AI solutions for the thriving semiconductor manufacturing sector

The CHIPS and Science Act is historic legislation passed by the U.S. government in 2022 aimed at regaining America’s leadership in semiconductor production. This investment, backed by an unprecedented $52 billion in federal funding, will also address supply chain vulnerabilities and national security concerns that have been made blatantly public by the Covid-19 epidemic.

In addition to revitalizing our chip manufacturing productivity and efficiency, the CHIPS Act will also push us to address another critical necessity—the need for a strong talent strategy. In addition to funding many new factories, the bill will create demand for thousands of technical positions needed to run these plants, a workforce that is in short supply given the semiconductor industry’s projected growth rate. America and the semiconductor industry will need to focus on creating a much larger pool of trained workers to staff all the new factories that come online by the end of the decade.

The new reality: talent strategy for tomorrow

In today’s high-tech world, job creation alone is no longer sufficient. For the industry to thrive, a methodical approach to developing and retaining a skilled workforce capable of handling the complexities of modern semiconductor manufacturing is needed.

In the past, it was assumed that there would be a sufficient supply of people with the required competencies to fill vacant positions. However, today’s semiconductor industry is not a market segment that is actively pursued by high school or even college graduates. This, combined with an aging workforce in which a significant number of workers will retire in a few years, makes the need for trained technicians for semiconductor manufacturers even more urgent.

We need strategies that not only focus on training new workers, but also on continuously improving the skills of current workers to keep pace with the experienced workforce that will leave the workforce by the end of the decade. We must go beyond just training new employees, but also enable existing technical staff to perform more effectively and retain institutional and tribal knowledge before it disappears.

Building more than just semiconductors: building AI assets that drive value

With the growing demand for skilled labor in the semiconductor industry, technological innovations such as artificial intelligence and machine learning are stepping in to fill this gap. Companies like Tignis are leading this transformation, developing AI-powered process control solutions to significantly increase the efficiency and precision of semiconductor manufacturing.

Tignis uses advanced artificial intelligence algorithms to monitor and optimize complex processes related to semiconductor production. These AI systems can predict and prevent potential problems before they occur, reduce waste and ensure maximum tool availability. By automating and optimizing these critical goals, Tignis not only increases semiconductor manufacturing efficiency, but also enables workers to be reallocated to more strategic, creative tasks that require human expertise.

In today’s paradigm, manufacturing knowledge is learned, captured, and retained by experts. Typically, semiconductor process engineers learn the theoretical levers and environmental factors that influence their process, but at the same time they must learn the company-specific subtleties of their factories, tools, and products that make their process formulations efficient and reliable. However, as paradigms change and experts retire, it may be difficult to maintain critical institutional knowledge. Artificial intelligence is an extremely valuable mechanism that not only learns the theoretical physics of a process, but also captures the nuances of that process over time in human-readable code. This AI code then becomes a permanent knowledge database for future engineers, democratizing tribal knowledge that was once hidden from specific individuals.

Expert knowledge

The integration of artificial intelligence and automation in the semiconductor industry is often a matter of concern, and job relocation concerns are prevalent among employees.

However, AI and automation are not just about speeding up and making processes more profitable; they aim to fundamentally change what work entails. They allow us to rethink how and where we use human creativity and skills.

This insight is crucial to changing the narrative about artificial intelligence from a narrative of threat to a narrative of opportunity. Artificial intelligence and automation are not just replacing human work, but rather redefining it. They free workers from mundane and repetitive tasks, allowing them to focus on more complex, strategic activities that machines cannot handle.

In the context of persistent labor shortages in the technology industry, artificial intelligence and automation offer a viable solution. They compensate for the lack of available human workers and help ensure that production does not stop due to labor constraints. More importantly, they create an environment in which all available human talent is used more effectively, maximizing the productivity and innovation potential of each employee. In this light, artificial intelligence and automation are essential tools for the evolution of the workforce. They not only adapt the industry to contemporary challenges, but also lay the foundations for future growth and development.

Turning the tide with artificial intelligence and automation

The U.S. semiconductor industry is currently facing a significant talent crisis, a challenge that will be solved through the strategic integration of artificial intelligence and machine learning. These technologies are fundamentally revolutionizing the landscape of production, learning and future growth.

But time is of the essence. Artificial intelligence can only learn from what it has seen in the past. Companies that wait to implement an AI strategy are missing out on valuable learning cycles and will be left behind by those that have already implemented AI strategies.

Tignis is at the forefront of this transformational journey. By focusing on lasers in the semiconductor industry, Tignis not only responds to industry trends, but actively shapes the future of semiconductor manufacturing. By prioritizing the development and implementation of artificial intelligence and machine learning, Tignis anticipates that workers will be fast, responsive and leverage knowledge accumulated over decades of successful, large-scale production.

Bibliography

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• House, W. (2023, February 3). FACT SHEET: CHIPS and the Science Act will cut costs, create jobs, strengthen supply chains and counter China. White House.
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• Allan, L. (2024, April 4). Artificial intelligence aims to train workers in the chip industry. Semiconductor engineering. https://semiengineering.com/ai-automation-to-help-train-workforce-preserve-legacy-knowledge-optimize-processes