Fused Deposition Modeling is one of the most used additive manufacturing technology to produce prototypes and final parts without geometrical complexity limitations. One of the most limiting aspects of this technology is the obtainable roughness. Frequently, to comply with the component requirements, it is necessary to improve surface quality by finishing operations. Barrel Finishing is typically employed in industry to finish Fused Deposition Modeling components due to the advantage that the part does not need to be clamped and the process parameters are marginally affected by the part shape. The aim of this work is to develop a geometrical model of the deposited filament in order to predict the surface roughness of part after Barrel Finishing operation. The model depends upon the Fused Deposition Modeling process parameters, namely the layer thickness and the deposition angle, and the material removed during Barrel Finishing operation. The estimation of this quantity is measured as function of working time by a profilometer procedure showing an inverse square relationship, as confirmed by the statistical analysis. The proposed formulation is not restricted to average roughness: several parameters are provided. The theoretical models are validated by an experimental campaign. The comparison between modeled and experimental data shows significant reliability by means of statistical analysis. This formulation is a useful tool in Computer Aided Manufacturing step to choose the optimum combination of process parameters in order to obtain the desired results provided by Barrel Finishing operation.

Roughness prediction in coupled operations of fused deposition modeling and barrel finishing / Boschetto, Alberto; Bottini, Luana. - In: JOURNAL OF MATERIALS PROCESSING TECHNOLOGY. - ISSN 0924-0136. - STAMPA. - 219:(2015), pp. 181-192. [10.1016/j.jmatprotec.2014.12.021]

Roughness prediction in coupled operations of fused deposition modeling and barrel finishing

BOSCHETTO, Alberto
;
Bottini, Luana
2015

Abstract

Fused Deposition Modeling is one of the most used additive manufacturing technology to produce prototypes and final parts without geometrical complexity limitations. One of the most limiting aspects of this technology is the obtainable roughness. Frequently, to comply with the component requirements, it is necessary to improve surface quality by finishing operations. Barrel Finishing is typically employed in industry to finish Fused Deposition Modeling components due to the advantage that the part does not need to be clamped and the process parameters are marginally affected by the part shape. The aim of this work is to develop a geometrical model of the deposited filament in order to predict the surface roughness of part after Barrel Finishing operation. The model depends upon the Fused Deposition Modeling process parameters, namely the layer thickness and the deposition angle, and the material removed during Barrel Finishing operation. The estimation of this quantity is measured as function of working time by a profilometer procedure showing an inverse square relationship, as confirmed by the statistical analysis. The proposed formulation is not restricted to average roughness: several parameters are provided. The theoretical models are validated by an experimental campaign. The comparison between modeled and experimental data shows significant reliability by means of statistical analysis. This formulation is a useful tool in Computer Aided Manufacturing step to choose the optimum combination of process parameters in order to obtain the desired results provided by Barrel Finishing operation.
Fused deposition modeling; barrel finishing; roughness prediction; finishing operation; material removal estimation; surface improvement
01 Pubblicazione su rivista::01a Articolo in rivista
Roughness prediction in coupled operations of fused deposition modeling and barrel finishing / Boschetto, Alberto; Bottini, Luana. - In: JOURNAL OF MATERIALS PROCESSING TECHNOLOGY. - ISSN 0924-0136. - STAMPA. - 219:(2015), pp. 181-192. [10.1016/j.jmatprotec.2014.12.021]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/660242
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