The thesis presents different processes for optimizing machining processes. It responds to the needs of industry for maximum efficiency. The correct approach to measuring and analysing results is presented in the beginning. The Pareto principle which expedites the process of distinguishing between significant and insignificant data is described next. By statistical process control and Sigma six, data after each production process is collected and errors are prevented not to pass on to the following processes. Real time optimization is based on capturing data during production process and comparing parameters to desired value. If a parameter starts to deviate, we optimize the process. As the last one, FMEA method for detection and prevention of potential errors is presented. During construction and production process, we try to predict possible mistakes and try to avoid them in advance by choosing the right production operation.