Virtual lithography system to improve the productivity of high-mix low-volume production

This paper proposes a new virtual lithography system to improve the productivity of high-mix / low-volume production. In the case of the conventional technique, product mask and wafer are used to determine a focus-exposure-matrix (FEM) exposure condition. The conventional technique is a "send-ahead" process involving exposure, metrology and data analysis that decreases productivity of manufacturing. In the case of low-volume/high-mix ASIC manufacturing, such a send-ahead process is particularly time-consuming and costly. Moreover, the exposure condition setting imposes a huge workload that is desirable to be avoided from the viewpoints of cost and TAT. Thus, a new methodology to determine exposure dose conditions for each mask in high-mix / low-volume production is required. In this paper, we propose a virtual lithography system to eliminate send-ahead exposure. Firstly, to improve wafer CD prediction accuracy, we rebuild the system, thereby transforming it from a training-based system to a simulation-based system. To make simulation models, we use a golden mask, which is not a product mask. Secondly, exposure conditions are determined by considering 2D patterns including hotspot patterns. Thirdly, the lithography simulation is carried out for each exposure tool. Using the golden mask, we calibrate simulation models for each exposure tool 1-3 . Various patterns including hotspots likely to become fatal errors for circuit reliability due to process proximity effects are considered. The virtual system provides optimal exposure parameters according to product and layer, considering long-term variation of exposure tool conditions. By developing this system, TAT and cost for the determination of exposure parameters will be improved. Elimination of send-ahead wafers can reduce TAT from mask delivery to exposure condition setup in high-mix / low-volume production. Drastic cost reduction is realized in high-mix / low-volume production.