Currently, machine tools are evolving from isolated solutions to become intelligent elements within intercommunicating production systems. This development holds the potential to predict machine-related cost-intensive production shutdowns and integrate these insights into the production planning and machine development. The present paper defines the objective of a machine tool that is autonomously and integrally able to identify, predict and communicate its condition. The objective is derived as a direct consequence of current trends in the condition analysis and prediction of production machines. The combination of methods from production technology and computer science is at the core of 'industry 4.0', opening up the possibility of an innovative fusion of machine and production knowledge with access to a multitude of semantically rich operational data and information. Against this backdrop, the basis for developing a selfmonitoring machine tool exists. It could lead to a more reliable maintenance and production planning as well as shop scheduling. In this paper innovative solutions for the implementation of the objective will be presented
