K.A. Desai

TL;DR: In this paper, a mathematical model computing process geometry parameters which include cutter/workpiece engagements and instantaneous uncut chip thickness in the presence of cutter runout is presented, which is more realistic as it accounts for interaction of cutting tooth trajectory with that of preceding teeth trajectories.

TL;DR: In this paper, a cutting force model accounting for change in process geometry due to static deflections of tool and workpiece is adopted in this work, which is used in predicting tool and piece deflection induced surface errors on machined components and then compensating the same by modifying tool path.

TL;DR: In this article, a methodology to classify surface error profiles and to relate the same with cutting conditions in terms of axial and radial engagement between cutter and workpiece is presented, where the proposed characterization scheme has been validated using computational studies and machining experiments.

TL;DR: In this paper, the effect of direction of parameterization and cutter diameter on process geometry, cutting forces, and surface error in peripheral milling of curved geometries has been investigated, where the curvature varies continuously along tool path, and the process geometry variables, namely feed per tooth, engagement angle, and maximum undeformed chip thickness too vary along toolpath.

TL;DR: A novel approach combining the mechanistic model and the supervised neural network (NN) model to predict instantaneous cutting force variation during the end milling operation is presented.