There are several methods of monitoring metal cutting processes. In this study, the combination of various methods in order to define an overall “cutting state” of a turning process is discussed along with an application to use these methods for adaptive fuzzy feed rate and cutting speed optimising control. For this purpose, different methods of monitoring individual cutting phenomena such as chip length and vibration level are aggregated and the combination of this information is considered to be the cutting state of the process. Expert data has been collected from a series of experiments concerning the apparent state of these phenomena as well as required control action. An adaptive optimizing fuzzy controller has been designed based on the concept of the cutting state and collected expert rules. The automatically classified cutting state as well as the control action based on this state is compared to expert data. There are notable differences which are analysed and solutions and further research are suggested based on the points requiring further improvement.