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Predictive framework for cutting force induced cylindricity error estimation in end milling of thin-walled components
Published in Elsevier Inc.
2020
Volume: 66
   
Pages: 209 - 219
Abstract
The static deflections of cutting tool and workpiece are the primary source for the deviation of machined components from the design specifications during end milling of thin-walled geometries. The deviations are expressed as per the Geometric Dimensioning and Tolerancing (GD&T) principles using size, form, and orientation of the features. This paper proposes a computational framework to estimate cutting force induced cylindricity error during end milling of thin-walled circular components. The framework combines computational elements such as Mechanistic force model, Finite Element Analysis (FEA) based workpiece deflection model, Cantilever beam formulation based tool deflection model, and Particle Swarm Optimization (PSO) based cylindricity estimation algorithm. It has been observed that the static deflections of a cutting tool and thin-walled component influence the cylindricity error considerably. The inevitable aspects associated with the end milling of thin-walled circular components such as concave-convex side machining and workpiece rigidity are investigated subsequently. It was observed that the cylindricity error during concave side machining is considerably smaller due to geometric configuration imparting adequate stiffness to thin-walled components. The study also demonstrated that an appropriate combination of productive cutting conditions and the component thickness could reduce cylindricity error considerably. The outcomes of the present study are substantiated by conducting a set of computational simulations and end milling experiments over a wide range of cutting conditions. The computational framework proposed in the present study can assist process planners in selecting appropriate cutting conditions to manufacture thin-walled circular components within tolerance limits specified by the designer. © 2020 Elsevier Inc.
About the journal
JournalData powered by TypesetPrecision Engineering
PublisherData powered by TypesetElsevier Inc.
ISSN01416359