Control of milling machine cutting force using artificial Neural Networks

The constant search of industry for productivity raises and market shares, pushes forward the development of new products capable of giving an answer to these concerns. Specifically the tool-machines makers have tried to solve these problems incrementing the capability of the machines they produce, essentially in speed and precision. The recent study of some problems associated to the machining process, has revealed the possibility of incrementing the productivity of some of vertical milling machine, only through the force control, keeping it constant and equal to the optimum value defined for the tool. The cutting force control, due to the system characteristics, can only be implemented by making use of adaptive control. In order to implement adaptive controllers we have at our disposal two technologies that have been showing good results. These technologies are Neural Networks and Fuzzy Logic. We thought that it would be of interest to research the use of Artificial Neural Networks in implementation of a controller. This has been the objective for the development of the work described in this paper. The results obtained have been encouraging, showing the possibility of implementing those controllers in real systems.