Intelligent control of via formation by photosensitive BCB for MCM-L/D applications

Via formation is a critical process sequence in multichip module (MCM) manu facturing, as it greatly impacts yield, density, and reliability. To achiev e low-cost manufacturing, modeling, optimization, and control of via format ion are crucial, In this paper,a model based supervisory control algorithm is developed and applied to reduce undesirable behavior resulting from vari ous: process disturbances, A series of designed experiments are used to cha racterize the via formation workcell (which consists of-the spin coat, soft bake, expose, develop, cure, and plasma descum unit process steps). The ou tput characteristics considered are film thickness, uniformity, film retent ion, and via yield, Sequential neural network process models are used for s ystem identification, and hybrid genetic algorithms are applied to synthesi ze process recipes. Computer simulation results show excellent control of o utput response shift and drift, resulting in a reduction of process variati on, The performance limits of the supervisory control system are investigat ed based on these simulation results; The control algorithm is verified exp erimentally, and the results show 82.6, 64.4, and 17.3% improvements in mai ntaining target via yield, film thickness, and film uniformity, respectivel y, as compared to open loop operation.