Chip Complexity and Global Semiconductor Talent Needs Drive Demand for Automation in Semiconductor Manufacturing

Staying ahead of an evolving semiconductor landscape

Since 2020, the semiconductor industry has experienced its share of challenges and opportunities with chip shortages, increased chip demand, government investments and more. While there may be headwinds that impact the short-term outlook for the industry, demand for semiconductors is expected to remain robust throughout the decade with semiconductor revenues predicted to grow by more than 80% from $550 billion in 2021 to $1 trillion by 2030. At Thermo Fisher Scientific, we are excited for the future of semiconductor technology and know that achieving this growth will require new capabilities in metrology tools. In this blog post, we’ll discuss two areas of focus for the semiconductor industry regarding metrology innovation—chip complexity and the global need for semiconductor talent—and how this drives a need for automation in semiconductor manufacturing.

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Integrated circuit complexity increases manufacturing process complexity

The number of steps it takes to design and produce today’s integrated circuits is steadily increasing—a result of new intricacies necessitated to support advancements made in power, performance and area. As semiconductors have moved from 32nm planar devices to 2 nm nanosheets, transmission electron microscopy (TEM) sample demand has also substantially increased as illustrated in the image below. For metrology labs, this is introducing a new challenge as sample demand reaches a point where manual processes, or the available technical resources are no longer sufficient to support the demand. Compounding this challenge is the need for faster data turns and time-to-data.

TEM demand and process steps increase from 32nm to 2nm

To overcome this challenge, semiconductor manufacturers are largely faced with two alternatives; acquire and deploy automated metrology tools or acquire additional metrology tools and hire additional tech talent to operate them.

Automation in semiconductor manufacturing offsets resourcing constraints

A second, and no-less-important, area of focus for semiconductor manufacturers is the growing global need for additional semiconductor talent and upskilling to meet execution demands. According to reports and articles written over the last year by organizations such as the Semiconductor Industry Association, McKinsey & Company and Nikkei Asia, the impact of the existing chip talent shortage is being felt worldwide. The table below summarizes some of the shortages reported in these most recent reports.

Country	Estimated semiconductor talent shortage
United States	70,000 to 90,000
Taiwan	30,000
Japan	35,000
South Korea	30,000

In addition to the numbers shared by these organizations, Deloitte published a report in 2022, The global semiconductor talent shortage, that estimates the semiconductor industry will need more than 1 million additional skilled workers by 2030 to support future growth.

While meeting this need will take several innovative approaches over the next few years to attract and build a growing semiconductor technology talent pool, one near-term solution is to utilize advanced automation capabilities available in metrology and yield analysis solutions, including Thermo Scientific instruments.

Automation in semiconductor manufacturing can provide two significant benefits: increased productivity and faster learning ramps for new, or reskilled technical resources.

Automated metrology and analysis enable faster time-to-data, increased productivity and throughput

Increasingly, many manufacturers are turning to technology, such as automation, artificial intelligence (AI) and machine learning to optimize their operation’s efficiency. Among the benefits automated tools can deliver are faster time-to-data, increased workforce productivity, and manufacturing throughput.

For the metrology lab, automated metrology tools can be invaluable, enabling lab operators to operate multiple tools simultaneously, generate accurate and precise data faster, accelerate new talent training and productivity, and increase data turns and sample throughput.

At Thermo Fisher, we have a long history of integrating AI and machine learning into our instruments to automate high-quality data collection. For example, the Thermo Scientific Metrios AX (S)TEM, introduced in 2019, was the world’s first commercially released TEM to use machine learning and AI. Designed exclusively for the semiconductor industry, the Metrios AX (S)TEM allows lab operators to automate recipe development, perform all necessary instructions to identify, align, and image regions of interest, and quickly acquire trusted data.

Moving forward, we will continue to develop innovative solutions for automation in semiconductor manufacturing to help with the enhanced performance of metrology tasks and increase semiconductor manufacturing productivity.

For the semiconductor industry, automation holds a great potential to transform lab and factory operations. Keep your eyes open for future blogs on AI and machine learning capabilities in our instruments. In the meantime, visit our Metrios AX (S)TEM and Thermo Scientific Helios 5 EX/L DualBeam websites to learn more about their capabilities.

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