Papers
2
Total Citations
25
H-Index
2
About
GengHong Wang is a leading researcher in semiconductor manufacturing automation, specializing in the scheduling and optimization of cluster tools—the robotic systems at the heart of wafer fabrication. Their work tackles the critical challenge of efficiently producing multiple wafer types on a single manufacturing line, a pressing need for modern foundries. Wang’s most-cited paper (2023, 21 citations) introduces a novel scheduling algorithm for single-arm multicluster tools that achieves lower-bound cycle times when processing two wafer types, directly addressing industry demands for flexibility and throughput. In a subsequent 2024 study (4 citations), Wang advanced the field by addressing time-constrained scheduling for cluster tools equipped with two-space process modules, enabling concurrent wafer processing within a single module—a design innovation that boosts productivity while respecting stringent timing constraints. These contributions have established Wang as a key figure in bridging theoretical scheduling models with practical semiconductor manufacturing constraints. Their work not only improves equipment utilization but also provides foundational insights for next-generation fabrication systems, making them a vital resource for students and engineers seeking to understand the intersection of operations research and real-world chip production.
Research Focus
Key Achievements
Top Papers
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