This thesis describes operational models that integrate process models to expedite process change decisions for cluster tool performance improvement. The process engineer attempting a process change needs to wait for the industrial engineer to approve the change after making sure it does not degrade cluster tool performance. Having a model that integrates process parameters into the operational model of the tool helps the process engineer quantify the impact of process changes on tool performance.This makes the process change decision faster. Two integrated models for understanding cluster tool behavior have been developed here. One is a network model that evaluates the total time needed to process a lot of wafers for a given sequence of activities involved in the process. Including a manufacturing process model (in the form of a Response Surface Model) gives an integrated network model that relates the total lot processing time to process parameters like temperature and pressure and to process times.

The second model developed is an integrated simulation model that can be used when the sequence of wafer moves is not given but is determined by a scheduling rule. The model can be used to quantify the impact of changes to process parameters and product characteristics like deposition thickness on total lot processing time. The thesis contains examples that illustrate the types of insights that one can gain into cluster tool behavior from using these integrated models.