Usage of the MANTIS Service Platform Architecture for servo-driven press machine maintenance
A forming press, is a machine tool that changes the shape of a workpiece by the application of pressure. Throughout MANTIS project, FAGOR ARRASATE’s servo-driven press machine is being analysed, in order to set up strategies that will permit to carry out an online predictive maintenance of the press machine.
The proposed solution advocates for soft sensor based algorithms. The soft sensing algorithms provide information about the physical status of the components, as well as information about the performance of the systems. These algorithms take advantage of existing or available internal signals of the systems. The objective is to estimate inaccessible states and parameters of the systems using as few physical sensors as possible to acquire the necessary signals to work with.
Currently a characterization of the system components has been done, in a scaled test bench of real press machine. A servomotor has been analysed in order to extract information about its performance during press machine work cycles, such as the applied current, voltages and generated torque. Besides, the applied soft sensor algorithm has proven to be suitable for estimating the desired magnitudes of systems when some of the system parameters are unknown.
At the same time, the mechanical part of the press machine has been analysed in order to elaborate an analytical model of the mechanical part of the system. The purpose of this development is to relate the torque generated by the servomotor with the force applied by the press ram.
This information will be used to detect effects that occur during metal forming processes, such as unbalanced forces and the cutting shock effect, allowing to carry out the maintenance of the system.