In this paper, a smart factory concept for autonomous mobile robots is presented. The main purpose is to increase productivity of the transport in machine-floor. It is based on advanced methods for failure handling and prevention, leading to increased robustness, less downtime and less effort in maintenance [1], [2]. Therefore, condition data and states of the robot are collected by Robot Operation System (ROS) and transferred to a factory hub (server). The collected data, e.g. voltages, currents, set points, velocities and accelerations are used to identify important system parameters, e.g. moving masses and friction parameters to enable the proposed smart factory concept. Further aim is to let the factory hub control a group of mobile robots using a self-organizing algorithm for different tasks. Due to the increasing customization of products causing smaller lot sizes [3], manufacturers of mobile robotic production systems have developed a diversity of flexible robots [4], [5], [6], [7], [8]. Mobile robots inside the production line allow for collecting and evaluation of system-inherent data e.g. handling and transportation time, wheel friction, workpieces mass, center of gravity and energy consumption during trajectory execution. In general, mobile robots are electrically driven. Hence, an estimation of the battery state is essential in order to automatically plan charging cycles and to organize and optimize the cooperation behavior of a group of mobile robots. In this proposed approach, mobile robots are equipped with a measurement system and connected via Bluetooth to a factory hub, providing monitoring, analyzing and planning tools. The battery states of all robots are considered in the process planning. The robots are based on the KUKA youBot, equipped with a soft gripper and a RealSense camera. A condition monitoring system measures the energy consumption of all components and transfers the information to the factory hub. The state of charge limits the number of executable operations. Therefore, in a first step the power consumption of all individual consumers is captured, e.g. EC-Maxxon base motors, PC, gripper, camera and five-axis arm. Experimental results show, that the youBot requires 46 W in standstill plus the drive power depending on the movement. Here, the results for mobile manipulation in industrial scenarios during preparation for the RoboCup@Work 2016 will be presented. The transfer of raw measurement data to the hub is shown, as well as the proposed algorithms allowing for range prediction and optimized set point generation. The concept provides excellent capability in data collection, analysis of existing production and production planning.