Abstract ▼ AI-Helper

This thesis presents an effort to develop a complete research that covers the tree most fundamental aspects of end-milling research which are modeling, monitoring and evaluation. These three sectors of end-milling research provide a panoramic view of the process because they deal with issues that ar...

This thesis presents an effort to develop a complete research that covers the tree most fundamental aspects of end-milling research which are modeling, monitoring and evaluation. These three sectors of end-milling research provide a panoramic view of the process because they deal with issues that are related to pre-process planning, in-process monitoring and control for optimal results, and post-process evaluation that assists engineers to draw conclusions and make remarks based on the obtained results. The ultimate goal of modern manufacturing systems is to be able to complete full product fabrication without any human intervention thus reaching absolute levels of automation through the process. To achieve such levels of automation and to be able to minimize human factor it is necessary to understand the underlying process and to be able to simulate it accurately. Additionally, full automation means being able to monitor the process for the occurrence of instabilities and being able to react to those instabilities. Last but not least, a fully automated manufacturing system should be able to evaluate itself by using objective methods that would not depend on personal features.
In this thesis a semi-analytical model for the prediction of cutting forces in ball end-milling for application in sculptured surface machining is presented. The model takes under consideration tool runout and its impact on chip geometry and 3D surface topography. The trajectory of the end-mill flutes is implemented as parameterized surface based on the axial elevation and angular position. The geometry of the workpiece is converted into a Z-buffer representation and intersection points with the flute trajectory surface are determined. Based on the intersection points, volumetric information of the generated chip can be extracted for process optimization. Semi-analytical model for the prediction of cutting forces is introduced and simulation results are presented.
Concerning monitoring of end-milling process, this thesis focuses on instability detection. Regardless of the advancements in machining stability prediction and modeling there is always need for the development of an effective chatter detection and monitoring method. Timely chatter detection prevents the damaging of the cutting tool and workpiece, because it allows for immediate intervention in the cutting process. The first step of the proposed method for instability detection is to decompose the vibration signal by using Gabor filter bank. Then, for the detection of the transition in cutting dynamics at the onset of chatter, the Teager’s nonlinear energy operator is used which can track variations in instantaneous frequency and amplitude. The proposed method is tested on data obtained from slot end-milling of an inclined surface for different levels of spindle speed.
For the evaluation of end-milling process, computer vision techniques in combination with microscope camera are used. In this thesis surface texture evaluation is performed by detecting the generated cusp lines and tool marks on the machined surface. The tool marks distribution is analysed in order to determine whether machining is performed under optimal cutting conditions. Results show that under optimal cutting conditions, the detected tool marks are normally distributed along the feed direction and the distance between two consecutive tool marks does not vary significantly. Based on the proposed methods, software is implemented that enables the three-dimensional reconstruction, calibration and evaluation of the inspected surface.

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