Masaru Sakai

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About

Masaru Sakai is a researcher specializing in the scheduling and optimization of semiconductor manufacturing equipment, with a particular focus on cluster tools and multicluster tools used in wafer fabrication. His work addresses some of the most challenging combinatorial problems in automated semiconductor processing, where precise coordination of robotic handlers, processing modules, and loadlock systems is critical to production efficiency. Sakai's most notable contributions center on developing intelligent scheduling algorithms that tackle deadlock prevention and makespan minimization in complex tool configurations. His 2017 paper on deadlock prevention for noncyclic scheduling of multicluster tools, which has garnered 17 citations, introduced an efficient policy for managing the intricate interactions that arise when multiple cluster tools operate in tandem — a problem of significant practical importance in modern fabrication facilities. Complementing this work, his research on dual-armed cluster tool scheduling explores noncyclic approaches to simultaneously minimize wafer residency time and overall makespan, accumulating 9 citations. Together, these contributions reflect Sakai's dedication to advancing beyond conventional cyclic scheduling paradigms, offering more flexible and robust solutions that align with the demanding throughput and quality requirements of contemporary semiconductor manufacturing.