Application of isight for Optimal Tip Design of Complex Tool Holder Spindle

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1 Application of isight for Optimal Tip Design of Complex Tool Holder Spindle WMSCI 2010 Author: Koo Hong Kwon Won Jee Chung Ki Beom Park School of Mechatronics, Changwon National University Tel: , Fax: Address: School of Mechatronics, Changwon National University Changwon, , South Korea ABSTRACT This paper presents the application of isight for optimal tip design of complex tool holder spindle. The complex tool holder is used for holding a (milling/drilling) tool of a machine tool. The engineering problem of complex tool holder results from the twisting of spindle of tool holder. This leads to the vibration of tool holder which makes the tool holder malfunction. This engineering problem can be solved by proposing the optimized mathematical approximation (or modeling) of finite element modeling for the complex tool holder using OLH and RBF neural network. The finite element modeling will be obtained by using ANSYS 11.0 Classic. The OLH gives us regular sampling, not random sampling, between lower and upper bounds. According to the DOE, we will perform the simulation of finite element modeling whose outputs are the minimum stress, by incorporating OLH (specifically a module of isight FD-3.1) into ANSYS 11.0 Classic. Finally the optimized mathematical approximation can be resulted in by using the RBF (another module of isight FD-3.1) of neural network structure. The effectiveness of our proposed approximation technique will be verified by making a prototype of complex tool holder based on the optimized dimensions of both length and thickness for tool holder spindle tip. Keywords: Optimized Approximation (Mathematical Modeling), Finite Element Modeling, Complex Tool Holder Spindle, Optimal Latin Hypercube (OLH), Radial Basis Function (RBF) Neural Network. 1. Introduction In present industrial society, different kinds of products with good quality should come up with diverse desire of consumers. Consequently the life cycle of a product is dramatically shortened, which in turn makes the time of developing new models reduced. Corresponding to the fast change of models, quick and precise machining of metallic patterns is needed. As one of alternatives for this purpose, high-speed machining is being highlighted. In high-speed machining, the engineering problem of vibration is a major matter of concern because it makes the quality of machined products defective. To cope with the problem of vibration, a tool holder (which is connected to a machine tool spindle by an adapter) is usually used for holding a tool so that it can reduce vibration even in high-speed machining. In this paper, we have a concern in a complex tool holder which can be used for milling, drilling, and taping jobs. [1] As one of engineering problems for the complex tool holder, large stress and deformation can often occur at the tip of tool holder spindle (against the confusion of machine tool spindle). This tip will be termed as tool holder spindle tip to which a tool is connected. Large stress and deformation around tool holder spindle tip will make the tool holder spindle tip break down or make the tool holder spindle twist. Consequently these phenomena will make the tool holder malfunction

For this purpose, we present the optimized approximation of finite element modeling for a complex tool holder spindle using both DOE (Design of Experiment) with Optimal Latin Hypercube (OLH) method

2 because the tool of a machine tool can machine no-good products. In order to prevent these phenomena, this paper aims at designing the optimal configuration (especially, length and thickness) of tool holder spindle tip. For this purpose, we present the optimized approximation of finite element modeling for a complex tool holder spindle using both DOE (Design of Experiment) with Optimal Latin Hypercube (OLH) method (specifically a module of isight FD-3.1) and approximation modeling method with Radial Basis Function (RBF) (another module of isight FD-3.1) neural network structure. [2] The finite element modeling will be obtained by using ANSYS 11.0 Classic. The OLH gives us regular sampling, not random sampling, between lower and upper bounds. According to the DOE, we will perform the simulation of finite element modeling whose outputs are the minimum stress, by incorporating OLH (specifically a module of isight FD-3.1) into ANSYS 11.0 Classic. Finally the optimized mathematical approximation can be resulted in by using the RBF (another module of isight FD-3.1) of neural network structure. The effectiveness of our proposed optimal design technique will be shown by being compared with the empirical design of an expert in the sense of twisting deformation. 2. Simulation of Finite Element Modeling using DOE with OLH Figure 1 shows the initial drawing (designed by the experts of EWSKorea, Ltd.) of a complex tool holder where the tool holder spindle, adapter and tool holder spindle tip are designated by captions. The prototype machined by using the initial design has resulted in the engineering problem that the tool holder spindle tip has been twisted or even broken down. The experts of EWSKorea have given us the suggestion that large stress and deformation around tool holder spindle tip can make the tool holder spindle tip break down or make the tool holder spindle twist. Based on this suggestion, we will focus on the optimal configuration (especially, length and thickness) of tool holder spindle tip in order to result in the minimum stress at the tool holder spindle tip. Instead of a full modeling of complex tool holder, only the finite element modeling of tool holder spindle tip has been made because the tool holder spindle is a key component which can be apt to be affected by stress and deformation. [3] As shown in Fig. 2, the finite element modeling of tool holder spindle tip for the complex tool holder tip has been obtained by using ANSYS 11.0 Classic. Thus this finite element modeling will be used for finding the optimal configuration of tool holder spindle tip. Notice that the element types of Solid 10 node 92 ANSYS 11.0 Classic are used for the finite element modeling of tool holder in Fig. 2.[4] The material properties of tool holder spindle (SCM415), i.e., Young s Modulus (E), Density, and Poisson s ratio, are shown in Table Finite Element Modeling of Tool Holder Spindle Tip Fig. 2 Finite Element Modeling of Tool Holder Spindle Tip Table 1 Material properties of Spindle Fig. 1 Drawing of Complex Tool Holder Property (unit) E Density Poisson s (MPa) (g/ mm 3 ) ratio

