Process optimization has always been a crucial step for effective usage of metal additive manufacturing (AM) processes: it consists in establishing quantitative relations between final part's characteristics and process parameters to find their optimal combination and obtain a fully functional mechanical component. Experimental investigation techniques are usually employed for this purpose but they can be extremely expensive and time-consuming, especially when the output of the process depends on a large number of parameters, like for AM. Numerical simulation could represent an alternative solution: by reproducing the real process characteristics, a simulation could provide useful insights, allowing to evaluate the performance of the process for different parameter combinations without relying exclusively on expensive experimental campaigns. In this work, a finite element AM simulation based on the inherent strain (IS) method was developed and the prediction performance in terms of part's residual deformation was evaluated by comparing the numerical results with the measurements carried out on an experimental campaign. A new model calibration approach for prediction improvement was also implemented and it allowed to discover an unexpected behaviour of the model that strongly affects the validity of this method for AM simulation.

Limitations of the inherent strain method in simulating powder bed fusion processes

Bugatti, Matteo;Semeraro, Quirico
2018-01-01

Abstract

Process optimization has always been a crucial step for effective usage of metal additive manufacturing (AM) processes: it consists in establishing quantitative relations between final part's characteristics and process parameters to find their optimal combination and obtain a fully functional mechanical component. Experimental investigation techniques are usually employed for this purpose but they can be extremely expensive and time-consuming, especially when the output of the process depends on a large number of parameters, like for AM. Numerical simulation could represent an alternative solution: by reproducing the real process characteristics, a simulation could provide useful insights, allowing to evaluate the performance of the process for different parameter combinations without relying exclusively on expensive experimental campaigns. In this work, a finite element AM simulation based on the inherent strain (IS) method was developed and the prediction performance in terms of part's residual deformation was evaluated by comparing the numerical results with the measurements carried out on an experimental campaign. A new model calibration approach for prediction improvement was also implemented and it allowed to discover an unexpected behaviour of the model that strongly affects the validity of this method for AM simulation.
2018
Additive manufacturing (AM); Calibration; FEM; Inherent strain (IS); Simulation; Validation; Biomedical Engineering; Materials Science (all); Engineering (miscellaneous); Industrial and Manufacturing Engineering, Clean Sky 2 Joint Undertaking, European Union (EU), Horizon 2020; AMATHO - Additive Manufacturing for Tiltrotor housing, JTI-CS2-2015-CFP02-FRC-01-03
File in questo prodotto:
File Dimensione Formato  
Limitations of the inherent strain method in simulating powder bed fusion processes.pdf

Accesso riservato

: Publisher’s version
Dimensione 4.09 MB
Formato Adobe PDF
4.09 MB Adobe PDF   Visualizza/Apri
compressed_bugatti-semeraro2018.pdf

Open Access dal 17/06/2020

: Post-Print (DRAFT o Author’s Accepted Manuscript-AAM)
Dimensione 8.7 MB
Formato Adobe PDF
8.7 MB Adobe PDF Visualizza/Apri
H2020_CSJU_emblem.pdf

accesso aperto

Descrizione: EU emblem
: Altro materiale allegato
Dimensione 147.7 kB
Formato Adobe PDF
147.7 kB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1064416
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 104
  • ???jsp.display-item.citation.isi??? 83
social impact