Industrial robots are deployed in many manufacturing industries and are a key technology in implementing production on the desired scale, speed, quality and costs. This work proposes various methods for the energy efficient use of medium and high payload industrial robots and robotized production systems. A new, complete robot system model is developed, applicable to various types of 6 degrees-of-freedom articulated manipulators, considering actuator drive systems and controller cabinet losses. In this thesis, methods for energyefficient large-scale robotized production planning are proposed, such as idling strategies, strategic selection of the robot manipulator type and intelligent brake management. A cluster analysis of the robot trajectory planning algorithms and a case study of dynamic robot program optimization within a robot production cell in the automotive industry are given. The effective use of regenerative energy is evaluated and a novel power converter system for multirobot cells is proposed to enable energy sharing between several robot actuator drive systems. Experimental validation and a viability proof of the proposed optimization approaches are provided. It is estimated that complementary implementation of all proposed methods increases the energy efficiency of robot manufacturing systems of ca. 30% over the state of the art.