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End-effector tools wear prediction: interaction with the workpiece modelling in a quasi-FEM approach

Dario Caniglia

End-effector tools wear prediction: interaction with the workpiece modelling in a quasi-FEM approach.

Rel. Alessandro Rizzo, Giovanni Guida. Politecnico di Torino, Corso di laurea magistrale in Mechatronic Engineering (Ingegneria Meccatronica), 2021

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Nowadays, in the “Industry 4.0” context, an important topic is the state of health (SoH) estimation of machines because, knowing the SoH of machines, it is possible to intervene before that some damage could occur. Thus, the companies can increase the performance of their production systems and to reduce the maintenance costs. The MorePRO project, owned by Brain Technologies, fits in this context. This project has the goal of developing a real-time system able to estimate the SoH of the end-effector tools in a CNC machine. The technique that Brain Technologies wants to develop is able to estimate the friction coefficient to which the tool is exposed during metal cutting operations, extracting from this parameter the information to estimate the SoH of the end-effector tool. This thesis goal is to start the development of a similar FEM (Finite Element Method) analysis in Mathworks environment to obtain a model of the tool interaction with the work piece. From this model, artificial data can be obtained and they can be used to develop estimation methodologies. In this thesis work, my role was the development and implementation of an algorithm to detect the part of the end-effector tool that is employed in the metal cutting operation. The main activities performed can be divided as follow: 1.??Creation of a model of the CNC machine: the CNC machine analysed was considered divided in two parts. The first part has the objective to place the end-effector and the second part to place and orientate the work piece. Models of the two parts were created using the acknowledgement acquired in the Robotics course. These models were necessary to obtain the 3D coordinates of the end-effector tool and the work piece. 2.??Creation of trajectories in the operational space: to simulate the CNC machine movement, it was necessary to give to our model a trajectory as input. This analysis is interested in the movements of the end-effector tool; thus, the trajectories were developed in the operational space. A segment in the space trajectory and a circumference in the space trajectory were developed. 3.??Identification of the interaction points: the end-effector tool was approximated to a points cloud. The points that interact with the work piece during the movement were identified and they will be used in a mechanical analysis.

Relators: Alessandro Rizzo, Giovanni Guida
Academic year: 2021/22
Publication type: Electronic
Number of Pages: 93
Corso di laurea: Corso di laurea magistrale in Mechatronic Engineering (Ingegneria Meccatronica)
Classe di laurea: New organization > Master science > LM-25 - AUTOMATION ENGINEERING
Aziende collaboratrici: Brain technologies
URI: http://webthesis.biblio.polito.it/id/eprint/21159
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