factory must meet productivity, yield and cost goals. Smart manufacturing enables factory operators to meet these goals. That is the focus of smart manufacturing.Ng: What is the biggest potential benefit of smart manufacturing?Chong: Smart manufacturing uses data to predict outcomes of a process step or machine operation. Once data is available in the global cloud, analytics can start to build data sets to run statistical modelling and examine factory operation trends. We can also use the data to identify past machine behaviors in order anticipate outcomes, including undesirable ones that we can then prevent.In the SMT example, if we can systematically examine days or weeks of historical performance, we can plot some statistical variations in the process specifically to a pick or placer or a robot and anticipate or avoid problems. However, all sensors must be in place in the bond head or the robot so that we can detect changes or variations in the robot’s movements.Kulicke Soffa smart manufacturing facility Ng: What are some recent factory improvements smart manufacturing has enabled? Chong: Kulicke Soffa has contributed to the hierarchical architecture of the smart factory and key technologies. COVID-19 is driving demand for greater factory connectivity, and K S offers solutions that are key to remote management and full control of smart equipment from a central control and embedding Internet of Things (IoT), big data, cloud computing and sensors in manufacturing. Using these technologies, a small smart factory can be remotely operated and managed.With COVID-19 limiting air travel around the world and access to support engineers, the need has grown for remote machine access to reduce the downtime per machine. Remote factory access enables off-site engineers to remotely identify and diagnose machine problems.Ng: What are barriers to faster adoption of smart factories?Chong: While most smart factories are capable of network connectivity and data collection, a key challenge is the lack of a business model for smart factories and smart equipment. Most factories must justify major capital investments by demonstrating ROI (Return of investments) potential. Capital improvements for every factory usually take several years to implement and are based on a complex business model. Factory connectivity requires substantial investments and years to implement. The same is true of the cloud infrastructure buildouts necessary to generate big data and meaningful analytics. The executive mandate for factory management to install capability usually calls for specific business targets in the planning stage.Another longstanding barrier to entry is the lack of compatibility of existing tools with new factory protocols, raising the question of whether the cost of replacing legacy tools justifies the need for a smart factory. If new factory investment is required for the latest tools to support the production of new products, the ROI will be much easier to justify.Ng: How is AI is important in smart manufacturing?Chong: AI interprets and learn from data to perform tasks and meet specific goals. Good examples of AI implementations include Amazon’s Siri and Alexa voice-command devices and self-driving cars being developed by Google and Tesla.At K S, over the years we’ve implemented AI in our smart wire bonders to reduce human intervention in our ProCu-7, PSP-2, ProCu Loop 2, Pro Bump and overhang processes.Thanks to AI, with senses of signals from the bonder, we can reduce the amount of parameters that an engineer or technician have to do trial and error. With on bonder metrology, PBI, loop height, wire sway features, AI allows us to measure process efficiency and provide feedback.Over several years of AI development, we have leveraged the technology to monitor machines and provide real-time performance feedback in order to provide better closed loop control such as short tail recovery in our bonder process. We can also use the data to predict machine behavior, monitor its health and track maintenance. Ultimately, AI enables fabs to improve manufacturing efficiency, productivity, yields and device quality.Ng: What’s an example of how AI has solved your manufacturing equipment problems?Chong: We’ve used AI to set RPM (real time monitor) limits, identify defective P-parts and monitor various conditions such as wire size and capillaries. These types of cases can arise in any manufacturing environment as humans make process mistakes or use the wrong part for a machine. With AI, we can prevent these problems and reduce the risk of further material lost from the wire bonding process.Ng: What advice do you have for factories looking to implement smart manufacturing systems?Chong: To build a smart factory, start by focusing on a clear set of business objectives and how smart manufacturing will help minimize or eliminate current factory inefficiencies. In other words, start with the end in mind – the problems that needs to be solved and the business goals – and identify the information you need to demonstrate ROI. Do you need to resolve, automate or improve processes or just to be more efficient? Before investing millions or billions of dollars to build a smart factory, identify those clear goals upfront. Then map out the particulars of implementation to avoid major problems around standards, protocols and connectivity.Bee Bee Ng is president of SEMI Southeast Asia.