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The automation of semiconductor factories through digitization is reshaping Smart Manufacturing to streamline the connectivity and orchestration of manufacturing processes across the entire supply chain. But the threat of cyberattacks and viruses looms. An estimated 26 billion smart and connected manufacturing devices are expected to be online by next year. Never before has the need been greater to protect the staggering volume of manufacturing data traversing increasingly intricate supply chain networks.“We are living in the time of digital manufacturing,” said Chen Chi-Hsien, Director of TSMC’s Manufacturing Technology Center. “Processes ranging from assembling equipment and upgrading hardware and software are increasing security challenges for semiconductor manufacturers. With viruses and malware constantly evolving to pose greater threats, all members of the supply chain – from manufacturing and equipment to operating system and software/firmware providers – should work together within the SEMI Smart Manufacturing platform to establish cybersecurity standards across the industry. Doing so will also enhance the development of smart manufacturing and accelerate digitalization.” Representatives from Tongfu Microelectronics, Adlink, NSHC, ABB, TSMC, ASE and Microsoft with SEMI CMO and SEMI Taiwan president Terry Tsao (left to right) Chi-Hsien offered his insights at the SEMI Smart Manufacturing and Cybersecurity Seminar, joining speakers from other leading semiconductor manufacturers including TFME and ASE to discuss the latest smart manufacturing trends and cybersecurity challenges. The April event in Hsinchu also featured representatives from ABB, Adlink, Microsoft, Rockwell, Siemens, Delta Electronics and the National Center for High-Performance Computing (NCHC) offering their views on how the semiconductor industry can speed its digital transformation using various technologies.With its 43 years’ experience in developing international standards, SEMI is committed to serving as the platform to establish universal information security standards for silicon wafer plants and semiconductor equipment, Terry Tsao, SEMI chief marketing officer and SEMI Taiwan president, said at the seminar. Tsao added that SEMI is now in discussions with leading semiconductor manufacturers to establish a communications framework for addressing potential security risks and facilitating the development of risk management and security solutions that safeguard the semiconductor supply chain.This year SEMI will debut its SMART Manufacturing EXPO to gather key supply chain players for critical discussions about security and to feature AI manufacturing and cybersecurity solutions. Co-located with SEMICON Taiwan, September 18-20, 2019, at TaiNEX 1 (Taipei Nangang Exhibition Center, Hall 1), the SMART Manufacturing EXPO will include Smart manufacturing hardware and software providers from around the world for the interdisciplinary discussions and collaboration key to developing strong Smart manufacturing security.For more information about the SEMI Smart Manufacturing Platform, contact Emmy Yi of SEMI Taiwan at [email protected] Yi is a marketing specialist at SEMI Taiwan.

As artificial intelligence’s (AI) sprawling influence reshapes industries from logistics and healthcare to automotive and manufacturing, Taiwan is poised to leverage its cutting-edge capabilities and rich history in semiconductor manufacturing to stake out a leadership position in AI. Taiwan’s semiconductor manufacturing industry accounts for a major share of the region’s GDP and, with its manufacturing prowess, the region is fertile ground for using AI to optimize and even revolutionize chip manufacturing. In an AI and Semiconductor Smart Manufacturing Forum recently hosted by SEMI Taiwan, experts from Micronix, Advantech, Nvidia and the Ministry of Science and Technology of Taiwan (MOST) shared their insights on how deep learning, data analytics and edge computing will shape the future of semiconductor manufacturing. Here are four key takeaways.1. Monitor, Forecast, and PreventToday, tier 1 foundries use AI tools to combine equipment know-how and manufacturing statistics in managing massive Fault Detection (FD) data, much in the way that a car’s tire-pressure monitoring system helps maintain safe inflation levels and prevent accidents. For example, AI enables the real-time collection and monitoring of massive amounts of processing data, then alerts system administrators of any hardware failures or other manufacturing abnormalities.AI also makes it possible to adopt Run-to-Run (R2R) control to automate manufacturing process adjustments and corrections by providing feedback that can drive higher processing efficiency. In addition, virtual metrology replaces manual sampling inspection for comprehensive quality control, enabling foundries to improve yields, reduce costs, and strengthen their competitive advantage.2. Beyond Automation: Edge Computing The evolution of IoT is giving rise to a paradigm shift in the industry as the recognition grows that smart factories must go beyond automation to focus also on intelligence. All information – from equipment status and manufacturing process statistics to on-site environmental data – needs to be collected through sensors. In highly time-critical scenarios, returning all sensor data to the cloud for processing is time-consuming and impracticable. This is where edge computing’s real-time features and lower cost than cloud computing come into play.How does edge computing work in a smart factory? First, a rich trove of data from various devices is collected and integrated via Manufacturing Execution Systems (MES). Software analysis then produces a real-time factory production status before production data is visualized through a combination of system platforms and human-machine interfaces. In the end, the data is analyzed realtime in the cloud so failures can be predicted and prevented to help increase capacity and reduce costs. The approach is even capable of Bill of Materials (BOM) predictions, allowing better collaboration between upstream and downstream suppliers.3. Deep Learning Accelerates AI Deep learning enables autonomous driving, intelligent voice assistance and many other AI breakthroughs. The heart of deep learning is its ability to automatically process and learn data in various formats such as images, video and text with no human domain knowledge. This increases predictive accuracy and efficiency in processing massive amounts of data. Deep learning also enhances the efficiency of human-machine collaboration.4. Taiwan’s Competitive Niche: Industry 3.5Industry 4.0 is not just about improving production management. It also focuses on integrating supply chains, even among competitive companies. For Industry 4.0 to thrive, rival companies must grow together. The first and third industrial revolutions centered on disruptive technologies like steam engines, transistors and digital, while the second and fourth revolutions homed in on competition among various business models, platforms and industry ecosystems.While Taiwan’s strengths include innovation, short time-to-market, low manufacturing costs, and high supply chain management efficiency, the region still lags advanced countries in basic industry and research capabilities. Squeezed by Chinese supply chains and high-end manufacturers in advanced countries, Taiwan should start by carving out an Industry 3.5 niche for the island’s manufacturers. SEMI will continue to facilitate cross-industry connection, collaboration and innovation to help manufacturers seeking higher production efficiency and lower costs incorporate AI as a core competitive advantage. At SEMICON Taiwan 2018, SEMI will unveil its Smart Manufacturing Journey, an exhibition that gathers leading AI companies such as ABB, Advantech, Nvidia, Sony and UPS to demonstrate a comprehensive roadmap for smart manufacturing technologies and applications. For more information, please visit the SEMICON Taiwan website.Emmy Yi is a marketing specialist at SEMI Taiwan.