Simulation-based framework to Automated Wet-etch station scheduling problems in the semiconductor industry

This work presents the development and application of an advanced modelling, simulation and optimization-based framework to the efficient operation of the Automated Wet-etch Station (AWS), a critical stage in Semiconductor Manufacturing Systems (SMS). Principal components, templates and tools available in the Arena^® simulation software are used to achieve the best representation of this complex and highly-constrained manufacturing system. The major aim of this work is to provide a novel computer-aided tool to systematically improve the dynamic operation of this critical manufacturing station by quickly generating efficient schedules for the shared processing and transportation devices. This model presents a flexible structure that can be easily adapted to emulate random scenarios with uncertain processing and transfer times. A user-friendly interface for dealing with real-world applications in industry is also introduced.