Due to the progressive automation in manufacturing technology, the automatic wear and process parameter control gains an increasing importance. In a series production these days, it will monitor the general machine condition and the process itself. And, if needed, appropriate corrective interventions are taken. In the single or small batch production, however, the monitoring process and corrective intervention is still in its infancy. This is mainly due to the operation of these systems. During a series production, highly experienced machine operators optimize the initial start-up phase of the cutting tool process empirically. In most cases, only post-production process monitoring exists. That means that when a deviation is detected in one produced part then corrective action is taken when the next part is produced. Such a process is not possible when a single part is produced. In that case, the quality of the product relies mainly on the competence of the machine operator. It is through experience and the human senses that an operator actively engaged in the process parameters establishes a stable production process. Due to economic considerations there is a growing cost issue associated with operating multiple machines and with machine availability. There is therefore the desire to employ appropriate automatic process monitoring and corrective systems in the individual production process as well. There is particularly a demand for a process monitoring system when deep drilling with gundrills at extreme depths up to six hundred times the drill diameter. Not only is the process itself costly, the parts themselves are also very expensive. In this paper, the objective is to create a general understanding of the conditions at the cutting edge in order to establish a foundation for developing an accurate process model. This model, continuously fed by process-relevant data, is designed to generate a short-term forecast of the stability of the drilling process and, if needed, to provide data for a corrective intervention. A model can only be as good as its input variables, so the various measurement systems are described in detail as well as their suitability. In analyzing the above and the physical conditions at the cutting edge, particular attention was focused on the sound-emitting effects that were created. During the analysis, the physical relationship between the cutting edge and the sound-emitting effects was examined. The structure-born noises were measured, filtered and validated to establish the relationship to the cutting edge. Based on this data, corrective intervention could be made in real time. Following the demands of the economy, the technical limits today were explored, possible solutions analyzed, developed and elaborated in a catalogue listing the requirements for implementing the process monitoring system. In collaboration with the Institute for Production Engineering and High Power Laser Technology (IFT) and Schoeller-Bleckmann Oilfield Technology GmbH & Co. KG (SBOT) this concept has been implemented specifically for the field of gundrilling and BTA drilling. To this end, a universal gundrill machine was developed and used as a test vehicle at the IFT. Following successful laboratory tests, the system was tentatively assigned to an Industrial gundrill machine from SBOT, and field trials were carried out under standard industrial conditions. This work proved that automatic monitoring of the gundrill process is possible by observing the structure-borne noise emissions. Further studies could confirm that such a concept can also be applied to other cutting applications.