Aggregate modeling of semiconductor equipment using effective process times

Performance evaluation using queueing models is common practice in semiconductor manufacturing. Analytical closed-form expressions and simulation models are popular in capacity planning and the analysis of equipment configurations. However, the complexity of semiconductor processes complicates the modeling of the equipment. Analytical models lack the required accuracy, whereas simulation models require too many details, making them impractical. Aggregation is a way to overcome this difficulty. The various details are not modeled in detail, but their contribution is lumped in the aggregate model, which makes the model more appropriate for both analysis and simulation. This paper gives an overview of our efforts to develop a top-down aggregate modeling approach for semiconductor equipment, starting from the effective process time concept inspired by the Factory Physics book of Hopp and Spearman. The strong feature of our modeling approach is that the aggregate model parameters are estimated directly from industrial data (arrival and departure times), without the need to quantify the various details.