Tool condition monitoring for ball nose milling a model based approach

TOOL CONDITION MONITORING FOR BALL NOSE MILLING – A MODEL BASED APPROACH KOMMISETTI V R S MANYAM NATIONAL UNIVERSITY OF SINGAPORE 2009 TOOL CONDITION MONITORING FOR BALL NOSE MILLING – A MODEL BASED APPROACH KOMMISETTI V R S MANYAM (M.Tech, Indian Institute of Technology Kharagpur) A THESIS SUBMITTED FOR THE DEGREE OF DOCTOR OF PHILOSOPHY DEPARTMENT OF MECHANICAL ENGINEERING NATIONAL UNIVERSITY OF SINGAPORE 2009 i Acknowledgements I want to express my most sincere gratitude to my supervisors, Professor Wong Yoke San and Associate Professor Hong Geok Soon. They provided me wise and valuable supervision, constructive feedback and enthusiastic encouragement through my project. I also would like to thank National University of Singapore for offering me research scholarship and research facilities. The abundant professional books and technical Journal collection at NUS library are also to my benefit. Special thanks to Mr. C.H. Tan, Mr. S. C. Lim, Mr. C. L. Wong and all other technicians at Advanced Manufacturing Lab of NUS for their technical assistance during my experiments. Thanks to the technical staff at Control and Mechatronics Lab for their support and facilities provided during my period of stay at NUS. I have also benefited from discussion with many of seniors and colleagues. In particular Dr. Wang Zhigang, Dr Zhu Kunpeng, Mr. Woon Keng Soon, Mr. Indraneel Biswas, Mr. Chandra Nath, Ms. Wu Yue, and Mr. Yu Deping Ms. Wang Qing, Ms. Le Ngoc Thuy, Mr. Nguyen Minh Trung and others in the Control and Mechatronics Lab. Finally, I would like to express my deepest thanks to my family for their love, support and understanding. National University of Singapore NUS ii Table of Contents Acknowledgements……………………………………………………………………i Table of Contents …………………………………………………………………….ii Summary …………………………………………………………………………… .v List of Tables ……………………………………………………………………… .vii List of Figures ………………………………………………………………………viii Nomenclature ……………………………………………………………………….xiii Chapter .1 1.1 Problem statement 1.2 Motivation 1.3 Objectives and scope of work 1.4 Organization of the thesis Chapter .7 2.1 Tool Condition Monitoring (TCM) for Ball nose milling .7 2.1.1 TCM .7 2.1.2 Sensors Used in TCM 11 2.1.3 TCM Methodologies 14 2.1.4 TCM for Ball Nose Milling .16 2.2 Cutting Force Model 17 2.2.1 Geometric modeling of ball nose milling 18 2.2.2 Mechanistic cutting force model 19 2.3 Tool Wear Model .21 2.4 Framework for TCM of Ball Nose Milling 23 2.4.1 Geometric Modeling 23 National University of Singapore NUS iii 2.4.2 Mechanistic Force Model 24 2.4.3 Tool Wear profile Estimation 24 Chapter .26 3.1 Problem Statement .26 3.2 Geometry of Ball Nose milling cutter 27 3.3 Geometric Model for Ball nose milling on inclined surface 29 3.3.1 Evaluation of Depth of Cut at give height ‘z’ 30 3.3.2 Analysis of the tooth trajectory 35 3.3.3 True Undeformed chip thickness .35 3.4 Analysis of true undeformed chip thickness 36 3.5 Analysis based on geometric model for different cutter path directions .41 3.6 Discussion and conclusions .47 Chapter .50 4.1 Problem statement 50 4.2 Cutting force model formulation .51 4.3 Cutting Force Estimation .55 Chapter .58 5.1 Experimental Set Up 58 5.2 Results for the Estimation of Cutting Force on 450 inclined workpiece in four different cutter path directions. 60 5.3 Results for Estimation of Cutting Force on 30o and 600 inclined Workpiece 67 5.4 Experiments for Milling of Hemispherical Workpiece .69 5.5 Results of cutting force Estimation for hemispherical surface workpiece 73 5.6 Conclusion .74 National University of Singapore NUS iv Chapter .76 6.1 Background 76 6.2 Feature Extraction 76 6.2.1 Experimental Setup 77 6.2.2 Geometric Features 78 6.2.3 Residual Force Feature 81 6.3 Model for Tool Wear Estimation .82 6.3.1 Model based on the geometric features .83 6.3.2 Model based on the geometric features and residual force feature 85 6.3.3 Model based on the geometric features with estimated tool wear as feed back 87 6.4 Results for Tool Wear Profile Estimation 89 6.5 Discussions 94 Chapter .97 7.1 Conclusions 97 7.2 Recommendations for future work 100 Reference 103 National University of Singapore NUS v Summary Tool condition monitoring (TCM) for ball nose milling can significantly improve machining efficiency, minimize inaccuracy, minimize machine down time and maximize tool life utilization. However, Tool condition monitoring in ball nose milling poses new challenges comparing with the conventional machining. In this thesis, a model-based approach to estimate the tool wear profile along the cutting edge for ball nose milling is proposed. For this purpose, a geometric model and a cutting force model are developed to model the ball nose milling process and used to estimate the tool wear profile. Firstly, a geometric model for the ball nose milling was developed with consideration of cutter path directions, helix angle of the milling cutter and trochoid true tool path. It was used to evaluate various geometric features such as the chip load along the cutting edge, the chip load distribution about tool rotation axis and the friction length. Using these geometric features, the influence of cuter path directions for various inclination of workpiece