Force Prediction in Robotized Ultrasonic Sheet Metal Forming Based on Finite Element Analysis and Artificial Neural Networks

The forces acting in the process of single point incremental forming (SPIF) change the geometry of the sheet metal. The tool-workpiece interaction process is non-linear due to the large deformations of the sheet metal, which determine the plastic behaviour, as well as the evolutionary boundary conditions resulting from the contact between the tool and the sheet. Instead of lubricating the contact surface of the forming tool and the sheet metal, an innovative environmentally friendly method to reduce the coefficient of friction by vibrating the sheet has been proposed. The finite element method (FEM) allowed a virtual evaluation of the deformation parameters of the SPIF process in order to determine the destructive loads. The FEM was chosen as a deterministic numerical tool to evaluate the set of defect parameters induced by forming forces. The paper also proposes a method for predicting the formation force using an artificial neural network (ANN), assuming that such a model is generalized to implicit data. In this context, an empirical analysis of the implementation of the ANN technique is performed.

Significant Contribution of Temperature on AISI D2 Tool Steel Ground Surface Characteristics and Integrities

The Controlled grinding is governed by the maximum surface temperature in the wheel-workpiece interaction. In this study, we demonstrate that temperature is the significant controller on the surface characteristic grinding, the surface integrity, the productivity and the fatigue life. Moreover, high temperature generated in abrasive processes is the main factor responsible on ground surface damage and its impact on the induced consequences in grinding of AISI D2 tool steel. The combined effects of abrasive type, cooling mode according to the cutting depth, on the temperature and residual stress distribution were highlighted by exploiting FEM. Obtained numerical results were validated with the experimental ones.

A Method to Determine the Minimum Chip Thickness during Longitudinal Turning

Micromachining, which is used for various industrial purposes, requires the depth of cut and feed to be expressed in micrometers. Appropriate stock allowance and cutting conditions need to be selected to ensure that excess material is removed in the form of chips. To calculate the allowance, it is essential to take into account the tool nose radius, as this cutting parameter affects the minimum chip thickness. Theoretical and numerical studies on the topic predominate over experimental ones. This article describes a method and a test setup for determining the minimum chip thickness during turning. The workpiece was ground before turning to prevent radial runout and easily identify the transition zone. Contact and non-contact profilometers were used to measure surface profiles. The main aim of this study was to determine the tool–workpiece interaction stages and the cutting conditions under which material was removed as chips. Additionally, it was necessary to analyze how the feed, cutting speed, and edge radius influenced the minimum chip thickness. This parameter was found to be dependent on the depth of cut and feed. Elastic and plastic deformation and ploughing were observed when the feed rate was lower than the cutting edge radius.

Investigation of Tool and Workpiece Interaction on Surface Quality While Diamond Turning of Copper Beryllium Alloy

Among all the materials, diamond turning of heterogeneous materials like copper beryllium (CuBe) poses serious machining challenges as the heterogeneity in the workpiece affects the quality of generated surface. Therefore, the present study is aimed to understand the effect of tool–workpiece interactions on the surface characteristics of heterogeneous CuBe workpiece material. Experiments and molecular dynamics simulation (MDS) were carried out to analyze the various surface and subsurface interactions during cutting. Results from the experiments on both the materials for whole cutting length show that the average roughness values on CuBe-machined surface are found to be ∼48% higher than those of copper (Cu). Scanning electron microscopy (SEM) results show that while deterministic lay pattern is obtained in the case of Cu, the CuBe-machined surface possesses near-random lay pattern, which is also reflected by the fast Fourier transform (FFT) spectrum of surface roughness profiles. Experimental and MDS results reveal that the hard precipitate suffers cracks which propagate vertically as well as radially and as the tool travels from Cu-rich phase to Be-rich phase, ductile to brittle transition in cutting mechanism is observed. Furthermore, it is observed that diamond-turned Cu and CuBe surfaces are contaminated by the oxides of C and Cu. MDS results verify the mechanisms involved in the surface and subsurface interactions during diamond turning.

Modeling of Tool-Workpiece Interaction in a Voxelized Framework

In the present study, a voxel based model for the interaction between cutting teeth of an arbitrary end mill geometry and a workpiece is presented. In this framework, the workpiece geometry is modeled using a voxelized representation that is dynamically updated as material is locally removed by each tooth of the cutting tool. A ray casting approach is used to mimic the process of the rake face of a tool moving through the workpiece material and to calculate the undeformed chip thickness and its variation in time. The resulting voxel based model framework was validated by comparison of predictions with experimentally measured milling forces. The results demonstrate the model’s ability to accurately simulate the interaction of cutting teeth with the bulk material of the workpiece. Implications of this new voxel based model framework are briefly discussed in terms of utility for predicting local surface finish and computational scalability of complex cutting configurations.

The Development of High Speed Virtual Milling Test

The concept of a hardware-in-the-loop experiment for high speed milling is introduced in this paper. The tool-workpiece interaction is virtually implemented in the experiment while the milling machine with the spindle is used as real element. In this paper, the basic components of the experiment are presented, namely, a contactless displacement sensor, a computational algorithm of the cutting force and a contactless electromagnetic actuator are discussed. Experiments on the prototype of the electromagnetic actuator are also shown to illustrate the potential of the concept. A feasibility study of the hardware-in-the-loop experiment is given, where the effect of the time delay included in the experiment is investigated.