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 automotive and aerospace industries due to its ability manufacture parts with complex geometries different types metallic materials. However, structure deposited layers geometrical characteristics manufactured are influenced by interaction among parameters. In this paper, fuzzy inference (FIS) was used develop two models for predicting optimizing LMD performed using AISI 316 stainless steel powder substrate. An experimental design, based on factorial analysis, correlate influence selected parameters, laser power (Lp), flow (Pf) focal length (Fl) bead height (Bh), width (Bw), depth penetration (Dp), dilution (d) wetting angle (wa). The factors Lp Fl were three operating levels each, factor Pf levels. analysis variance allowed identifying affects Bh, Bh/Bw ratio, d wa, as well increase in showed increasing geometric Bw Dp. first FIS, bead’s characteristics, presented high adequacy (error up 8.43%) assessing conditions. second FIS through output defuzzified index (ODI) measured best possible parameters interaction, given studied conditions variables assessed.