Experimental investigation of WEDM process through integrated desirability and machine learning technique on implant material

Journal of the Mechanical Behavior of Materials

Kumar Anish¹  Gupta Arun Kumar¹  Sharma Renu² 

[1] Department of Mechanical Engineering, M. M. deemed to be UniversityMullana-Ambala-133207 (Haryana), India;Department of Physics, M. M. deemed to be UniversityMullana-Ambala, 133207 (Haryana), India;

关键词: wedm;    cp-ti g2;    biocompatibility;    mrr;    sem;    surface morphology;    desirability function;    machine learning;   

DOI  :  10.1515/jmbm-2021-0005

来源: DOAJ

【 摘 要 】

CP-Ti G2 has become the preferred biocompatible material for various devices mainly used in orthopedic and dental implants and it is also used in aviation and aircraft. While CP-Ti G2 deals with good ductility, higher stiffness, and fatigue resistance. The novelty of present research work was attentive to the effect of WEDM factors on MRR. After machining, surface topography was examined through SEM. MRR was modeled through ANOVA to analyze the adequacy. It was observed that POT, POFT, PC, and SGV most significant factors. The WEDM factors have also been significantly deteriorating the morphology of machined samples in the form of craters, debris, and micro cracks. A multi-objective optimization ‘desirability’ function hybrid with a supervised machine learning algorithm was applied to obtain the optimal solutions. The results show a good agreement between actual and predicted values.

【 授权许可】

Unknown