In this paper we study the problem of a modeling, identifying, and monitoring an industrial robot. We start by showing how a robot can be modeled in increasing degree of accuracy using high end tools such as MathModelica. This model can be transformed semi-automatically into a minimal state-space form which in turn can be used for identification. Moreover, the physically connected equations can be identified recursively, making it possible to monitor critical parts of the robot. When attached to a well trimmed detection scheme this provides a big help for operators, who easily can track problems with the process.