Symbiotic Simulation Control in Semiconductor Manufacturing

Abstract

Abstract. Semiconductor manufacturing is a highly complex and asset intensive process. Solutions are needed to automate control of equipment and improve efficiency. We describe a symbiotic simulation control system which uses reactive what-if analysis to find a stable configuration of a wet bench tool set. This control system is based on a generic framework for symbiotic simulation. We show that symbiotic simulation can be used to make control decisions in near real-time. Furthermore, we show that our approach yields a notable performance improvement over common practise.

Symbiotic Simulation Model Validation for Radiation Detection Applications

“…We have developed such a generic framework based on agent technologies [1]. In previous work, we have applied this framework to realise a symbiotic simulation control system (SSCS) for automatic control of semiconductor manufacturing equipment [3]. Here we make use of the same framework to realise an SSMVS in the context of radiation detection.…”

“…As mentioned above, we have already used our generic framework to realise an SSCS for equipment control [3]. The Radiation-SSMVS can be realised using the same framework.…”

Using simulation and hybrid sequencing optimization for makespan reduction at a wet tool

“…As a result, Cycle Time (CT) reductions obtained at critical production steps could generate considerable productivity improvements and eventually lead to a capacity increase at no investment cost (Quek et al 2007;Aydt et al 2008). Hence, CT improvements also become strategic targets for companies that want to maintain competitive advantages, especially when they operate in highly dynamic industries, such as the semiconductor industry (Kuo, Chien, and Chen 2011).…”

“…Automated wet tools can be classified as batch chamber tools; they include several chambers, or tanks, each of which can accommodate a batch of wafers, usually made of one or two lots. Due to the inherent complexities and the peculiar scheduling constraints, simulation approaches are usually preferred to model wet tools (Govind and Fronckowiak 2003;Noack et al 2008;Aydt et al 2008); simulation models support investigations on the impact of operational settings variations on wet tools performance (Noack et al 2008). Using an optimization framework for the metallization process, Noack et al (2008) optimize dispatching rules and virtual queue capacity in front of a wet tool.…”

“…The effects of various dispatching rules and recipe dedication schemes on wet stations capacity is analyzed by Quek et al (2007). Recipe dedication optimization at wet tools is also investigated by Aydt et al (2008); a symbiotic simulation control system is created to dynamically adjust the recipe dedication settings at the available tools with respect to the current WIP level. Govind and Rotondo, Geraghty, and Young Fronckowiak (2003) investigate the impact of scheduling policies, maximum waiting time for batching operations and maximum internal buffer level on CT at wet tools by means of a hybrid simulation model that combines transient entity modeling and a resident-entity approach.…”