Systematic approach for determining optimal processing parameters to produce parts with high density in selective laser melting process

Tran, Hong Chuong; Lo, Yu Lung

doi:10.1007/s00170-019-04517-0

Cited by 58 publications

(38 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…When forming uneven tracks, for example in the case of the humping or balling effects, the tracks are irregular, which lead to adjacent tracks and successive layers insufficiently melting and, as a result, lack-of-fusion porosity occurs. The correlation between the shape and size of the melt pool/single tracks and porosity in 3D parts has been proven in many investigations (Yadroitsev, 2009;Tran and Lo, 2019;Kuo et al, 2020). The occurrence of defects during the L-PBF process was also described in detail in Kyogoku and Ikeshoji (2020) and Oliveira et al (2020).…”

Section: Introductionmentioning

confidence: 90%

Monitoring of Laser Powder Bed Fusion by Acoustic Emission: Investigation of Single Tracks and Layers

et al. 2021

View full text Add to dashboard Cite

Quality concerns in laser powder bed fusion (L-PBF) include porosity, residual stresses and deformations during processing. Single tracks are the fundamental building blocks in L-PBF and their shape and geometry influence subsequent porosity in 3D L-PBF parts. The morphology of single tracks depends primarily on process parameters. The purpose of this paper is to demonstrate an approach to acoustic emission (AE) online monitoring of the L-PBF process for indirect defect analysis. This is demonstrated through the monitoring of single tracks without powder, with powder and in layers. Gas-borne AE signals in the frequency range of 2–20 kHz were sampled using a microphone placed inside the build chamber of a L-PBF machine. The single track geometry and shape at different powder thickness values and laser powers were studied together with the corresponding acoustic signals. Analysis of the acoustic signals allowed for the identification of characteristic amplitudes and frequencies, with promising results that support its use as a complementary method for in-situ monitoring and real-time defect detection in L-PBF. This work proves the capability to directly detect the balling effect that strongly affects the formation of porosity in L-PBF parts by AE monitoring.

show abstract

Section: Introductionmentioning

confidence: 90%

Monitoring of Laser Powder Bed Fusion by Acoustic Emission: Investigation of Single Tracks and Layers

et al. 2021

View full text Add to dashboard Cite

show abstract

“…After acquiring the data of the process parameters, chamber images and MPIs respectively from the printing controller, overview CCD and coaxial CCD, the printing features can be extracted and utilized to estimate the built quality ̂( ) at time k. In this work, the polishing compensator will adjust the polishing process parameters (e.g. laser power and scan speed) to perform the polishing function based on Table 1 [32].…”

Section: The Polishing Compensationmentioning

confidence: 99%

MPI-Based System 2 for Determining LPBF Process Control Thresholds and Parameters

Adnan

Yang

Kuo

et al. 2021

IEEE Robot. Autom. Lett.

Self Cite

View full text Add to dashboard Cite

Determining thresholds of the primary control loops (System 1) of an additive manufacturing (AM) process is challenging when realizing System 1 with its fast and intuitive capability for adapting to different metal powers, machine configurations, and process parameters. Based on the convolution neural network and long short-term memory models, this paper presents a secondary tuning loop (System 2) to classify the types of melt-pool images (MPIs) from a coaxial camera online, suggest polishing parameters, and determine the control thresholds of System 1 offline. Case studies indicate that the thresholds and parameters of System 1 including smoke discharging, powder coating, and laser polishing of control loops of a laser powder bed fusion (LPBF) machine can be more deliberatively and logically decided by the proposed MPI-based System 2.

show abstract

“…Density of the additively manufactured part built via L-PBF has a crucial impact on mechanical properties of the fabricated component. An approach to identify processing parameters for producing high-density parts was employed to select the processing conditions, as described in the previous studies [31][32][33][34]. Tong Tai AM250 selective laser melting (SLM) machine (Kaohsiung, Taiwan), equipped with a 50-400 W YAG laser with the laser spot size of D4sigma = 54 µm, was used to fabricate rectangular bar shape samples with dimensions of 10 × 5 × 5 mm 3 .…”

Section: Build Processmentioning

confidence: 99%

Analytical Modeling of Residual Stress in Laser Powder Bed Fusion Considering Part’s Boundary Condition

Mirkoohi

Tran

et al. 2020

Crystals

Self Cite

View full text Add to dashboard Cite

Rapid and accurate prediction of residual stress in metal additive manufacturing processes is of great importance to guarantee the quality of the fabricated part to be used in a mission-critical application in the aerospace, automotive, and medical industries. Experimentations and numerical modeling of residual stress however are valuable but expensive and time-consuming. Thus, a fully coupled thermomechanical analytical model is proposed to predict residual stress of the additively manufactured parts rapidly and accurately. A moving point heat source approach is used to predict the temperature field by considering the effects of scan strategies, heat loss at part’s boundaries, and energy needed for solid-state phase transformation. Due to the high-temperature gradient in this process, the part experiences a high amount of thermal stress which may exceed the yield strength of the material. The thermal stress is obtained using Green’s function of stresses due to the point body load. The Johnson–Cook flow stress model is used to predict the yield surface of the part under repeated heating and cooling. As a result of the cyclic heating and cooling and the fact that the material is yielded, the residual stress build-up is precited using incremental plasticity and kinematic hardening behavior of the metal according to the property of volume invariance in plastic deformation in coupling with the equilibrium and compatibility conditions. Experimental measurement of residual stress was conducted using X-ray diffraction on the fabricated IN718 built via laser powder bed fusion to validate the proposed model.

show abstract

Systematic approach for determining optimal processing parameters to produce parts with high density in selective laser melting process

Cited by 58 publications

References 29 publications

Monitoring of Laser Powder Bed Fusion by Acoustic Emission: Investigation of Single Tracks and Layers

Monitoring of Laser Powder Bed Fusion by Acoustic Emission: Investigation of Single Tracks and Layers

MPI-Based System 2 for Determining LPBF Process Control Thresholds and Parameters

Analytical Modeling of Residual Stress in Laser Powder Bed Fusion Considering Part’s Boundary Condition

Contact Info

Product

Resources

About