[5] Table 2 Base Line, Lower Boundary and Upper Boundary of 2 Design Variables (unit : mm) Length of Tool holder Spindle Tip Thickness of Tool Holder Spindle Tip Initial Value Lower Bound Upper Bound

3 2.2 Simulation using DOE with OLH Now our concern is on how to generate the candidate values of length and thickness of tool holder spindle tip. Table 2 shows base lines (or initial design values), lower bounds and upper bounds for the 2 design variables. [5] Table 2 Base Line, Lower Boundary and Upper Boundary of 2 Design Variables (unit : mm) Length of Tool holder Spindle Tip Thickness of Tool Holder Spindle Tip Initial Value Lower Bound Upper Bound Range of Movement initial simulation for the base line values aims at resulting in the LOG file of ANSYS 11.0 Classic which can be imported into isight FD-3.1. In isight FD-3.1, 2 design variables are automatically input to the LOG file by using the OLH module. The OLH needs the lower bound, upper bound and increment for each design variable. The outputs of simulation using LOG file are the stress of tool holder spindle tip. As shown in Table 3, we have obtained 100 sets of inputs (design variables) according to the DOE using OLH. Accordingly 100 outputs (i.e., stresses) are automatically saved in the isight FD-3.1. These input and output data now can be used for resulting in an optimized approximation model by using the RBF module of isight FD-3.1. [7] Figure 5 shows one of output data resulted from the ANSYS 11.0 simulation, i.e., MPa. In this paper, isight FD-3.1 will be used for automatically generating the level values of design variables, by using Optimal Latin Hypercube (OLH) method. This means that OLH is incorporated into ANSYS 11.0 Classic. The output at each simulation is the stress at the tool holder spindle tip. As shown in Fig. 3, even though OLH starts with a random Latin Hypercube matrix, it can optimize the order of levels in each column to obtain the combinations of factor levels (design points) spread as evenly as possible though design space. [6] Fig. 4 Procedure of Simulation using ANSYS 10.0 Classic and isight 3.1 Fig. 3 Optimal Latin Hypercube Method Figure 4 illustrates the procedure regarding how ANSYS 10.0 Classic can be incorporated into isight FD-3.1. First, the finite element modeling of tool holder spindle tip is simulated for the base line values of 2 design variables, by using ANSYS 11.0 Classic. The Fig. 5 Stress Analysis Result of Tool Holder Spindle Tip using ANSYS 11.0 Classic

spindle tip through 1,000 simulations. Figures 7 and 8 show the optimized 2- dimensional and 3-dimensional approximation models, respectively.

000 sets of outputs (stress and deformation) are saved in isight 3.1.