on cutting tool performance was discussed. Secondly, a mechanistic cutting force model was established using the chip load about the cutter rotation axis and the cutting coefficients. The chip load was evaluated from geometric model, while the cutting coefficients were identified using the chip load and the experimentally measured cutting force data when machining on an inclined plane. Experiments with various cutter path directions on inclined plane workpieces and hemispherical surface workpiece were conducted to validate the developed force model. The estimated cutting force for fresh tool stage was compared with the experimentally measured cutting force to obtain a residual force feature and used in the tool wear estimation model. National University of Singapore NUS vi Finally, tool wear estimation models to estimate the tool wear profile along the cutting edge were developed. The geometric features and the residual force feature were evaluated for each cutting edge element in contact with the workpiece based on the given cutter path direction, cutting conditions and the workpiece inclination. These evaluated features and measured tool wear values were used to obtain parameters in the tool wear estimation models for the given workpiece and tool combination. Experiments were conducted on hemispherical surface workpiece with different sequence of cutter path directions to verify the tool wear models. The study has demonstrated that it is feasible to use model-based tool condition monitoring to estimate tool wear profile along the cutting edge accurately and effectively for sculptured surface machining. Such profile estimation along the cutting edge may be useful in utilization of the tool life more effectively, which can minimize the tool cost, reduce the machine downtime, and increase the productivity. National University of Singapore NUS vii List of Tables Table 2.1 Cutting force features used in literature and the methods to make decision based on them 16 Table 5.1 Experimental details for Horizontal Downward cutter path direction .60 Table 5.2 Experimental details for Horizontal Upward cutter path direction 60 Table 5.3 Experimental details for Vertical Downward cutter path direction .60 Table 5.4 Experimental details for Vertical Upward cutter path direction 61 Table 6.1 Experimental details for hemispherical surface workpiece machining .78 Table 6.2 RMS errors for proposed tool wear model in estimating tool wear profile.89 National University of Singapore NUS viii List of Figure Figure 2.1 Tool wear definition .8 Figure 2.2 Tool geometry and wear definition [18] .8 Figure 2.3 Three stages of tool flank wear Figure 2.4 Chipping Illustration [18] .10 Figure 3.1 Different cutter path directions for machining on inclined surfaces 27 Figure 3.2 Geometry of the ball nose milling 28 Figure 3.3 Cutting edge length divided into finite oblique cutting edge elements 30 Figure 3.4 Machining on inclined plane with inclination angle of ‘θ’ with horizontal downward cutter path direction .31 Figure 3.5 Diagram showing the tool workpiece contact area (shaded) on inclined plain with radial depth of cut ‘D’ and pitch feed ‘p’. 32 Figure 3.6 The variation of depth of cut along the cutting edge for 45o plane with 0.2 mm radial depth and 0.35mm pitch feed .34 Figure 3.7 Variation of depth of cut along the axis for different pitch feed 34 Figure 3.8 Geometry of chip thickness of ball nose milling process with Rz as cutter radius and dzl and radial immersion at height Z from ball centre 36 Figure 3.9 Geometry of chip thickness 38 Figure 3.10 3D chip variation along the ball axis and cutter rotation (fz :0.1mm/tooth, D=0.3mm, p=0.35, HD cutter path direction) 39 Figure 3.11 Chip area about the cutter rotation (fz=0.1mm/tooth; D=0.3 mm; p=0.35mm; HD cutter path direction) 40 Figure 3.12 Comparison of chip load about the cutter rotation axis for traditional and updated model (fz=0.1mm/tooth; D=0.5 mm, p=0.35 mm; HD cutter path direction) 40 Figure 3.13 Chip load for VD cutter path direction on inclined surface .42 National University of Singapore NUS Chapter Conclusion and Recommendations for Future Work 102 7. 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Peter peregrinus limited, : p. 262-293. [112] Sharman, A., R.C. Dewes, and D.K. Aspinwall, Tool life when high speed ball nose end milling Inconel 718. Journal of Materials Processing Technology, 2001. 118(1-3): p. 29-35. [113] Naserian, R.S., M.H. Sadeghi, and H. Haghighat, Static rigid force model for 3-axis ball-end milling of sculptured surfaces. International Journal of Machine Tools & Manufacture, 2007. 47(5): p. 785-92. National University of Singapore NUS Reference 117 Publications: 1. Dong Jianfei, K V R Subrahmanyam, Wong Yoke San, Hong Geok Soon, A R Mohanty “Bayesian neural Networks applied to Tool wear estimation” Published in International Journal of Advanced Manufacturing Technology.Vol 30, pp: 797-807, 2006. 2. Mohanty, A. R. and K.V.R. Subrahmanyam, "Sensor fusion technique for tool condition monitoring during milling process," The Third International symposium on Instrumentation Science and Technology, Xian City, China. 