Prediction of geometrical characteristics and process parameter optimization of laser deposition AISI 316 steel using fuzzy inference

Laser metal deposition (LMD) process is an additive manufacturing technique that has attracted the interest of the automotive and aerospace industries due to its ability to manufacture parts with complex geometries and different types of metallic materials. However, the structure of the deposited la...

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Bibliographic Details
Published in:International journal of advanced manufacturing technology 2021-07, Vol.115 (5-6), p.1547-1564
Main Authors: Velázquez, Daniel René Tasé, Helleno, André Luís, Fals, Hipólito Carvajal, dos Santos, Raphael Galdino
Format: Article
Language:English
Subjects:
Adequacy
Aerospace industry
CAE) and Design
Computer-Aided Engineering (CAD
Design of experiments
Dilution
Engineering
Factorial analysis
Industrial and Production Engineering
Inference
Interaction parameters
Laser deposition
Lasers
Mechanical Engineering
Media Management
Optimization
Original Article
Process parameters
Stainless steels
Substrates
Variance analysis
Wetting
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Summary:Laser metal deposition (LMD) process is an additive manufacturing technique that has attracted the interest of the automotive and aerospace industries due to its ability to manufacture parts with complex geometries and different types of metallic materials. However, the structure of the deposited layers and the geometrical characteristics of the manufactured parts are influenced by the interaction among the deposition process parameters. In this paper, fuzzy inference (FIS) technique was used to develop two models for predicting the geometrical characteristics and for optimizing the LMD process parameters. LMD was performed using AISI 316 stainless steel powder and substrate. An experimental design, based on factorial analysis, was used to correlate the influence of selected deposition process parameters, laser power (Lp), powder flow (Pf) and focal length (Fl) with the process geometrical characteristics bead height (Bh), bead width (Bw), depth of penetration (Dp), dilution (d) and wetting angle (wa). The factors Lp and Fl were used with three operating levels each, and the factor Pf was used with two operating levels. An analysis of variance allowed identifying that the Pf affects the Bh, Bh/Bw ratio, d and wa, as well as the increase in Lp showed an increasing of the geometric characteristics Bw and Dp. The first FIS, for predicting the bead’s geometrical characteristics, presented high adequacy (error up to 8.43%) for assessing the experimental conditions. The second FIS showed through the output defuzzified index (ODI) measured the best possible process parameters interaction, given the studied operating conditions and the output variables assessed.
ISSN:0268-3768
1433-3015
DOI:10.1007/s00170-021-07269-y