Discovering models of software processes from event-based data
ACM Transactions on Software Engineering and Methodology (TOSEM)
Discovering models of behavior for concurrent workflows
Computers in Industry - Special issue: Process/workflow mining
Workflow Mining: Discovering Process Models from Event Logs
IEEE Transactions on Knowledge and Data Engineering
Trace based analysis of process interaction models
WSC '05 Proceedings of the 37th conference on Winter simulation
Business process mining: An industrial application
Information Systems
Advances in analytics: integrating dynamic data mining with simulation optimization
IBM Journal of Research and Development - Business optimization
Survey of research in modeling conveyor-based automated material handling systems in wafer fabs
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
Automated Trace Analysis of Discrete-Event System Models
IEEE Transactions on Software Engineering
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Modeling and analysis of automated material handling systems in semiconductor manufacturing is difficult because of its complexity, the large amount of data originating from different sources as well as the often incomplete monitoring of transport processes. This article proposes an automated method and tool for building high level models of such systems based on transport logs, routing information and static system data. On the basis of this model, a method for tracing and correlating lot movements is presented and used to support system experts in locating fab areas that most likely caused defects measured on wafers, e.g. due to temporarily contaminated clean room air. In addition, several methods to analyze the transport systems performance, such as the determination of lot detours or causes for a potentially critical load of certain system parts are discussed.