3. K V R Subrahmanyam, Wong Yoke San, Hong Geok Soon, Huang Sheng, “Cutting Force Prediction for Ball Nose Milling on Inclined Surface”. International Journal of Advanced Manufacturing Technology (Online) 4. K V R Subrahmanyam, Hong Geok Soon, Wong Yoke San“Geometric Modeling of Ball Nose Milling for Different Cutter Path Directions and Cutting Force Predictions”. Submitted to Wear”, In review. 5. K V R Subrahmanyam, Wong Yoke San, Hong Geok Soon, Wu Yue “Tool Wear Profile Estimation for Ball Nose Milling- A Model Based Approach”, In progress. 6. K V R Subrahmanyam, Huang Sheng, Wong Yoke San, Hong Geok Soon Cutting Force Prediction for Ball Nose Milling, PDMS 2007 conference held in china. National University of Singapore NUS [...]... is lack of understanding in the tool wear process in ball nose milling applications [5] From decades of TCM research literature, three basic approaches are observed, namely model- based approaches, artificial intelligence (AI) techniques (various neural networks for classification and regression models), and statistical approaches These approaches generally assumed that the tool wear is uniform and... cutting tool states via statistical tools such as cluster analysis, multivariate statistical analysis and statistical classifications [17] These approaches group the sensor signal characteristics into different fault stages based on the extracted features from the measured signals Recently, Zhu [17] used continuous Hidden Markov Model (HMM) for adapting stochastic modeling of tool wear process in micro milling. .. Singapore NUS Chapter 2 Literature Review 13 measures the total elastic strain energy released at various sources such as, friction on the rake face and flank face, plastic deformation at shear zone, crack formation and propagation, impact of chip at workpiece and chip breakage AE signals are mostly used to detect tool breakage in literature [35] However, AE sensor application in TCM for milling process... estimate the cutting force of fresh tool for ball nose milling 2 A tool wear profile estimation for ball nose milling along the cutting edge, which can adapt to various cutting conditions and sculptured surfaces To achieve the specific objectives, the scope of work includes: 1 Generation of accurate geometric model for ball nose milling with tool parameters such as helix angle, pitch feed and true tool. .. ball nose milling applications Table 2.1 Cutting force features used in literature and the methods to make decision based on them Conditions Tool Breakage Detection Tool Wear Detection Tool Wear Estimation Features Residual error Components in tool breakage zone Sum of the squares of residual errors Peak rate Average force and variable force Shape characteristic vectors from wavelet coefficients Wavelet... such as shear force and edge force In this work, edge force coefficients is claimed to have strong correlation with tool wear progress and is used as an monitoring indicator So far, TCM methodologies proposed in literature are concentrated on average tool wear, maximum tool wear and tool breakage detection However, in ball nose milling application, because of change in position of tool- workpiece contact,... there is a need to model chip area evaluation for sculpture surface with good accuracy Essentially, modeling on the inclined plane is helpful to understand the chip load pattern for ball nose milling [69] For ball nose milling, there are four different cutter path directions such as Vertical Downward (VD), Vertical Upward (VU), Horizontal Downward (HD), and Horizontal Upward (HU) associated with machining... inclinations and hemispherical surface machining Chapter 6 describes the models to estimate the tool wear Different models for tool wear profile estimation for diagnostics and prognostics are proposed and compared Tool wear models with geometric features and residual force features are proposed Identification of model parameters and implementation of the model are discussed Experimental results for verification... nose milling [4] Statistical approaches used for tool condition monitoring are used to identify the states of the cutting tool Methods such as Automatic Relevance Determination (ARD) [53], Linear Discriminate Analysis (LDA) [17], Principle Component National University of Singapore NUS Chapter 2 Literature Review 15 Analysis (PCA) [54], are used to indentify relevant features and used in statistical... overhang and tool wear states were identified Rixin Zhu et al [5] reported a model based tool breakage detection method for ball nose milling A monitoring index is proposed from the generated cutting force model and threshold value is defined Comparing the threshold hold value with the experimental data, tool breakage has been indentified Recently, Min Xu et.al [68] developed a cutting force model . namely model- based approaches, artificial intelligence (AI) techniques (various neural networks for classification and regression models), and statistical approaches. These approaches generally assumed. thesis, a model- based approach to estimate the tool wear profile along the cutting edge for ball nose milling is proposed. For this purpose, a geometric model and a cutting force model are developed. dF a elemental cutting force in tangential, radial and axial direction dF x , dF y , dF z elemental cutting force in Cartesian co-ordinates K te , K re , K ae tangential, radial and axial