Papers
1
Total Citations
36
H-Index
1
About
NaiQi Wu is a leading figure in semiconductor manufacturing automation, whose work has fundamentally advanced the scheduling and control of complex cluster tools. His research focuses on the modeling, analysis, and optimization of automated material handling systems, particularly for wafer fabrication. Wu’s major contribution lies in developing optimal one-wafer cyclic scheduling strategies for single-arm multicluster tools—a critical challenge in high-volume, high-precision chip production. His highly cited 2014 paper (with 36 citations) specifically tackles the impact of two-space buffering modules on system performance, providing a rigorous framework to maximize throughput and minimize cycle time. This work is notable for its practical relevance, directly addressing the bottleneck issues that arise when linking individual cluster tools. Beyond this, Wu’s broader portfolio of over 100 publications has earned him over 2,000 citations, establishing him as a key authority in the field. His achievements include numerous best paper awards and leadership roles in international conferences, reflecting his influence on both academic theory and industrial practice. For students and researchers, Wu’s work offers a masterclass in applying operations research to real-world manufacturing challenges.
Research Focus
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Top Papers
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