[7] Stephen A. Batzer, Ghatu Subhash, Walter Olson, John. W. Sutherland: Large Strain Constitutive. Model Development for Application to Orthogonal ...
7th International Scientific Conference on Production Engineering DEVELOPMENT AND MODERNIZATION OF PRODUCTION
NUMERICAL MODELING OF CHIP GENERATION PROCESS Sabahudin Ekinovic, Edin Begovic University of Zenica, Faculty of Mechanical Engineering, Fakultetska 1, 72000 Zenica, B&H
Keywords: Chip generation, Finite Element Method, AdvantEdge ABSTRACT: Numerical modelling, especially, Final Element Method getting more and more space and relevancy in simulation of machining processes today. Any serious investigation and research in this area is consists of experiment followed by numerical simulation. Although some differences in obtained results exists - comparing experiment on real objects and numerical modelling, and even if the experimental techniques are still more relevant one, numerical simulation shows high level of agreement with real results. This paper give short insight into part of a research authors conducted on 3 different steel materials in 2 different states, normalised and annealed. Focus of the research was on chip generation process in high speed machining. Plan experiment has been conducted, chips in every experimental run collected, metallographically prepared and compared with virtual chip obtained by numerical simulation in AdvantEdge commercial FEM software.
1. INTRODUCTION Numerical modelling - FEM in particularly, plays important role in modelling machining processes. Starting from 70s of the last century up to these days, many researchers have been involved in numerical modelling of machining processes. Yet the complexity of these processes that include different scientific area like thermodynamics, mathematics, mechanics, material science, tribology, deformation etc. has been the main obstacle in obtaining more accurate and applicable results. First numerical simulation of chip generation process was performed by Zienkewicz and Kakino, 1971 [1]. To avoid problems of modelling high deformation rates, they simplified process and load in advance modelled - pre-formed chip, then analysed small elasto-plastic strain caused by cutting tool movement. Anyway this work, today, is an important moment in history of modelling chip generation processes. Its main disadvantage – no ability to predict chip shape, has been solved in 1976 with ICM (Iterative Convergence Model) developed by Shirikashi i Usui. Although, these researchers have brought modelling of chip generation process into next level, it is important to highlight that first investigations, from 70s-90s, did not take too much care about accuracy of results but were much more focused on modelling process itself. According to the results of a survey covering the dissemination of modelling techniques for machining operations [2], about 18% of this specific research activity is engaged in numerical modelling. These statistics have distinguished three techniques which can be applied to solve the heat transfer problem in metal cutting, namely: the finite element (FEM), the finite difference (FDM) and the boundary element (BEM) methods. In recent years, the finite element method has particularly Edited by: I.Karabegovic, V. Dolecek, M. Jurkovic University of Bihac, Faculty of Technical Engineering
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S.Ekinovic, E.Begovic – Numerical modelling of chip generation process become the main tool for simulating metal cutting processes. Consequently, numerical simulation that follows up experimental research becomes an important part of machining process investigations and standard investigation methodology [3-9]. In order to enable accurate describing of chip generation process, numerical model has to describe and support following [4]: • Extremely high and localised deformation • Crack initiation and chip development • Friction • Complex material behaviour followed up by thermal and viscoplastic effects • Brakeage of material To fulfil these preconditions adequately chosen and appropriate hardware and software solutions are required. Many software solutions has been developed and in use for these processes. Some of them are for example: Abaqus, Deform, Oxcut, KontiSpam, AdvantEdge etc. No matter which of these is used, accuracy of results relies mostly on an accurate description of chip generation - separation process. To describe this process software producers use different approach and technique. Some of those techniques that might be found in literature are: • Predefined separation line (geometrical parameter). • Euler, Lagrange and ALE (arbitrary Lagrange Euler) analaysis • Criterion based on material to cut properties... To simulate process of chip generation most of the software apply Lagrange approach and techniques of adaptive meshing and remeshing. Mesh adaptivity is main precondition for obtaining accurate results and at the same time decrease CPU time. Mesh adaptivity might be: • H-adaptivity – change size and number of the elements • P- adaptivity - change degree of interpolation function. • R-adaptivity, - rearanging existing mesh Other but not less important precondition is formulation of stress strain state – so call, material constitutive models that describe the flow stress of the workpiece material under high strain, strain rate and temperature conditions that proximately exist during the process. Different models might be found in literature like are – Johnson-Cook, Zerilli-Armstrong, Oxley, Maekawa, Marusich...
