End-effector tools wear prediction: analysis and modelling of a CNC machine and new formulation of the friction coefficient
Emanuele Pansica
End-effector tools wear prediction: analysis and modelling of a CNC machine and new formulation of the friction coefficient.
Rel. Alessandro Rizzo, Giovanni Guida. Politecnico di Torino, Corso di laurea magistrale in Mechatronic Engineering (Ingegneria Meccatronica), 2022
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Abstract
In recent years, we have been witnessing a technological transformation of industry, the so-called Industry 4.0. In this context, the State of Health assessment (SOH) of industrial machines is a very important topic because by having information about the SOH of the machines, it is possible to operate preventive maintenace to avoid damages that may occur and, consequently, causing waste of money and time. Implementing SOH, companies could have more efficient production systems and reduce costs related to maintenance and machine downtime. The MOREPRO Project, owned by Brain Technologies, aims to develop a system capable of estimating the SOH of the end effector tools of a CNC machine in real-time.
In particular, their main purpose is to develop a technique that is first able to estimate the friction coefficient to which the tool is subjected during metal cutting operations, and then extract from this parameter the information necessary to estimate the SOH of the tool at the end of the stroke
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