Manufacturing industries give importance to the reduction of energy consumption due to the increase in energy cost and to create an eco-friendly environment. Assembly line is considered to be one of the cost intensive systems. Robots are recently being used to perform the assembly tasks instead of manual labor. There is a requirement of efficiently balancing the assembly line by allocating equal amount of work to workstations and assignment of best fit robot to perform the tasks allocated to those workstations. The authors could not find any research on optimizing cycle time and total energy consumption concurrently in robotic assembly line systems to date. The objective of this paper is to propose models with dual focus on time and energy to minimize the cycle time and total energy consumption simultaneously, one model (time based model) with the primary focus to optimize cycle time and the other model (energy based model) with the primary focus to optimize total energy consumption. Particle swarm optimization is used as the optimization tool to solve this problem. Computational experiments are conducted on the proposed models using the benchmark problems available in the open literature and the results are presented. The two models proposed in this paper are very well applicable to automobile body shop with robot based lines. The models proposed have a significant managerial implication in real assembly line systems. Depending upon the priorities of the management, primary focus on reducing either cycle time or total energy consumption, suitable models could be selected. The proposed models are useful to reduce the total energy consumption and cycle time in robotic assembly lines. It is observed that the computation time for the time based model is less compared to energy based model.