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Optimal planning in robotized cladding processes on generic surfaces

Published online by Cambridge University Press:  21 January 2018

Paolo Magnoni*
Affiliation:
Institute of Industrial Technologies and Automation, National Research Council, via Corti 12, 20133 Milan, Italy. E-mails: [email protected], [email protected] Department of Mechanical and Industrial Engineering, University of Brescia, via Branze 39, 25123 Brescia, Italy. E-mail: [email protected]
Nicola Pedrocchi
Affiliation:
Institute of Industrial Technologies and Automation, National Research Council, via Corti 12, 20133 Milan, Italy. E-mails: [email protected], [email protected]
Sebastian Thieme
Affiliation:
Fraunhofer Institut fur Werkstoff und Strahltechnik, Winterbergstr 28, 01277 Dresden, Germany. E-mail: [email protected]
Giovanni Legnani
Affiliation:
Department of Mechanical and Industrial Engineering, University of Brescia, via Branze 39, 25123 Brescia, Italy. E-mail: [email protected]
Lorenzo Molinari Tosatti
Affiliation:
Institute of Industrial Technologies and Automation, National Research Council, via Corti 12, 20133 Milan, Italy. E-mails: [email protected], [email protected]
*
*Corresponding author. E-mail: [email protected]

Summary

Cladding through laser metal deposition is a promising application of additive manufacturing. On the one hand, industrial robots are increasingly used in cladding because they provide wide wrist reorientation, which enables manufacturing of complex geometries. On the other hand, limitations in robot dynamics may prevent cladding of sharp edges and large objects. To overcome these issues, this paper aims at exploiting the residual degrees of freedom granted by the cladding process for the optimization of the deposition orientation. The proposed method optimizes the robot head orientation along a predefined path while coping with kino-dynamic constraints as well as process constraints. Experimental tests and results are reported and used to validate the approach.

Type
Articles
Copyright
Copyright © Cambridge University Press 2018 

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