Sequential modeling of via formation in photosensitive dielectric materials for MCM-D applications

Multichip module (MCM) technology is considered a strategic solution in ele ctronics packaging because this approach offers significant advantages in e lectrical and thermal performance and reliability. However, manufacturing c ost is a critical issue for mass production of high-performance MCM package s. To realize low-cost manufacturing technology, process modeling, optimiza tion, and control techniques are required. In this paper, a modeling approa ch for via formation in MCM dielectric layers composed of photosensitive be nzocyclobutene (BCB) is presented. A series of designed experiments are use d to characterize the via formation workcell (which consists of the spin co at, soft bake, expose, develop, cure, and plasma descum unit process steps) . The output characteristics considered are film thickness, refractive inde x, uniformity, film retention, and via yield. Sequential neural network pro cess models are constructed to characterize the entire process. In the sequ ential scheme, each workcell subprocess is modeled individually, and each s ubprocess model is linked to previous subprocess outputs and subsequent sub process inputs. This modeling scheme is compared with both the global and u nit process modeling approaches to evaluate model prediction capability. Th e sequential method shows superior capability, with an average rms predicti on error of 6.40% over all responses, compared to a 11.61% rmse for the glo bal model and a 12.05% error for the unit process models.