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Navigating the Talent Crunch: AI Solutions for a Thriving Semiconductor Manufacturing Sector

May 6, 2024  Author: Tignis   Category: Tignis News

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The CHIPS and Science Act is a historic piece of legislation passed by the US government in 2022 aimed at regaining American leadership in semiconductor manufacturing. Supported by an unprecedented $52 billion in federal funding, this investment will also address supply chain vulnerabilities and national security concerns that were made glaringly public by the COVID epidemic.

In addition to revitalizing our chip manufacturing prowess and capacity, the CHIPS Act will also drive us to address another vital necessity —the need for a strong talent strategy. Beyond the funding of many new fabs, the Act will create demand for thousands of technical jobs needed to operate these fabs, talent that is in very short supply based on the projected growth rate of the semiconductor industry. America and the semiconductor industry will need to focus on establishing a much larger pool of trained workers to staff all the new fabs that will come online through the end of the decade.

The New Reality: A Talent Strategy for Tomorrow

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

In the past, the assumption was that there would be an adequate supply of individuals possessing the required abilities to fill open positions. However, the semiconductor industry today is not a market segment that is actively sought after by high school or even college graduates. Combined with an aging workforce where significant numbers of workers will be retiring in a few years, it makes the need for trained technicians even more pressing for semiconductor manufacturers.

We need strategies that not only focus on training new workers but also on continuously enhancing the skills of existing employees to keep pace with the experienced staff expected to leave the workforce through the end of the decade. We need to look beyond just training new employees but also enabling existing technical staff to operate more efficiently and retain institutional and tribal knowledge before it disappears.

Building More Than Just Semiconductors: Building AI Assets That Increase in Value

In the face of this growing need for skilled labor in the semiconductor industry, technological innovations such as AI and machine learning are stepping in to bridge this gap. Companies like Tignis are at the forefront of this transformation, developing AI-powered process control solutions to significantly enhance the efficiency and precision of semiconductor manufacturing.

Tignis leverages advanced AI algorithms to monitor and optimize the complex processes involved in semiconductor manufacturing. These AI systems can predict and prevent potential issues before they occur, reduce waste, and ensure that tool availability is maximized. By automating and optimizing these critical goals, Tignis not only increases the yield of semiconductor production but also frees up human workers to be reallocated on more strategic, creative tasks that require human insight.

In today’s paradigm, manufacturing knowledge is captured, learned, and retained by expert individuals. Typically, semiconductor process engineers are taught the theoretical levers and environmental factors that affect their process, but at the same time they also need to learn the company-specific subtleties of their fab, tools, and products that make their process recipes efficient and dependable. But as paradigms shift and experts retire, critical institutional knowledge can be difficult to retain. AI is a highly valuable mechanism that does more than just learn the theoretical physics of a process, it also captures the nuances of that process over time in human-readable code. This AI code then becomes a persistent knowledge database for future engineers, democratizing the tribal knowledge that was once siloed in specific individuals.

Expert Insight

The integration of AI and automation into the semiconductor industry is often met with apprehension, with concerns about job displacement prevalent among the workforce.

David Park, VP of Marketing at Tignis has a more optimistic viewpoint in these areas saying, “AI and automation are not just about making processes faster or more cost-effective; they are about fundamentally transforming what a job entails. They enable us to rethink how and where we deploy human creativity and skills.”

This insight is crucial in shifting the narrative around AI from one of threat to one of opportunity. Park’s perspective highlights that AI and automation do not merely replace human labor but rather redefine it. They free human workers from mundane and repetitive tasks, allowing them to focus on more complex, strategic activities that machines are not equipped to manage.

In the context of ongoing labor shortages in the tech industry, AI and automation present a viable solution. They compensate for the lack of available human workers and help ensure that production does not stall due to workforce constraints. More importantly, they create an environment where all available human talent is used more effectively, maximizing the output and innovation potential of each employee. In this light, AI and automation are essential tools in the evolution of the workforce. They are not just adapting the industry to modern challenges but are also setting the foundation for future growth and development.

Turning the Tide with AI and Automation

The U.S. semiconductor manufacturing industry is currently facing a significant talent crunch, a challenge that is being addressed through the strategic integration of AI and machine-learning. These technologies are fundamentally revolutionizing the landscape of manufacturing, learning, and future growth.

But time is of the essence. AI can only learn from what it has seen in the past. Companies that wait to implement an AI strategy are losing valuable learning cycles and will be left behind by those that have already put AI strategies into place.

Tignis is at the forefront of this transformative journey. With a laser-focused commitment to the semiconductor industry, Tignis is not just responding to industry trends but actively shaping the future of semiconductor manufacturing. By prioritizing the development and implementation of AI and machine-learning, Tignis is envisioning a workforce that is quick, responsive, and leverages the knowledge that has been aggregated over decades of successful high-volume manufacturing.

References:

Howard, K. (2024, March 25). Chip market in the US: Influence of the CHIPS Act in GovCon. GovCon Wire. https://www.govconwire.com/articles/chip-market-in-us-chips-act-govcon

Morra, J. (2023, August 9). U.S. semiconductor workforce shortage reaching critical stage. Electronic Design. https://www.electronicdesign.com/technologies/embedded/article/21270688/electronic-design-us-semiconductor-workforce-shortage-reaching-critical-stage

House, W. (2023, February 3). FACT SHEET: CHIPS and Science Act will lower costs, create jobs, strengthen supply chains, and counter China. The White House.

Collins, B. (2024, February 19). US considering more than $10 billion in subsidies for Intel as part of CHIPS act to secure domestic semiconductor… TechRadar. https://www.techradar.com/pro/us-considering-more-than-dollar10-billion-in-subsidies-for-intel-as-part-of-chips-act-to-secure-domestic-semiconductor-manufacturing

Semiconductors and Artificial Intelligence – IEEE IRDSTM. (n.d.). https://irds.ieee.org/topics/semiconductors-and-artificial-intelligence#:~:text=AI%20demands%20will%20have%20lasting%20impacts%20on%20semiconductor%20design%20and%20production

Allan, L. (2024, April 4). AI takes aim at chip industry workforce training. Semiconductor Engineering. https://semiengineering.com/ai-automation-to-help-train-workforce-preserve-legacy-knowledge-optimize-processes