Process optimization for directed energy deposition of SS316L components

Pei Yi Lin, Fang Cheng Shen, Kuo Tsai Wu, Sheng Jye Hwang, Huei Huang Lee

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)


Directed energy deposition (DED), also known as laser cladding, is a metal additive manufacturing process in which a high-power laser combined with a coaxial powder delivery system is used to additively manufacture a three-dimensional metal component layer-by-layer. Due to its convenience and superior quality, DED has gained popularity in recent years. However, despite many advantages, it has low deposition efficiency and produces parts with poor surface evenness, high porosity, and poor mechanical properties. This study performs one-factor-at-a-time experiments to valuate five DED processing parameters, namely the laser and powder focus point positions, laser head raising height (Z-offset), laser power, powder feed rate, and laser scanning speed. The laser and powder focus point positions and the Z-offset are first adjusted to maximize the surface evenness and deposition efficiency. Several experiments are then performed to investigate the effects of laser power, powder feed rate, and laser cladding speed on the porosity and dilution of DED-built parts. Finally, a mathematical model is proposed to predict the quality (i.e., dilution) of DED-built parts as a function of DED processing parameters. Based on the results, the optimal focus point positions and Z-offset are found. The variations of porosity and dilution with three processing parameters are shown. The proposed model can be used to set up DED processing parameters to produce higher quality parts on the first attempt.

Original languageEnglish
Pages (from-to)1387-1400
Number of pages14
JournalInternational Journal of Advanced Manufacturing Technology
Issue number5-6
Publication statusPublished - 2020 Nov 1

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Software
  • Mechanical Engineering
  • Computer Science Applications
  • Industrial and Manufacturing Engineering


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