Advanced semiconductor packaging and AI manufacturing: the growth wave is far from over

Structural Transformation of the Semiconductor Industry: Growth Drivers Are Being Reset

Citing the view of Srini Subramanian, Executive Vice President of Advanced Technology Solutions at Nordson, the long-term growth trajectory of the semiconductor industry has never been more compelling. In the past, semiconductor demand was primarily driven by a single application. Today, artificial intelligence, connectivity, cloud infrastructure, and electrification simultaneously drive up computing demand across multiple domains, with semiconductors forming the foundation of it all. Over 400 TB of data is generated globally every day, growing at an annual rate of about 20%. Every message, every algorithm training session, and every autonomous system increases the demand for chip performance, energy efficiency, and reliability.

Architectural Shift: From 2D to 3D, Advanced Packaging Becomes a Key Growth Area

In response to computing demands, chip architecture is undergoing a fundamental transformation. 2.5D designs have been widely adopted, while 3D architecture brings higher functional density through more compact stacked integration. This shift makes advanced packaging one of the fastest-growing areas in semiconductor manufacturing, with annual growth rates generally ranging from 10% to 12%. Advanced packaging is no longer just traditional single-chip packaging but includes complex elements such as multi-die configurations, stacked structures, and fine-pitch interconnects. This requires micron-level precision, extremely high thermal stability, and electrical reliability, driving strong demand for precision machining and inspection technologies.

AI from Design to Production: Changing the Manufacturing Logic

A landmark change in 2026 is that AI is no longer theoretical but directly enters the production line. Traditional inspection systems rely on preset rules or thresholds and struggle with increasingly complex device structures. AI-driven inspection can learn from real production data, more accurately identify defect patterns, reduce false positives, and improve inspection performance. More importantly, AI transforms inspection data from a mere quality gate into a feedback mechanism for manufacturing optimization—data becomes a strategic asset for process adjustment, yield improvement, and maintenance strategy planning.

Extreme Reliability Requirements Driven by Electrification

More and more electronic components are embedded in electric vehicles, wearables, industrial automation, and smart consumer electronics, while tolerance for reliability is sharply decreasing. Electrification is particularly prominent: semiconductor chips in a modern car manage battery control, power conversion, advanced driver assistance, and connectivity. This trend requires that every step in the manufacturing process—from precision dispensing and surface treatment to selective soldering—must have extremely high repeatability and traceability. The advanced packaging stage becomes a critical node determining long-term product reliability; any minor process deviation can lead to severe consequences in safety-critical applications.

Opportunities and Challenges for Japan's Semiconductor IndustryFor Japan's semiconductor industry, this trend presents both opportunities and challenges. Japan has deep expertise in semiconductor materials (such as photoresists and packaging materials), precision equipment (e.g., inspection, dispensing, and coating equipment), and manufacturing process control. Japanese companies like Nordson, Tokyo Electron, and Disco hold significant positions in advanced packaging equipment and inspection technology. As demand for AI manufacturing and electrification rises, Japanese firms have the opportunity to combine their high-precision manufacturing advantages with AI data capabilities to redefine quality standards.

However, Japan's share in logic chip manufacturing and advanced packaging capacity has already been overtaken by competitors such as TSMC and Samsung. Transforming advantages in materials and equipment into system-level competitiveness and building an independent AI-driven manufacturing ecosystem remain key challenges. The "Post-5G Semiconductor" plan and the advanced packaging R&D alliance promoted by Japan's Ministry of Economy, Trade and Industry are precisely attempts to bridge this gap.