Browsing by Subject "metal additive manufacturing"

Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    Optimization of Chessboard Scanning Strategy Using Genetic Algorithm in Multi-Laser Additive Manufacturing Process
    (ASME, 2021-02) Malekipour, Ehsan; Valladares, Homero; Shin, Yung; El-Mounayri, Hazim; Mechanical and Energy Engineering, School of Engineering and Technology
    Residual stress and manufacturing time are two serious challenges that hinder the widespread industry adoption and implementation of the powder-bed fusion (PBF) process. Commercial Multi-Laser PBF (ML-PBF) systems have been developed by several vendors in recent years, which dramatically increase the production rate by employing more heat sources (up to 4 laser beams). Although numerous research works conducted toward mitigation of the effects of residual stress on printed parts in the Single Laser PBF (SL-PBF) process, no research work on this topic has been reported for the ML-PBF process to date. One of the most efficient real-time approaches to mitigate the influence of residual stress and as such the process lead time effectively is to improve the scanning strategy. This approach can be also implemented effectively in the ML-PBF process. In this work, we extend the previously developed GAMP (Genetic Algorithm Maximum Path) strategy for optimizing the scanning path in ML-PBF. The E-GAMP (the Extended GAMP) strategy manipulates the printing topology of the islands and generates more thermally efficient scanning patterns for the chessboard scanning strategy in ML-PBF. This strategy extends the single thermal heat source to multiple ones (2 as well as 3 lasers). To validate the effectiveness of the proposed strategy, we simulate the thermal distribution throughout a simple rectangular layer by ABAQUS for both the traditional successive scanning strategy and the E-GAMP strategy. The results demonstrate that the E-GAMP strategy considerably decreases the manufacturing time while it reduces the maximum temperature gradient, or in other words, generates a more uniform temperature distribution throughout the exposure layer.
  • Thumbnail Image
    Item
    Scanning Strategies in the PBF Process: A Critical Review
    (ASME, 2021-02) Malekipour, Ehsan; El-Mounayri, Hazim; Mechanical and Energy Engineering, School of Engineering and Technology
    The powder-bed fusion (PBF) process is capable of producing near-fully dense metallic parts; however, various defects — particularly thermal abnormalities — can still be observed during the process. Some of these thermal defects — cracks, distortion, delamination of layers, and microporosity — cannot be removed by post-processing operations. The majority of these abnormalities are the result of residual stress, heat accumulation, lack of inter-track /inter-layer bonding, lack of powder fusion, or a combination of these factors. Modifying the scanning strategy (the topology of scanning tracks) can efficiently mitigate these abnormalities by adjusting the process parameters and adopting proper scanning patterns. The implementation of different scanning strategies significantly changes the ultimate quality of printed parts and manufacturing process lead time. Choosing a proper scanning strategy minimizes the residual stress and internal porosity, generates homogeneous microstructure, and avoids heat accumulation throughout the part during the printing process. In this work, we conducted a critical review of different scanning strategies, their pros and cons, limitations, and influence on the resulting properties of fabricated parts. Furthermore, we report the latest efforts for improvement of the current scanning strategies and introduce the-state-of-the-art strategies in the multi-laser PBF (ML-PBF) process. The insights provided here can assist scholars in evaluating existing scanning strategies and scanning patterns, and in identifying ways both to overcome scanning limitations and to modify them. On the other hand, it can assist manufacturers in selecting the best scanning strategies for their products based on their designs, demands, and resources.