4 Table 3 isight 3.1 simulation The optimized approximation model resulted from the RBF module will be used for finding the optimal values of 2 design variables which can result in the minimum stress at the tool holder spindle tip through 1,000 simulations. Figures 7 and 8 show the optimized 2- dimensional and 3-dimensional approximation models, respectively. Using this model, the stress and at the tool holder spindle tip can be calculated. Using this model, the stress and at the tool holder spindle tip can be calculated. As a result, Table 4 shows 1,000 sets of inputs (design variables) obtained by using RBF module. The 1,000 sets of outputs (stress and deformation) are saved in isight 3.1. Among them, we can obtain the optimal design variables which result in the minimum stress at the tool holder spindle tip, as indicated by a red line (specifically length = 6.7mm, thickness = 8.9mm). These optimal design variables are assigned to the finite element modeling of ANSYS 10.0 Classic. As shown in Table 5, the stress of initial finite element modeling has been reduced by about 20 % as compared with the optimized approximation model of RBF. It can be concluded that the optimized approximation model of RBF is meaningful in a practical sense. 3. Optimized Approximation using RBF The data resulted from the OLH module can be imported into the RBF module of isight FD-3.1 so that an optimized approximation model between 2 input variables (i.e., tool holder spindle tip length, and tool holder spindle tip thickness) and 1 output variables (stress at tool holder spindle tip) can be established. It is well known that RBF neural network is one of methods of curve fitting in multi-dimensional space. This means that training through RBF searches for one space from multidimensional spaces, which can be agreed best with data sets to be trained. Figure 6 shows the structure of RBF neural network. Fig. 7 2D Optimized approximation model Fig. 6 RBF neural network structure. Fig. 8 3D Optimized approximation model

Table 4 Tool holder spindle tip stress Table 6 Comparison of Initial Prototype with Optimized Prototype Twisting Deformation Initial Optimized Reduction Prototype Prototype Rate 0.02 0.008 60% Fig.

The prototype of complex tool holder using the optimal configuration of tool holder spindle tip is shown in Fig. 9.

5 Table 4 Tool holder spindle tip stress Table 6 Comparison of Initial Prototype with Optimized Prototype Twisting Deformation Initial Optimized Reduction Prototype Prototype Rate % Fig. 9 Prototype of Complex Tool Holder Table 5 Comparison of Initial Finite element modeling with Optimized Approximation Model of RBF Initial Finite element Optimized approximation Reduction Rate modeling model Stress % 4. Prototype The effectiveness of our proposed optimal design technique is shown by being compared with the empirical design of an expert in the sense of twisting deformation. The prototype of complex tool holder using the optimal configuration of tool holder spindle tip is shown in Fig. 9. The twisting deformation has been measured by using a test bar with length of 50mm as shown in Fig. 10. Table 6 shows that the twisting deformation of the optimized prototype (length = 6.7mm, thickness = 8.9mm) has been reduced by 60% when compared with the initial prototype (length = 10.5mm, thickness = 8mm). Fig. 10 Measurement of twisting deformation 5. Conclusion As mentioned before, the engineering problem of complex tool holder has resulted from the twisting of spindle of tool holder. This leads to the vibration of tool holder which makes the tool holder malfunction. This

6 engineering problem can be solved by proposing the optimized mathematical approximation (or modeling) of finite element modeling for the complex tool holder using the application of isight (specifically both DOE with OLH and RBF neural network). When our proposed approximation technique has been compared with the initial empirical design of prototype, the optimized approximation for a complex tool holder spindle using both DOE with OLH method and RBF neural network structure is more efficient in that it can use ANSYS Log files and an approximation model of RBF, as well as reducing the twisting deformation drastically. [5] Cho, Y.D. Chung, W.J. Lee, C.M. Hwang, Y.K. Kim, J.H. Park, K.B. Yoon, S.H. Simulation Techniques for Visualizing Phenomena in a Body of Rotation MSV07, 2007 [6] Jung, D.W. Chung, W.J. Kim, H.C. Bang, Y.M. Yoon, Y.M. Six Sigma Robust Design of Fork Park for LCD Transfer System WMSCI, [7] isight Training Book. Engineous Korea, Acknowledgement This work was supported by grant No. RTI from the Regional Technology Innovation Program of the Ministry of Knowledge Economy (MKE). The authors of this paper were partly supported by the Second Stage of Brain Korea21 Projects. Special thanks give to Vice President Jung Han PARK and Associate Engineer Sang Woo KYE of EWSKorea Inc., for helping us in both making experiments and prototyping the complex tool holder References [1] Lim, J.S., Nam, K.Y., Chung, W.J., and Lee, C.M., 2006, Development of 24,000rpm high- speed spindle by statistical Method, KSMTE, Spring Conference, pp. 285~290. [2] Park, K.B. Chung, W.J. Lee, C.M. Model Updating of High-Speed Spindle Transactions of the Korean Society of Machine Tool Engineers, vol.17, No 2, pp.7-12, [3] Park, K.B. Chung, W.J. Lee, C.M. Cho, Y.D. Kim, J.H. Finite Element Modeling and Simulation for Shape Design of a Super High-Speed Rotating-Shaft Using Design of Experiment MSV07, 2007 [4] Tae Sung Software &Engineering, Inc. ANSYS Classic Training Manual 2008

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