The U.S. semiconductor defect inspection equipment market size was valued at USD 556.05 million in 2024, growing at a CAGR of 7.1% from 2025 to 2034. Government incentives through the CHIPS and Science Act are propelling the expansion of semiconductor manufacturing in the U.S., leading to increased installation of defect inspection tools. These investments aim to strengthen domestic chip supply chains and require high-precision inspection systems to meet volume and yield expectations. For instance, in June 2025, Texas Instruments announced its plans to invest USD 60 billion in the domestic production of foundational semiconductors in the U.S.
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The U.S. semiconductor defect inspection equipment market focuses on tools and systems used to detect, classify, and analyze defects in semiconductor wafers, photomasks, and packaging. These systems ensure yield optimization, process control, and quality assurance during semiconductor manufacturing, supporting both front-end and back-end production. The U.S.-based fabs are accelerating production at advanced nodes such as 5nm and 3nm. These smaller geometries make semiconductor structures more vulnerable to micro-defects, necessitating the deployment of advanced inspection machines to maintain process control and ensure device performance in high-density chips.
The growing demand for AI accelerators and high-performance computing chips is increasing complexity in semiconductor design and production. Inspection systems play a crucial role in ensuring wafer quality at every layer, thereby supporting the error-free fabrication of processors used in data centers, research, and edge computing. Moreover, major foundry expansions are underway in the U.S., including greenfield fabs focused on logic, memory, and analog devices. Each phase of construction involves large-scale installation of metrology and defect detection systems to ensure cleanroom integrity and maintain competitive yield levels.
Increased Focus on Defense and Aerospace Supply Chain Security: Growing concerns over national security and technological sovereignty have led to a renewed emphasis on strengthening the domestic semiconductor supply chain for defense and aerospace applications. According to the Aerospace Industries Association, in 2023, the U.S. aerospace and defense sales exceeded USD 955 billion, marking a 7.1% growth from the previous year. Critical systems used in satellites, avionics, radar, and missile guidance demand flawless, high-reliability semiconductor components that perform consistently under extreme conditions. This demand has triggered a significant shift in manufacturing strategy, prompting U.S.-based defense contractors and chipmakers to invest in secure, in-house fabrication capabilities.
Surge in Electric Vehicle (EV) Chip Demand: The expansion of electric vehicle manufacturing across the U.S. is creating demand for automotive-grade semiconductors, especially those used in power management, motor control, battery systems, and safety sensors. According to the U.S. Energy Information Administration, Tesla’s market share accounted for 48.9% of the total electric vehicle market in 2Q24. These chips must meet stringent standards related to thermal stability, durability, and failure tolerance under variable road and climate conditions. Given the safety-critical nature of these components, defect inspection equipment has become indispensable to EV chip production workflows.
Based on defect, the U.S. semiconductor defect inspection equipment market segmentation includes crystal defect inspection, metal defect inspection, mask/reticle defect inspection, and others. The crystal defect inspection segment dominated the market in 2024 with ~31% of the revenue share as the increased production of high-performance chips has elevated the need to detect even the slightest imperfections in crystal structures during wafer fabrication. These defects, such as dislocations or stacking faults, severely impact transistor behavior, reliability, and device yield, especially at smaller nodes. Leading-edge fabs operating at sub-7nm scales rely on advanced optical and X-ray-based tools to identify abnormalities in the crystal lattice that results from thermal stress, process variations, or material inconsistencies.
In terms of inspection technique, the U.S. semiconductor defect inspection equipment market segmentation includes 2D inspection techniques, 3D inspection techniques, and machine learning and AI. The machine learning and AI segment is expected to register the highest CAGR from 2025 to 2034, as rising chip complexity and data-intensive inspection environments boost the adoption of machine learning and AI algorithms in defect inspection systems. These technologies enhance pattern recognition, classify anomalies in real time, and adapt to evolving defect types that traditional rule-based systems may overlook. As fabs transition to advanced nodes and heterogeneous integration, inspection workloads become more demanding, requiring intelligent systems that differentiate between nuisance defects and yield-critical issues with greater accuracy. AI-based tools reduce false positives, optimize process control, and improve decision-making across the production line.
The competitive landscape of the U.S. semiconductor defect inspection equipment market is shaped by rapid innovation cycles, strategic technology alliances, and an increasing focus on advanced node capability. Companies are aggressively pursuing market expansion strategies that include investments in R&D to develop high-resolution, AI-integrated inspection platforms capable of detecting sub-nanometer defects. Mergers and acquisitions are playing a central role in consolidating niche capabilities such as e-beam inspection and deep learning analytics, followed by post-merger integration to streamline product portfolios. Strategic alliances between inspection system providers and chip manufacturers are emerging to co-develop customized inspection solutions tailored for EUV lithography and advanced packaging.
A few major companies operating in the U.S. semiconductor defect inspection equipment market include Applied Materials, Inc.; Camtek; Hitachi High-Tech Corporation; HORIBA Group; KLA Corporation; Komatsu NTC.; Merck KGaA; Onto Innovation; PDF Solutions; and Toray Group.
In February 2025, TORAY ENGINEERING Co., Ltd. launched a novel inspection system for large glass substrates in the advanced semiconductor packaging industry, featuring double-sided inspection and internal defect detection.
In October 2024, Merck acquired Unity-SC, a company specializing in metrology and inspection instrumentation. This acquisition enhances Merck's capabilities in critical technologies relevant to artificial intelligence applications, particularly in the area of Heterogeneous Integration.
Report Attributes |
Details |
Market Size in 2024 |
USD 556.05 million |
Market Size in 2025 |
USD 594.97 million |
Revenue Forecast by 2034 |
USD 1,103.06 million |
CAGR |
7.1% from 2025 to 2034 |
Base Year |
2024 |
Historical Data |
2020–2023 |
Forecast Period |
2025–2034 |
Quantitative Units |
Revenue in USD million and CAGR from 2025 to 2034 |
Report Coverage |
Revenue Forecast, Competitive Landscape, Growth Factors, and Industry Trends |
Segments Covered |
|
Competitive Landscape |
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Report Format |
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Customization |
Report customization as per your requirements with respect to countries, regions, and segmentation. |
The market size was valued at USD 556.05 million in 2024 and is projected to grow to USD 1,103.06 million by 2034.
The market is projected to register a CAGR of 7.1% during the forecast period.
A few of the key players in the market are Applied Materials, Inc.; Camtek; Hitachi High-Tech Corporation; HORIBA Group; KLA Corporation; Komatsu NTC.; Merck KGaA; Onto Innovation; PDF Solutions; and Toray Group.
The crystal defect inspection segment dominated the market with ~31% of the revenue share in 2024, as the increased production of high-performance chips has elevated the need to detect even the slightest imperfections in crystal structures during wafer fabrication.
The machine learning and AI segment is expected to register the highest CAGR from 2025 to 2034, fueled by rising chip complexity and data-intensive inspection environments are accelerating the adoption of machine learning and AI algorithms in defect inspection systems.