Fuzzy logic-based inference system for prediction of energy input in laser metal deposited Aisi316 single-beads

Tipo
Artigo de evento
Data de publicação
2020
Periódico
32nd European Modeling and Simulation Symposium, EMSS 2020
Citações (Scopus)
3
Autores
Tase Velazquez D.R.
Helleno A.L.
de Oliveira M.C.
Fals H.C.
Macias E.J.
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Resumo
© 2020 The Authors.Laser metal deposition (LMD) process has the capability to produce functional and complex 3D parts. The deposits characteristics are strongly influenced by the deposition parameters and volume energy input. The aims of this paper is to predict using a fuzzy logic-based inference system (FIS), the volume energy generated after depositing AISI 316 SS single-beads by LMD. Previously to FIS modeling, the influence of laser power (Lp), laser scan speed (Lss), powder flow (Pf) and focal length (Fl) on deposited beads were studied by analyzing the response-variables bead height (Bh) and bead width (Bw). ANOVA allowed identifying that Pf mostly affect the Bh, and Lp has greater significance on Bw. Predictive FIS modeled presented high adequacy assessing the experimental conditions, showing an average relative error of 4.76 %. Thus, the proposed FIS can be can be effectively utilized to predict the volume energy input and be integrated within an automated LMD environment to reduce complexities in process planning activities and increase process stability.
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Assuntos Scopus
Average relative error , Deposition Parameters , Experimental conditions , Focal lengths , Inference systems , Laser metal deposition , Laser scan speed , Process stability
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