Log-based State Machine Construction for Analyzing Internal Logistics of Semiconductor Equipment

For evaluation of equipment productivity and diagnosis purposes state-transition models of equipments are necessary. In most cases these models are not provided by equipment manufacturers and therefore must be constructed by analysts (process engineers) based on log files. The construction of such models is a very time-consuming process that is impeded by the unknown structure of the events in the logs. The approach presented in this paper aims to automate the process of model construction by combining finite state machine generation with event text analysis. Some heuristics and user interaction are used to increase the efficiency of the model generation process. The approach was tested on different equipment types at Infineon Dresden. Section