It is well-known that semiconductor manufacturing is one of the most complex types of production. Consequently, making the right decisions in order to get the optimum output of a semiconductor fab is quite challenging. For that reason, sophisticated discrete event simulation studies may be seen as a kind of magic tool for fab managers to face the ever-increasing complexity. But building complex dynamic simulation models in order to solve complex problems is not always the best solution. This article gives an overview of the discussion about the correct level of complexity of discrete event simulation models and lists the main reasons for the creation of overcomplex models. To provide guidance for practitioners, lessons learned are derived from four "real world" use cases in which the correct level of complexity was a major issue.
Usually simulation studies of automated material handling systems of semiconductor fabs are extremely time consuming. This is due to the high detail of models used for investigations which are partly provided by transportation system suppliers. These models only provide poor possibilities for adjustment and are computationally expensive. The article will address these issues by proposing an adjustable supplierindependent base simulation model. It allows easy building, adjusting, and running simulation models of path-based systems without deeper programming knowledge. A use case of Infineon's Dresden fab revealed simulation results with an accuracy in the same range as the supplier models while disregarding a few details and thus showing significant time savings in modeling and adjusting the system as well as running simulation studies. This can be done by choosing an appropriate level of abstraction.
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