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Over the next five years the Taiwan government plans to invest NT$1.546 billion to build the workforce direly needed for future semiconductor industry research and development. The largesse is a tribute to efforts by SEMI president and CEO Ajit Manocha to enhance the competitiveness of the semiconductor industry by stressing the importance of talent development during his annual visits with the Taiwan president. He has been instrumental in bringing together Taiwan government agencies and local industry representatives – two players in developing the talent pool of the future – to discuss workforce initiatives.As the talent gaps threatens to choke the long-term growth potential of the chip industry, Manocha has emerged as a passionate champion of workforce development. In a letter to more than 2,000 semiconductor companies worldwide, he urged to executives act together to build the workforce vital to industry growth. In 2018, he met with Taiwan President Tsai Ing-wen to discuss ideas for attracting and retaining skilled workers to help ensure Taiwan remains a top investment destination for high-tech multinationals.In early 2019, SEMI Taiwan established its SEMI Taiwan Workforce Development Council to promote talent and career development. Already, the group’s work is resonating in the global semiconductor industry. In September last year, Manocha joined executives from industry heavyweights ASE, MediaTek and TSMC in a visit to President Tsai to urge the government to pursue industry sustainability through talent development. President Tsai responded by instructing her staff to review government resources available for talent development, help drive public-private dialogue and partnerships, and form talent development projects involving the government, industry, academia and research institutes.To carry out comprehensive workforce initiatives, SEMI Taiwan continues to work with the National Security Council and the Executive Yuan (the cabinet). We also launched the Semiconductor Industry Development Council in partnership with leading high-tech companies in Taiwan including ASE, TSMC, MediaTek, PSMC, VIS, MXIC, Nanya, Etron and UMC. Focused on developing semiconductor talent and technology, localizing equipment sourcing, and improving cybersecurity, the council has formed the following seven initiatives: Make existing government talent development programs more flexible to better meet the industry’s workforce needs. Recruit outstanding scholars and leading experts in scientific research, and solicit world-class scientific research teams. Extend age restrictions and other requirements for the Einstein Program (established by the Taiwan MOST, Ministry of Science and Technology) to attract outstanding foreign scholars to Taiwan. Establish a domestic semiconductor research ecosystem and provide sufficient research funding to cultivate R D talent. Strengthen female education in STEM (science, technology, engineering, mathematics) and encourage women to re-join the workforce to help meet the industry’s workforce needs. Continue to promote MOST University-Industry Collaboration Projects (Large Alliance) to connect the upstream academic and research sector with downstream industries. Encourage cooperation between science and technology universities and the chip industry to develop the talent necessary for smart manufacturing to thrive. SEMI’s advocacy efforts with the Taiwan government, the industry and academia are clearly paying off. The Executive Yuan recently announced three major talent development strategies – expanding the talent development capabilities of higher education institutions, promoting industrial-academic cooperation and encouraging businesses to strengthen recruiting efforts and increase funding for semiconductor talent development.The building momentum includes plans by the Taiwan Ministry of Education plans to establish semiconductor technology research centers at several national universities. By passing the sandbox law and loosening regulations organizational personnel, finance and education, the government is freeing up more funding to support semiconductor industry talent development. The ministry also plans to gradually expand the number of students enrolled in STEM curriculum and continues to promote talent training programs and recruiting strategies to help close the workforce gaps and reduce related industry risks. A highly skilled workforce is indispensable to the development of the semiconductor industry and among the most strategic resources in any region. It’s only through long-term partnerships between the government, industry and academia that impactful and sustainable workforce development goals and initiatives can be developed to help the chip industry realize its full potential to innovate and solve some of the world’s greatest challenges. The programs are key to the ability of Taiwan’s semiconductor industry to sharpen its competitive edge. More importantly, they are also the center of gravity in the region’s pursuit of its position as the global semiconductor hub. Jo-Ann Su is senior director and Winnie Chang is marketing and public relations 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.