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

Multichip module (MCM) technology is considered a strategic solution in electronics packaging because this approach offers significant advantages in electrical and thermal performance and reliability. However, manufacturing cost is a critical issue for mass production of high-performance MCM packages. To realize low-cost manufacturing technology, process modeling, optimization, and control techniques are required. In this paper, a modeling approach for via formation in MCM dielectric layers composed of photosensitive benzocyclobutene (BCB) is presented. A series of designed experiments are used to characterize the via formation workcell (which consists of the spin coat, soft bake, expose, develop, cure, and plasma descum unit process steps). The output characteristics considered are film thickness, refractive index, uniformity, film retention, and via yield. Sequential neural network process models are constructed to characterize the entire process. In the sequential scheme, each workcell subprocess is modeled individually, and each subprocess model is linked to previous subprocess outputs and subsequent subprocess inputs. This modeling scheme is compared with both the global and unit process modeling approaches to evaluate model prediction capability. The sequential method shows superior capability, with an average rms prediction error of 6.40% over all responses, compared to a 11.61% rmse for the global model and a 12.05% error for the unit process models.