4.7 Article

Factor analysis of selective laser melting process parameters with normalised quantities and Taguchi method

期刊

OPTICS AND LASER TECHNOLOGY
卷 119, 期 -, 页码 -

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.optlastec.2019.105592

关键词

Additive manufacturing; Parameters optimizing; Dimensionless quantities; Selective laser melting; 316L stainless steel

资金

  1. National Natural Science Foundation of China [11772344]
  2. National Key RAMP
  3. D Program of China [2016YFB1100700]

向作者/读者索取更多资源

Extensive experiments have been carried out to derive material-process-microstructure-properties relationships for powder bed fusion (PBF) process. Selecting a set of appropriate processing parameters to achieve high quality part is of great challenge, since the quality of part is affected by many factors involved in the process. However, a lot of investigations of processing parameters on performance of part merely focused on one or two parameters variation while others were fixed. A comprehensive study about the influence of multiple factors on selective laser melting (SLM) process is still lack of deep research. In this paper, normalised quantities, such as E-0*, q*, nu*, etc., and a dimensionless group of process variables are adopted to determine a processing window. Taguchi method is used to optimize the settings of processing parameters. Experiments were carried out by SLM with 316 L stainless steel powder. The following response variables, top surface roughness (R-a), hardness (HV) and density (rho) were measured. The effect of laser power q, scanning speed nu, hatch spacing h and their interactions, such as q x nu, q x h, nu x h, on top surface roughness (R-a), hardness (HV) and density (rho) was evaluated by Analysis of Variance (ANOVA). It is shown that laser power is of great significance among the parameters, while hatch spacing, scanning speed and their interactions affect the quality of samples with differently significant levels. The results of this research show that normalised processing map is a powerful tool for optimizing processing parameters to get high quality parts.

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