Peripheral milling is one of the most used technologies in the mechanical industry thanks to its accuracy and versatility. Nonetheless these redeeming qualities may be compromised in cutting operations where the flexibility of both the tool and the workpiece is relevant. In such conditions the tool/workpiece flexibility may cause static deflections or vibrations leading to inacceptable surface errors. Due to the complexity of these mechanisms, the most suitable approach to deal with surface errors is the use of virtual predictive techniques. This thesis presents models and approaches aiming at ensuring the required accuracy on machined components when the tool/workpiece flexibility is limiting the process performances, fitting Industry 4.0 paradigm.
Modelling and toolpath generation strategies for zero-defect peripheral milling
MORELLI, LORENZO
2023
Abstract
Peripheral milling is one of the most used technologies in the mechanical industry thanks to its accuracy and versatility. Nonetheless these redeeming qualities may be compromised in cutting operations where the flexibility of both the tool and the workpiece is relevant. In such conditions the tool/workpiece flexibility may cause static deflections or vibrations leading to inacceptable surface errors. Due to the complexity of these mechanisms, the most suitable approach to deal with surface errors is the use of virtual predictive techniques. This thesis presents models and approaches aiming at ensuring the required accuracy on machined components when the tool/workpiece flexibility is limiting the process performances, fitting Industry 4.0 paradigm.File | Dimensione | Formato | |
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PhD_annual_report_form_Lorenzo_Morelli_completo2.pdf
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Revised_Thesis_SmartIndustry_LorenzoMorelli_clean2.pdf
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https://hdl.handle.net/20.500.14242/216508
URN:NBN:IT:UNIPI-216508