The search of optimal operation parameters of a belt furnace for microelectronic packaging process using artificial neural networks

摘要

Energy dissipation and the transport of ceramic packaging substrates in a belt furnace for the manufacture of multichip module (MCM) devices were investigated based on computational fluid dynamics (CFD). Using the results of temperature profiles and knowledge of thermal expansion coefficients and thermophysical properties, the transient thermal stresses of the substrates were calculated through structure analysis at each grid point along the belt. Various levels of the belt speed and purging-gas flow rate were considered in the CFD simulation to evaluate their influence on stress formation inside the solid-state substrates. Results show that the induced thermal stress in MCM substrates is highly sensitive to their heating histories as well as the flow fields that develop inside the furnace. Subsequently, a search for optimal operating conditions for the firing process was conducted, with the goal of minimizing stress generation inside the glass-ceramic substrates, using the surface response method and an artificial neural network (ANN) approach. These efforts verified that high process-yields and excellent product-reliability for ceramic packaging devices could be achieved. [References: 8]