This doctoral thesis is part of the High Performance Machining line of the University of Mondragon, whose main objectives include the development of adaptive control systems to increase productivity in machining processes. In the case of flat grinding, the objective being pursued is the development of an intelligent tool to assist the user during the set-up of the process, as well as during the process itself and subsequent quality control. The intelligent tool will offer the user both the most suitable grinding wheel for the specific application under analysis and a recommendation for configuring the process parameters. During grinding, an adaptive control will be activated to modify working conditions as the wheel wears to meet workpiece requirements for longer intervals between diamond dressing operations. After grinding the workpiece, the required tolerances are checked using measuring systems incorporated on the machine itself, thus avoiding laboratory measurements.
This set of new features is expected to bring substantial benefits to industrial grinding processes, by increasing productivity, reducing rejects and streamlining setting and quality control tasks. This doctoral thesis covers the functionalities related to the measurement of the flatness of the part on the machine itself, the estimation of the degree of wear of the grinding wheel and the prediction of the surface roughness of the part. As well as that, a first version of an adaptive control was developed that adjusts the process parameters to the power consumed, wheel wear and volume of material removed to avoid problems from thermal damage and failure to obtain the desired roughness.