Estimation of the Influence of Tool Wear on Force Signals: a Finite Element Approach in AISI 1045 Orthogonal Cutting

Industrial concerns arise regarding the significant cost of cutting tools in machining process. In particular, their improper replacement policy can lead either to scraps, or to early tool replacements, which would waste fine tools. ISO 3685 provides the flank wear end-of-life criterion. Flank wear is also the nominal type of wear for longest tool lifetimes in optimal cutting conditions. Its consequences include bad surface roughness and dimensional discrepancies. In order to aid the replacement decision process, several tool condition monitoring techniques are suggested. Force signals were shown in the literature to be strongly linked with tools flank wear. It can therefore be assumed that force signals are highly relevant for monitoring the condition of cutting tools and providing decision-aid information in the framework of their maintenance and replacement. the objective of this work is to correlate tools flank wear with numerically computed force signals. The present work uses a Finite Element Model with a Coupled Eulerian-Lagrangian approach. The geometry of the tool is changed for different inns of the model, in order to obtain results that are specific to a certain level of wear. The model is assessed by comparison with experimental data gathered earlier on fresh tools. Using the model at constant cutting parameters, force signals under different tool wear states are computed and provide force signals for each studied tool geometry. These signals are qualitatively compared with relevant data from the literature. At this point, no quantitative comparison could be performed on worn tools because the reviewed literature failed to provide similar studies in this material, either numerical or experimental. Therefore, further development of this work should include experimental campaigns aiming at collecting cutting forces signals and assessing the numerical results that were achieved through this work.