Abstract:The development of additive manufacturing (AM) technology provides higher feasibility for designing and manufacturing lattice structures. However, the manufacturing process usually generates residual deformation and stress, and even produces cracking, thus affecting the performance of the parts. This work establishes a simulation model of the Ti-6Al-4V lattice structures during laser powder bed fusion (LPBF) based on the inherent strain method. Effects of geometric lattice parameters (inclination angle, rod di… Show more
“…The thermal stresses generated during the L-PBF process can persist elastically even after plastic deformation occurred during rapid cooling [25][26][27][28][29]. This residual stress was measured in the bottom region of specimens fabricated under conditions of 370 W, 380 W, and 390 W, with the corresponding results depicted in Figure 4.…”
Section: Microstructure Of As-built Specimensmentioning
confidence: 98%
“…Assuming that the recrystallization temperature is where more than 50% of the total area undergoes recrystallization, the recrystallization temperature under the laser power condition of 370 W was found to be above 1095 Therefore, there are limitations in determining the driving force for recrystallization with increasing laser power based on the EBSD test condition performed in this study. The thermal stresses generated during the L-PBF process can persist elastically even after plastic deformation occurred during rapid cooling [25][26][27][28][29]. This residual stress was measured in the bottom region of specimens fabricated under conditions of 370 W, 380 W, and 390 W, with the corresponding results depicted in Figure 4.…”
Section: Microstructure Of Heat-treated Specimensmentioning
Over the past few decades, there has been much research on additive manufacturing in both the academic and the industrial spheres to overcome the limitations of conventional manufacturing methods, thereby enabling the production of complex designs for improved performance. To achieve this purpose, it is crucial to meticulously set suitable laser parameters within the context of microstructural characteristics, including type and fraction of defects, texture development, residual stress, and grain size, etc. In the present study, we focused on recrystallization behavior, a type of relaxation process for accumulated thermal stress during the L-PBF process, as a function of laser power applied on the L-PBF process. The laser power has significant effects on the amount of recrystallized grain, directly related to the recrystallization temperature. Within the range of laser power used in this study, a downward trend was observed in the recrystallization temperature as the laser power increased from 370 W to 390 W. This trend suggests that higher laser power leads to a faster cooling rate, influenced by the volume of melt pool as well as the amount of heat dissipation from the melt pool, resulting in higher thermal stress during the process.
“…The thermal stresses generated during the L-PBF process can persist elastically even after plastic deformation occurred during rapid cooling [25][26][27][28][29]. This residual stress was measured in the bottom region of specimens fabricated under conditions of 370 W, 380 W, and 390 W, with the corresponding results depicted in Figure 4.…”
Section: Microstructure Of As-built Specimensmentioning
confidence: 98%
“…Assuming that the recrystallization temperature is where more than 50% of the total area undergoes recrystallization, the recrystallization temperature under the laser power condition of 370 W was found to be above 1095 Therefore, there are limitations in determining the driving force for recrystallization with increasing laser power based on the EBSD test condition performed in this study. The thermal stresses generated during the L-PBF process can persist elastically even after plastic deformation occurred during rapid cooling [25][26][27][28][29]. This residual stress was measured in the bottom region of specimens fabricated under conditions of 370 W, 380 W, and 390 W, with the corresponding results depicted in Figure 4.…”
Section: Microstructure Of Heat-treated Specimensmentioning
Over the past few decades, there has been much research on additive manufacturing in both the academic and the industrial spheres to overcome the limitations of conventional manufacturing methods, thereby enabling the production of complex designs for improved performance. To achieve this purpose, it is crucial to meticulously set suitable laser parameters within the context of microstructural characteristics, including type and fraction of defects, texture development, residual stress, and grain size, etc. In the present study, we focused on recrystallization behavior, a type of relaxation process for accumulated thermal stress during the L-PBF process, as a function of laser power applied on the L-PBF process. The laser power has significant effects on the amount of recrystallized grain, directly related to the recrystallization temperature. Within the range of laser power used in this study, a downward trend was observed in the recrystallization temperature as the laser power increased from 370 W to 390 W. This trend suggests that higher laser power leads to a faster cooling rate, influenced by the volume of melt pool as well as the amount of heat dissipation from the melt pool, resulting in higher thermal stress during the process.
“…They highlighted gaps and research opportunities in the areas of residual stress optimization, in additive manufacturing processes. Gan et al [14] established a simulation model of the Ti-6Al-4V lattice structures during laser powder bed fusion (LPBF) based on the inherent strain method and studied the effects of geometric lattice parameters on residual deformation and stress. They emphasised that the effects of supports on residual deformation and stresses cannot be ignored.…”
Laser powder bed fusion (L-PBF) is widely used in automotive, aerospace, and biomedical applications thanks to its ability to produce complex geometries. In spite of its advantages, parts produced with this technology can show distortion due to the residual stresses developed during the printing process. For this reason, numerical simulations can be used to predict thermal gradients and residual stresses that can result in part distortion. Thus, instead of performing experimental tests and using a trial and error approach, it is possible to use numerical simulation to save time and material. In this work, the effect of laser power and scan speed on residual stress and part distortion was analysed using a commercial finite element analysis (FEA) software DEFORM-3D™ with a layer-by-layer approach. Moreover, the accuracy of the numerical model with respect to process parameters and the utilised mesh was also studied. The results obtained from the numerical simulation were compared to the actual distortions to evaluate the accuracy of the FEM model. The predicted distortions using FEM analysis well fit the trend of the measured ones. The accuracy of the numerical model increases by considering a finer mesh.
“…Optimizing the printing process can also help to reduce defects and improve the quality of the printed parts [6]. For example, by predicting the temperature and stress distributions during the printing process, manufacturers can identify potential defects and adjust the printing parameters to prevent them [7], [8]. Additionally, in-situ monitoring techniques, such as infrared cameras and acoustic sensors, can help detect defects in real time and enable corrective actions to be taken during printing [9].…”
Industry 4.0, also known as the Fourth Industrial Revolution, is a term used to describe the current trend of automation and data exchange in manufacturing and other industries. The Internet of Things (IoT) plays a crucial role in Industry 4.0 by connecting devices, machines, and products to the Internet and enabling real-time data exchange. Moreover, additive manufacturing is a key developing manufacturing technology in Industry 4.0. New technologies such as data analysis with Artificial Intelligence and machine vision are widely used in optimization. However, in a lab environment, these technologies depend on the data collected from the process. For such work, the researchers should be able to focus on their core research rather than on the development of infrastructure to collect and analyse the data. This research presents an open software and hardware IoT solution to monitor a laser wire direct energy deposition system installed in a cartesian type 3-axis machine tool. The IoT solution adopts three open-source tools for core issues, such as 1) interoperability, flexibility, and availability; 2) data storage; and 3) data visualization of sensor data and manufacturing process signals. The system architecture is based on one or more edge devices connected to sensors and forwarding their data toward a local API endpoint. The endpoint is created with Node-RED, an open-source visual flow-based development tool for IoT data. Node-RED forwards the data to an open-source InfluxDB database. Finally, the data is visualized with an open-source Grafana application. The system is prototyped, designed, implemented, and tested in a lab environment to monitor a laser-wire direct energy deposition process. The significance of such a flexible IoT data collection system for research and development projects can be integral. Thus, providing savings in time and money can substantially speed up the development of new technologies where the value arises from the sensor data and its analysis.
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