We propose self-maintenance robot system as a method which realizes work for a long time without maintenance by the human workers. This system absorbs the change which occurs in robot's hardware by learning, and maintains working ability. We propose the two methods of learning changes in the physical information of the robot as methods which realizes the maintenance-free robot system. One is a method to learn robot's physical information based on the input and output information in the task practice from the no physical information of the robot by using a neural network which has a task common layer and a task independence layer. We use a neural network which has a task common layer and a task independence layer to learning. Other is a method to learn robot's physical information based on the difference in hoping action and actual action. In this report, we verify of these learning system by the computer simulation.