Development of a Novel System for Adaptive Machining of Near-Net-Shape Components

Near-net-shape components are popular among the aerospace industry for low material waste and high manufacturing efficiency. However, it is difficult to machine such components into final shapes because the machining allowance is often distributed unevenly and even insufficient. This paper proposed a novel system for adaptive machining near-net-shape components, which integrates units like on-machine measurement based on probe and ultrasonic-sensor, machining allowance constrained localization, tolerance range constrained shape reconstruction, and TCP (tool cutter position) template-based NC programming. Firstly, localization and free form deformation (FFD)-based shape construction are performed within the tolerance ranges of the component, and an even distribution of the machining allowance can be obtained. Next, the quick NC programming that directly manipulates the TCPs by using spatial deformation is introduced. Last, the data transmission between units is illustrated. A case study of the machining titanium turbine blade is performed, which validates the proposed system.

Surface Integrity Investigation to Determine Rough Milling Effects for Assessment of Machining Allowance for Subsequent Finish Milling of Alloy 718

The planned material volume to be removed from a blank to create the final shape of a part is commonly referred to as allowance. Determination of machining allowance is essential and has a great impact on productivity. The objective of the present work is to use a case study to investigate how a prior rough milling operation affects the finish machined surface and, after that, to use this knowledge to design a methodology for how to assess the machining allowance for subsequent milling operations based on residual stresses. Subsequent milling operations were performed to study the final surface integrity across a milled slot. This was done by rough ceramic milling followed by finish milling in seven subsequent steps. The results show that the up-, centre and down-milling induce different stresses and impact depths. Employing the developed methodology, the depth where the directional influence of the milling process diminishes has been shown to be a suitable minimum limit for the allowance. At this depth, the plastic flow causing severe deformation is not present anymore. It was shown that the centre of the milled slot has the deepest impact depth of 500 µm, up-milling caused an intermediate impact depth of 400 µm followed by down milling with an impact depth of 300 µm. With merged envelope profiles, it was shown that the effects from rough ceramic milling are gone after 3 finish milling passes, with a total depth of cut of 150 µm.

Robust Chatter Stability Prediction of the Milling Process considering Uncertain Machining Positions

Milling stability is a function of the tool point frequency response functions (FRFs), which vary with the movements of the moving parts within the whole machine tool work volume. The position-dependent tool point FRFs result in uncertain prediction of the stability lobe diagram (SLD) for chatter-free machining parameter selection. Taking the variations of modal parameters to represent the variations of tool point FRFs, this paper introduces the edge theorem to predict the robust milling chatter stability. The application of the edge theorem requires the minimum and maximum modal parameters within the machining space defined by the machining position and machining allowance information. Then, radial basis function artificial neural networks (RBFANNs) are used to predict the position-dependent modal parameters in X and Y directions based on the sample information of machining positions and related modal parameters at the tool point. Moreover, sample machining spaces are determined based on the aforementioned sample positions, and the trained RBFANNs are used to obtain corresponding sample extreme modal parameters. On this basis, RBFANNs for predicting the position and machining allowance-dependent extreme modal parameters can also be trained, and they are combined with the edge theorem and zero exclusion condition to calculate robust pairs of the spindle speed (n) and limiting axial cutting depth (aplim) and then plot the robust SLD (RSLD). A case study was performed on a real three-axial vertical machining center, and the plotted RSLD considering position variations was compared with the traditional SLD. Results of the chatter tests show that the RSLD can provide more reliable (ap, n) pairs to guarantee the milling stability, validating the feasibility of the proposed robust milling chatter stability prediction method.

Determining the machining allowance for WAAM parts

In order to decrease mass, and thus fulfil the targets for airplane traffic emission reduction, the amount of titanium alloys used for structural components is rising. With the conventional milling process, low material utilization and short tool life lead to high manufacturing costs. Therefore, a process chain consisting of wire and arc additive manufacturing (WAAM) and machining is developed. To realize its full potential, the machining process needs to be adapted to the near-net shaped components. A special focus lies on the machining allowance, since it influences both processes and in result the final part quality. In this paper a method to model the machining allowance is proposed and verified by analysing the changes from waviness to surface roughness occurring during peripheral milling of WAAM parts.

The use of a measuring arm with a laser scanner for analysis and support of regenerative surfacing processes of forging dies

The article presents the results of research conducted in order to develop the technology of regenerative surfacing of forging dies. The selected example shows how the use of a measuring arm with a laser scanner can be used to support the regeneration process. The tests were conducted in industrial conditions of a forging die. The analysis of the regeneration process was carried out at each of 4 stages: after wear in the forging process, after initial machining, after regenerative surfacing and after final machining. It has been shown that scanning can be used to develop programs for mechanical pre- treatment, to measure the volume of padding welds, to determine the amount of finishing allowance, to verify the effectiveness of the surfacing process and to control the quality of the die before the forging process. The obtained results confirmed the effectiveness of the regeneration carried out. In terms of performance, it has been shown that too much padding weld's material is a machining allowance. For this reason, the treatment is time and energy consuming and about 68% of the padding weld's material is waste or chips. The analysis showed the possibility of saving up to 45% of the weld metal material by using reasonable allowances of smaller thickness. These results indicate the need to modify the regeneration technology and the legitimacy of using robotic surfacing, which can provide greater precision and repeatability in the layingof padding weld’s beads. The next stage of research will be robotization of the analyzed forging die regeneration process using WAAM technology.

Analysis of Multi-Objective Optimization of Machining Allowance Distribution and Parameters for Energy Saving Strategy

Machining allowance distribution and related parameter optimization of machining processes have been well-discussed. However, for energy saving purposes, the optimization priorities of different machining phases should be different. There are often significant incoherencies between the existing research and real applications. This paper presents an improved method to optimize machining allowance distribution and parameters comprehensively, considering energy-saving strategy and other multi-objectives of different phases. The empirical parametric models of different machining phases were established, with the allowance distribution problem properly addressed. Based on previous analysis work of algorithm performance, non-dominated sorting genetic algorithm II and multi-objective evolutionary algorithm based on decomposition were chosen to obtain Pareto solutions. Algorithm performances were compared based on the efficiency of finding the Pareto fronts. Two case studies of a cylindrical turning and a face milling were carried out. Results demonstrate that the proposed method is effective in trading-off and finding precise application scopes of machining allowances and parameters used in real production. Cutting tool life and surface roughness can be greatly improved for turning. Energy consumption of rough milling can be greatly reduced to around 20% of traditional methods. The optimum algorithm of each case is also recognized. The proposed method can be easily extended to other machining scenarios and can be used as guidance of process planning for meeting various engineering demands.