Technical Bottlenecks and Process Optimization Pathways for AI Chip Wafer Manufacturing under Advanced Semiconductor Nodes
DOI:
https://doi.org/10.54097/v1tq3e15Keywords:
Semiconductor industry, AI chip, wafer manufacturing, advanced semiconductor nodes, process optimization, yield managementAbstract
With the rapid growth of AI workloads, there is now a high demand for high-end node wafer manufacturing, and at the same time, better power efficiency and higher yield are required. Identify the main technical bottlenecks in AI chip wafer manufacturing at advanced semiconductor nodes and put forward feasible process optimisation paths based on manufacturing integration. AI chips are not only the result of new-generation architecture but also depend on factors such as lithography technology, device structure, defect management, interconnect reliability, process fluctuation and yield optimisation to some extent in their actual performance and economic feasibility. Based on the theory of classical scaling, research in semiconductor manufacturing and recent reports on advanced-node processes have shown that the main problem is how to align performance scaling with manufacturability. Optimisation strategies based on design-technology co-optimisation, critical-layer process control, yield-oriented defect management and adaptive fab collaboration are also proposed. Therefore, the construction of advanced-node AI chip manufacturing will require the parallel development of device structure, process integration and manufacturing governance in the semiconductor industry.
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