Model-driven directed-energy-deposition process workflow incorporating powder flowrate as key parameter

被引:19
|
作者
Traxel, Kellen D. [1 ]
Malihi, Darin [1 ]
Starkey, Kyler [1 ]
Bandyopadhyay, Amit [1 ]
机构
[1] Washington State Univ, Sch Mech & Mat Engn, WM Keck Biomed Mat Res Lab, Pullman, WA 99164 USA
基金
美国国家科学基金会;
关键词
Additive manufacturing; Process modeling; Ti6Al4V; Directed energy deposition; CHALLENGES;
D O I
10.1016/j.mfglet.2020.08.005
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Process optimization for directed-energy-deposition, an industrial laser-based additive manufacturing technique, is a time-intensive endeavor for manufacturers. Herein we investigate the use of a modified analytical process-model based on powder-bed-fusion techniques, to predict quality build parameters by incorporating the effects of three key parameters: laser-power, scanning-speed, and powder flowrate. Titanium alloy (Ti6Al4V) tracks of varying parameters were built, studied, and used to predict parameters for quality builds used at different parameters. The model agreed well with experimental build quality at powder flowrates less than 6.5 g/min, whereas, higher flowrates created significant unmelted-particle regions, despite optimal parameter predictions. Processing of multi-layer bulk samples revealed that parameters in the optimal range account for relative densities >99%, indicating quality bulk processing parameters. Our results indicate that process modeling with the incorporation of powder feedrate as a key parameter is possible using a commercial laser-based additive manufacturing system. (C) 2020 Society of Manufacturing Engineers (SME). Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:88 / 92
页数:5
相关论文
共 50 条
  • [1] Process parameter optimization for laser powder directed energy deposition of Inconel 738LC
    Javidrad, Hamidreza
    Aydin, Huseyin
    Karakas, Burak
    Alptekin, Sertac
    Kahraman, Aylin Sahin
    Koc, Bahattin
    OPTICS AND LASER TECHNOLOGY, 2024, 176
  • [2] An Overview of the Process Mechanisms in the Laser Powder Directed Energy Deposition
    Piscopo, Gabriele
    Atzeni, Eleonora
    Saboori, Abdollah
    Salmi, Alessandro
    APPLIED SCIENCES-BASEL, 2023, 13 (01):
  • [3] Model-driven Derivation of BPMN Workflow Schemata from SOM Business Process Models
    Puetz, Corinna
    Sinz, Elmar J.
    ENTERPRISE MODELLING AND INFORMATION SYSTEMS ARCHITECTURES-AN INTERNATIONAL JOURNAL, 2010, 5 (02): : 57 - 72
  • [4] Process parameter study for enhancement of directed energy deposition powder efficiency based on single-track geometry evaluation
    Jardon, Zoe
    Ertveldt, Julien
    Hinderdael, Michael
    Guillaume, Patrick
    JOURNAL OF LASER APPLICATIONS, 2021, 33 (04)
  • [5] Incorporating Model-Driven Techniques into Requirements Engineering for the Service-Oriented Development Process
    Loniewski, Grzegorz
    Armesto, Ausias
    Insfran, Emilio
    ENGINEERING METHODS IN THE SERVICE-ORIENTED CONTEXT, 2011, 351 : 102 - 107
  • [6] Integration of a model-driven workflow into an industrial pharmaceutical facility: supporting process development of API crystallisation
    Pickles, Thomas
    Svoboda, Vaclav
    Marziano, Ivan
    Brown, Cameron J.
    Florence, Alastair J.
    CRYSTENGCOMM, 2024, 26 (34) : 4678 - 4689
  • [7] Investigation of dimensional and geometrical tolerances of laser powder directed energy deposition process
    Piscopo, Gabriele
    Salmi, Alessandro
    Atzeni, Eleonora
    PRECISION ENGINEERING-JOURNAL OF THE INTERNATIONAL SOCIETIES FOR PRECISION ENGINEERING AND NANOTECHNOLOGY, 2024, 85 : 217 - 225
  • [8] Systematic evaluation of process parameter maps for laser cladding and directed energy deposition
    Bax, Benjamin
    Rajput, Rohan
    Kellet, Richard
    Reisacher, Martin
    ADDITIVE MANUFACTURING, 2018, 21 : 487 - 494
  • [9] Numerical modeling of coaxial powder stream in laser-powder-based Directed Energy Deposition process
    Guan, Xiaoyi
    Zhao, Yaoyao Fiona
    ADDITIVE MANUFACTURING, 2020, 34
  • [10] A coupled fluid-mechanical workflow to simulate the directed energy deposition additive manufacturing process
    Beghini, Lauren L.
    Stender, Michael
    Moser, Daniel
    Trembacki, Bradley L.
    Veilleux, Michael G.
    Ford, Kurtis R.
    COMPUTATIONAL MECHANICS, 2021, 67 (04) : 1041 - 1057