Abstract: In the next generation of Small Form Factor (SFF) microsystem technologies, the complexity of microsystem packaging is on the rise. The pursuit of high integration and multifunctionality has led to a continuous reduction in film thickness, and necessitated adjustments in materials and processes, which, in turn, have given rise to concerns related to structural reliability and signal integrity (structural design and optimization, multi-physical and multi-scale coupling, thermal management, and electromagnetic compatibility). This array of challenges introduces substantial uncertainties in designing and optimizing microsystem packaging architectures. To navigate these complexities, the application of process and reliability models has proven instrumental in curtailing development costs and timelines. Central to this methodology is the simulation of materials and device architectures, which plays a pivotal role in expediting technological advancements. Material and architecture simulations facilitate the iterative adjustment of design parameters through data modeling, specifically by comprehending the impact of device architecture and materials on process enhancement. Additionally, they enable material/architecture co-design encompassing material selection, structural design, and performance optimization. As microsystem integration continues to advance, the co-simulation optimization of materials within architectural systems is poised to become an indispensable, if not the paramount, facet of developing new devices rooted in innovative materials and processes. The precision of simulation results for the microsystem packaging process and reliability depends largely on the input of material models. Therefore, an essential prerequisite for the precise forecasting of microsystem packaging process behavior and reliability lies in a comprehensive grasp of the material constitutive relations. Most of the organic/inorganic packaging materials in microsystem packaging have significant time dependence, but the time-dependent is often ignored in practical modeling, and the influence of time-dependent behavior has not been widely concerned and systematically studied.