2. Chip shape analysis in AdvantEdge Chip shape numerical modelling in AdvantEdge software has been performed in order to improve selection of controlled factors of an experiment. The experiment is based on full factorial plan 23 with 3 factors and 11 experimental runs (8+3 repetition in central point). Tested material is X210Cr12. Levels of controlled factors are shown in Table 1. Table 1. – Control factors levels Factors
Factor levels Upper level (+1)
Central point (0)
Lower level (-1)
Cutting speed
A=v, m/min
250
375
500
Feed
B=f, mm/o
0,1
0,3
0,5
Depth of cut
C=d, mm
0,1
0,3
0,5
Level values in table 1. are based on literature data. Goal of the experiment was to define moment when segmentation of chip starts. It is well known that segmentation of chip reveals moment when conventional machining transforms into high speed machining. Intention of the authors was to perform numerical modelling for each experimental run in order to predict possible chip shape before experimental runs and to found if the selected experimental space encircled cutting conditions that will produce segmented chip. That has been done using AdvantEdge commercial software. Results 2
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S.Ekinovic, E.Begovic – Numerical modelling of chip generation process confirmed that selected factor levels were well chosen. After getting results for all numerical simulations – in all experimental points - an example is shown on figure 1., experiment on real model has been conducted. Third Wave AdvantEdge
Plastic Strain 4 3.7 3.428 3.142 2.85 2.571 2.285 2 1.7142 1.428 1.14 0.8571 0.571 0.285714 0
2.6
Y (mm)
2.4
2.2
2
1.8 4.5
5
5.5
6
X (mm)
Figure 1. An example of numerical simulation for one experimental run Chips are collected and metalographicaly prepared for microscopy. Prepared chip samples were observed under optical microscope in order to get photos of 100x magnified chip samples. These photos are compared with results of numerical simulation. Two examples of comparison are given in figures 2 and3 - below. -- PROCESS -Depth of cut = 0,1 mm Length of cut = 3,0 mm Feed = 0,1 mm Cutting speed = 250,0 m/min Initial temperature = 20,0 degC Friction coefficient = Default Cutting mode = General Coolant = OFF
Figure 2. Comparison of chip shapes for experimental run 1
3. CONCLUSION Numerical simulation has brought many advantages to cutting process analysis. Results of these simulations became more and more reliable and can be effectively used in preparing experimental investigation. Benefits are numerous starting from better understanding of chip generation process, up RIM 2009, Cairo, Egypt
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S.Ekinovic, E.Begovic – Numerical modelling of chip generation process -- PROCESS -Depth of cut = 0,1 mm Length of cut = 3,0 mm Feed = 0,5 mm Cutting speed = 500,0 m/min Initial temperature = 20,0 degC Friction coefficient = Default Cutting mode = General Coolant = OFF
Figure 3. Comparison of chip shapes for experimental run 4 to the experiment cost savings and efficiency increasing. Presented investigation is a good example of effective combination of numerical simulations and experimental investigation.
4. REFERENCES [1] Childs T., Maekawa K., Obikawa T., Yamane Y.: Metal Machining, Theory andApplication, Arnold, Great Britain, London, 2000. [2] W. Konig, F. Klocke, M. Rehse: Prospects for the use of process models in metal cutting, VDI Berichte, No. 1399 (1998), 235-249. [3] A.H. Adibi-Sedeh, V. Madhavan, B. Bahr: Effect of Some Modifications to Oxley's Machining Theory and the Applicability of Different Material Models, Proc. 5th CIRP International Workshop on Modeling of Machining Operations, West Lafayette, IN, USA May, 20-21, 2002 [4] Kalhori V.: Modelling and Simulation of Mechanical Cutting, Doctoral Thesis, Luleå University of Technology, Sweden, 2001 [5] A.H. Adibi-Sedeh, V. Madhavan, B. Bahr: Effect of Some Modifications to Oxley's Machining Theory and the Applicability of Different Material Models, Proc. 5th CIRP International Workshop on Modeling of Machining Operations, West Lafayette, IN, USA– May, 20-21, 2002 [6] Taylan Altan, Partchapol (Jay) Sartkulvanich, Ibrahim Al-Zkeri: Status of FEM Modeling in High Speed Cutting - A Progress Report - CIRP- High Performance CuttingConference, Vancouver, Canada, June 12-13, 2006 [7] Stephen A. Batzer, Ghatu Subhash, Walter Olson, John. W. Sutherland: Large Strain Constitutive Model Development for Application to Orthogonal Machining, Proc. 5th CIRP International Workshop on Modeling of Machining Operations, West Lafayette, IN, USA – 2002 [8] Taylan Altan, Partchapol (Jay) Sartkulvanich, Ibrahim Al-Zkeri, Hyunjoong Cho: Status of FEM Modeling in Cutting and Roller Burnishing - A Progress Report -Workshop on Computer Simulation in Hard Turning and High Performance Machining, Columbus, Ohio, May 25, 2006 [9] Eu-Gene Ng, Tahany I. El-Wardany, Mihaela Dumitrescu, Mohamedd A. Elbestawi: Physics Based Simulation of High Speed Machining, Proc. 5th CIRP International Workshop on Modeling of Machining Operations, West Lafayette, IN, USA, 2002 4
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