A novel approach of online monitoring for laser powder bed fusion defects: Air-borne Acoustic Emission and Deep Transfer Learning

Li, Zhiwen; Zhang, Zhifen; Zhang, Shuai; Bai, Zijian; Qin, Rui; Huang, Jing; Wang, Jie; Huang, Ke; Zhang, Qi; Wen, Guangrui

doi:10.1016/j.jmapro.2023.07.064

Cited by 4 publications

(2 citation statements)

References 30 publications

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“…A few technical obstacles, including AM's rough surface roughness, which is incomparable to that of traditional production techniques like machining and injection molding, are impeding the full commercialization of AM technology [17,18]. The general surface quality is addressed by the AM community, especially in the AM process field, using simple profile surface texture criteria like Ra and Rq, although actual parameters are showing to be more beneficial [19].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of 3D Printing Orientation on Volume Parameters and Mechanical Properties of As-Build TI64ELI

Lebea,

Desai,

Ngwangwa

et al. 2024

Metals

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The discovery of the utility of various titanium alloys as implant biomaterials has resulted in these materials becoming far more popular than other metals in the medical world. However, the production of these materials using additive manufacturing has its own challenges some of those being the surface finish that can be used as an implantology material. As such, the purpose of this study is to evaluate the influence of 3D-printed Ti64ELI on the as-built samples printed at 60°, 90°, and 180° orientations. Such studies are very limited, specifically in the development of the laser shock peening surface modification of dental implants. The study showed that each mechanical test that was performed contributes differently to the printing orientation, e.g., some tests yielded better properties when 180° printing orientation was used, and others had poorer properties when a 180° printing orientation was used. It was observed that 60° testing yielded a micro-hardness value of 349.6, and this value was increased by 0.37% when 90° orientation was measured. The lowest HV value was observed under a 180° orientation with 342.2 HV. The core material volume (Vmc) was 0.05266 mm3/mm2 at a 60° orientation, which increased by 11.48% for the 90° orientation. Furthermore, it was observed that the surface roughness (Sa) at 60° orientation was 43.68 μm. This was further increased by 6% when using the 90° orientation.

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Section: Introductionmentioning

confidence: 99%

Evaluation of 3D Printing Orientation on Volume Parameters and Mechanical Properties of As-Build TI64ELI

Lebea,

Desai,

Ngwangwa

et al. 2024

Metals

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show abstract

“…At this stage, several monitoring methods have been adopted to investigate online monitoring systems for process quality. These methods primarily focus on monitoring processing signals related to the manufacturing process or quality, such as heat 7 and acoustics 8 etc. However, the sensors used in these methods generally need to be installed inside the printing chamber.…”

Section: Introductionmentioning

confidence: 99%

Data-fusion for in-situ monitoring and molten state identification during LPBF of NiCoCr medium-entropy alloy

Li,

Yan,

2024

Sci Rep

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Laser powder bed fusion (LPBF) is an additive manufacturing technology with high practical value. In order to improve the quality of the fabricated parts, process monitoring has become a crucial solution, offering the potential to ensure manufacturing stability and repeatability. However, a cardinal challenge involves discerning a precise correlation between process characteristics and potential defects. This paper elucidates the integration of an off-axis vision monitoring mechanism via a high-speed camera focused on capturing the single-track melting phenomenon. An innovative image processing method was devised to segment the plume and spatters, while Kalman filter was employed for multi-object tracking of the spatters. The features of both the plume and spatters were extracted, and their relationship with molten states was investigated. Finally, the PSO-XGBoost algorithm was utilized to identify five molten states, achieving an accuracy of 92.16%. The novelty of this approach resides in its unique combination of plume characteristics, spatter features, and computationally efficient machine learning models, which collectively address the challenge of limited field of view prevalent in real production scenarios, thereby enhancing process monitoring efficacy. Relative to existing methodologies, the proposed PSO-XGBoost approach offers heightened accuracy, convenience, and appropriateness for the monitoring of the LPBF process. This work provides an effective and novel approach to monitor the LPBF process and evaluate the part fabrication quality for complex and changeable working conditions.

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In-situ monitoring in laser powder bed fusion based on acoustic signal time-frequency synchrosqueezing transform and multi-scale spatially interactive fusion convolutional neural network

Li,

Zhang,

Zhang

et al. 2024

Journal of Manufacturing Processes

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A novel approach of online monitoring for laser powder bed fusion defects: Air-borne Acoustic Emission and Deep Transfer Learning

Cited by 4 publications

References 30 publications

Evaluation of 3D Printing Orientation on Volume Parameters and Mechanical Properties of As-Build TI64ELI

Evaluation of 3D Printing Orientation on Volume Parameters and Mechanical Properties of As-Build TI64ELI

Data-fusion for in-situ monitoring and molten state identification during LPBF of NiCoCr medium-entropy alloy

In-situ monitoring in laser powder bed fusion based on acoustic signal time-frequency synchrosqueezing transform and multi-scale spatially interactive fusion convolutional neural network

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