Model for estimating the depth of cut with regard to machine tool system dynamics and in-process gauge position
Authors
A. V. Akintseva
South Ural State University, Chelyabinsk
P. P. Pereverzev
South Ural State University, Chelyabinsk
V. G. Nekrutov
South Ural State University, Chelyabinsk
D. V. Moiseev
Sevastopol State University, Sevastopol
V. G. Shalamov
South Ural State University, Chelyabinsk
B. A. Lopatin
South Ural State University, Zlatoust Branch, Zlatoust
A. V. Morozov
Vladimir State University named after A. and N. Stoletovs, Vladimir
Keywords:
plunge cylindrical grinding, cutting depth, technological system dynamics, active control device (ACD), machining accuracy, digital twin
Abstract
The relevance of the study is driven by the lack of effective digital tools in mechanical engineering for predicting the stability of surface machining accuracy during grinding. This leads to costly pilot tests, understated cutting conditions, and the production of defective parts. External plunge grinding operations, which are final for precision parts, present a particular challenge. Existing models often fail to account for the combined influence of dynamic processes in the technological system (TS), variable workpiece compliance, and the position of the active control device (ACD). The aim of this work is to develop a cutting depth model that integrates these factors to improve prediction accuracy. The paper analyzes the limitations of existing static approaches and substantiates the necessity of considering dynamic vibrations that lead to periodic loss of contact between the wheel and the workpiece. Based on established analytical relationships between cutting force, elastic deformations, workpiece mass, and dynamic parameters of the TS, a comprehensive model is proposed. The model allows for calculating the actual cutting depth, current workpiece dimensions, and radial forces throughout the entire step-feed cycle. The conducted simulation demonstrates the significant impact of dynamics: an increase in workpiece mass can raise the actual radial feed by up to 16 %, cause fluctuations in feed rate of up to ±46 %, and fluctuations in radial cutting force of up to ±34 % compared to static calculations. The developed model serves as a basis for creating a digital twin of the grinding process, enabling virtual verification and optimization of technological cycles, and predicting indicators of form and dimensional accuracy. This paves the way for reducing defects and increasing productivity.
