Wander Pinto Ribeiro

Dr. Wander Pinto Ribeiro


Research Focus & Metrics

Academic Career Length

3Years (2024-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 January 2024 in REM - International Engineering Journal
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Journal Article
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WRWander Pinto Ribeiro
Wander Pinto Ribeiro
Carlos Henrique de OliveiraCarlos Henrique de Oliveira
Carlos Henrique de Oliveira
LOLeonardo Albergaria Oliveira
Leonardo Albergaria Oliveira
TBTarcísio Gonçalves de GONCALVES Brito
Tarcísio Gonçalves de GONCALVES Brito
EPEmerson José Paiva
Emerson José Paiva
RPRogério Peruchi
Rogério Peruchi
The metalworking industry faces challenges in maintaining process performance due to variables affecting product quality, particularly in processes requiring precise control over machined part finishes. Duplex stainless steels, known for their high strength, work hardening, and low thermal conductivity, pose specific machining challenges that can hinder producing high-quality components and equipment. This study aimed to determine optimal parameters for end milling of duplex stainless steel UNS S32205. Formulated as a combined objective function derived from minimizing the mean square error (MSE) for parameters Ra and ßf, subject to a common constraint. The optimization was conducted using generalized reduced gradient (GRG). A Pareto frontier was constructed, offering efficient results with Ra = 0.4534 μιη and Rt = 3.2671 μιη for varying weights assigned to Ra and Rt. Adjusting weights in the objective function allowed prioritization based on specific needs. Optimal input parameters were identified as cutting speed (vc) = 60.79 m/min, feed per tooth (fz = 0.15 mm/tooth, axial depth of cut (ap) = 0.90 mm, and radial depth of cut (ae) = 16.31 mm, simultaneously optimizing both parameters. This approach reduced the mean square error (RMSE), determining roughness Ra and Rt mean and variance, thus improving the machining process. Confirmatory trials using an orthogonal Taguchi arrangement (L9) yielded results within the algorithm's confidence interval. This research offers a robust methodology for optimizing machining parameters, enhancing product quality in the metalworking industry.