This paper presents digital panel assembly (DPA) methodologies and applications for sheet component assembly in automotive body manufacturing processes. Core to DPA is the customized finite element analysis formulas we have developed, which simulates assembly processes and predicts assembly dimensions by taking into consideration the panel compliances. Two key analysis types of the DPA are presented, the deterministic analysis and variation analysis. We present a methodology to utilize the quadratic form of Taylor series expansion to approximate the assembly dimensions efficiently in variation simulation, and discuss its pros and cons versus the traditional Monte Carlo method under different modeling conditions. For either the deterministic or variation analysis, linear models (without contact, efficient but less accurate), and nonlinear models (with contact, less efficient but accurate) can be established. It is shown that the linear models are only valid when panels do not penetrate, and that the nonlinear models should generally be used for accurate assembly dimension prediction. Based on the DPA methodologies, a software tool called Elastic Assembly Variation Simulation (EAVS) is presented, followed by application case studies. The confidence intervals for variation analysis are also discussed.