The U.S. semiconductor supply chain is gaining strong momentum, driven mainly by strategic government policies, increased investment, and a rapidly growing demand for advanced technologies. According to the Semiconductor Industry Association (SIA), the United States is projected to triple capacity by 2032, with 2025-2027 marking critical years for initial production from new semiconductor fabrication facilities (fabs).
Major players are building new or expanding existing fabs across the nation. As these facilities come online, success will depend on maintaining uptime and high-quality yields while continuing to optimize efficiencies.
But keeping these fabs running smoothly while meeting stringent quality, safety, and environmental standards brings a unique set of challenges. Managing these complex facilities is a monumental task. They are operationally complex — requiring an extreme level of precision, cleanliness and environmental controls. Not to mention, they need to operate 24x7 without interruption.
Here are some of the best practices that facility managers can leverage to boost quality output.
Digitization of facility management
Digitizing facility services involves leveraging advanced technologies to optimize operations, enhance efficiency, and ensure the stringent conditions required for semiconductor manufacturing are consistently met. Many of the technologies that make up a smart factory are not necessarily new. But today, they are more robust, cost effective and easier to integrate into a connected platform.
The Internet of Things (IoT) has been instrumental in improving operations by enabling real-time monitoring, predictive maintenance, and data-driven optimization. Sensors on tools (such as lithography or etching equipment) can collect data on vibration, temperature, pressure, and gas flow. These sensors can also monitor cleanroom conditions, with real-time alerts to prevent contamination. Or they can monitor power usage of high-energy tools (such as EUV lithography machines) to optimize energy consumption.
The output from this type of equipment can generate massive amounts of data to harness for actionable insights. When combined with integrated cloud platforms and AI, the level of real-time intelligence can be transformative.
Smart cleaning
Proper cleaning is critical for maintaining ultra-clean environments and ensuring high yields in chip production. AI-enhanced smart cleaning harnesses data for real-time process monitoring and parameter adjustments.
A data intelligence platform can streamline and display analytics tailored for immediate access to data. With an integrated IoT hub for visibility and task validation, examples of front-line team data can include:
- Work completion against planned routes
- Quality performance and inspections
- Recognition patterns and performance trends
- Training compliance
- Safe workplace observations
This technology allows greater accuracy and efficiency with real-time actionable metrics, robust reporting, and up-to-date KPIs. In highly regulated industries like semiconductor manufacturing, the solution can help meet compliance and audit challenges, while enabling continuous improvement.
Proactive maintenance strategies
Highly specialized, expensive tools like photolithography machines, etchers, and deposition systems are prone to operational challenges. A laser failure or misalignment in an EUV system or a vacuum pump failure can stop an entire line.
Predictive maintenance (PdM) shifts from reactive or scheduled maintenance to a data-driven, just-in-time approach to anticipate equipment failures. It’s the difference between changing a specific part on a sensible schedule and knowing when it is optimal for operations and lifecycle costs.
Combining IoT sensors with data analytics, AI and machine learning, PdM enables detection of equipment anomalies or subtle deviations that could lead to defective product or production downtime. Some examples include:
- Heat monitoring - Detects heat caused by insulation issues or conduction problem so you can act before discharge events or arc faults.
- Partial discharge monitoring - Partial discharge usually isn’t visible, but it destroys insulation over time, which will cause a full and destructive discharge.
- Circuit monitoring - Measures power and power quality data, including harmonic disturbance in the wave forms and voltage transients (sags and swells) that can damage sensitive equipment.
Where just-in-time maintenance strategies have been implemented, the result can be dramatic. According to Nucleus Research, PdM initiatives can reduce downtime by between 35-50%, extend asset lifespan by between 20-40%, lower costs, improve safety, and enhance product quality.
It’s important to keep in mind that effective PdM implementation relies on high-quality, accessible data, integration with existing systems, and the flexibility to meet a fab’s specific needs.
The human factor
Contrary to popular belief, AI and other smart technologies will not replace skilled workers in a semiconductor manufacturing facility. Technology alone won’t deliver ROI. Rather, AI and other advanced technologies need to be viewed as a strategic enabler to enhance roles, not replace them. It’s not about replacing people but empowering them.
Nevertheless, this transition will demand new technical and analytical skillsets. It will reduce more manual tasks, shifting roles toward oversight, analytics, and troubleshooting of automated systems. Companies should focus on upskilling and reskilling their workforce incorporate AI fundamentals, IoT solutions, and data analytics.
However, demand for skilled workers currently outpaces supply. Given the shortage of skilled engineers and technicians in the industry, growing a stable workforce to meet increasing production demands could be a challenge.
Embracing outsourcing may be the answer to rapidly expanding the labor pool. This is particularly true if the outsourcing partner has a combination of in-depth expertise working within the complex semiconductor environment, along with a deep understanding of how smart and AI-enabled technologies can transform operations.
This success of the U.S. semiconductor industry will depend on implementing smart technologies, innovative facility management solutions and a stable workforce with specialized skills. Leveraging partnerships with experts that can drive these implementations and processes may hold the key to manufacturing success in the near future.
