PREPRODUCTION RESULTS DEMONSTRATING MULTIPLE-SYSTEM MODELS FOR YIELD ANALYSIS

We have assembled an integrated view of the entire via manufacturing p rocess, This integrated study includes five key plasma processes that culminate in the production of vias on CMOS wafers, There are essentia lly no linear cross-correlations between the processing steps and ther e are no linear correlations between the individual process steps and the yield for vias, as measured by the resistance between metal-one (M 1) and metal-two (M2). Using a neural network, we demonstrate that the key processing steps to determine the M1M2 resistance are the thick o xide deposition and the anisotropic via etch, Of lesser significance a re the etchback planarization, an isotropic etch and plasma enhanced t etra-ethoxy siliane (PETEOS) deposition, Keeping in mind that there ar e five processing steps, the numerical value of M1M2 resistance can be predicted ahead of time, before completion of all five processes, Thi s prediction can be done to an accuracy of about 1 Omega. By using ada ptive neural networks, the intelligent agents can modify their predict ive behavior with respect to process changes effected by the engineeri ng staff, Our pre-production demonstration suggests that these program s could be used in feedback and feedforward control for production yie ld.