Intelligent Machining Systems

Machining is one of the most widespread manufacturing processes and plays a critical role in industries. As a matter of fact, machine tools are often called mother machines as they are used to produce other machines and production plants. The continuous development of innovative materials and the increasing competitiveness are two of the challenges that nowadays manufacturing industries have to cope with. The increasing attention to environmental issues and the rising costs of raw materials drive the development of machining systems able to continuously monitor the ongoing process, identify eventual arising problems and adopt appropriate countermeasures to resolve or prevent these issues, leading to an overall optimization of the process. This work presents the development of intelligent machining systems based on in-process monitoring which can be implemented on production machines in order to enhance their performances. Therefore, some cases of monitoring systems developed in different fields, and for different applications, are presented in order to demonstrate the functions which can be enabled by the adoption of these systems. Design and realization of an advanced experimental machining testbed is presented in order to give an example of a machine tool retrofit aimed to enable advanced monitoring and control solutions. Finally, the implementation of a data-driven simulation of the machining process is presented. The modelling and simulation phases are presented and discussed. So, the model is applied to data collected during an experimental campaign in order to tune it. The opportunities enabled by integrating monitoring systems with simulation are presented with preliminary studies on the development of two virtual sensors for the material conformance and cutting parameter estimation during machining processes.