A New Method for Multi-objective Optimal Design of Milling Parameters by Considering Chatter Vibrations
Published May 13, 2019 by SAE International in United States
Downloadable datasets for this paper availableAnnotation of this paper is available
Event: Automotive Technical Papers
The desired milling process with high material removal rate (MRR) and low surface roughness of the product can be achieved only if machining chatter is absent. Incorporating chatter into the optimal selection of the machining parameters leads to a complex problem. Therefore, the approach of selecting conservative intervals for the machining parameters is usually employed instead. In this paper, a practical approach is proposed to specify the optimal machining parameters (depth of cut and spindle speed) in order to maximize MRR and minimize forced vibrations by considering machining chatter. Firstly, the worst-case scenario-based optimization problem in terms of the surface quality is solved to find the critical time at which maximal amplitude vibrations occur. Then, the time dependency of the problem is eliminated. Secondly, the multi-objective optimization is conducted to achieve the Pareto Optimal Front (POF). The Stability Lobe Diagram (SLD) is obtained independently through well-established analytical methods. Optimal machining parameters on the obtained POF are mapped into the SLD to represent optimal results for the cases at which machining chatter is absent. Finally, these optimal results are sorted by the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) decision-making method and displayed on the combined POF-SLD diagram which can be used by the machining operator for determination of the process parameters. A case study is considered, illustrating the efficiency of the proposed method.
CitationJafarzadeh, E., Khodaygan, S., and Sohani, A., "A New Method for Multi-objective Optimal Design of Milling Parameters by Considering Chatter Vibrations," SAE Technical Paper 2019-01-5043, 2019, https://doi.org/10.4271/2019-01-5043.
Data Sets - Support Documents
|[Unnamed Dataset 1]|
- Bonilla Hernández, A.E., Beno, T., Repo, J., and Wretland, A. , “Integrated Optimization Model for Cutting Data Selection Based on Maximal MRR and Tool Utilization in Continuous Machining Operations,” CIRP Journal of Manufacturing Science and Technology 13:46-50, 2016.
- Sangwan, K.S., Saxena, S., and Kant, G. , “Optimization of Machining Parameters to Minimize Surface Roughness Using Integrated ANN-GA Approach,” Procedia CIRP 29:305-310, 2015.
- Wang, B., Liu, Z., Song, Q., Wan, Y. et al. , “Proper Selection of Cutting Parameters and Cutting Tool Angle to Lower the Specific Cutting Energy during High Speed Machining of 7050-T7451 Aluminum Alloy,” Journal of Cleaner Production.
- Jiang, Z., Zhou, F., Zhang, H., Wang, Y. et al. , “Optimization of Machining Parameters Considering Minimum Cutting Fluid Consumption,” Journal of Cleaner Production 108(Part A):183-191, 12/1/2015.
- Rao, R., Pawar, P., and Shankar, R. , “Multi-Objective Optimization of Electrochemical Machining Process Parameters Using a Particle Swarm Optimization Algorithm,” Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 222(8):949-958, 2008.
- Kondayya, D. and Krishna, A.G. , “An Integrated Evolutionary Approach for Modelling and Optimization of Wire Electrical Discharge Machining,” Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 225(4):549-567, 2011.
- Jafarzadeh, E., Movahhedy, M.R., Khodaygan, S., and Ghorbani, M. , “Prediction of Machining Chatter in Milling Based on Dynamic FEM Simulations of Chip Formation,” Advances in Manufacturing 6(3):334-344, 2018.
- Jafarzadeh, E. and Movahhedy, M.R. , “Numerical Simulation of Interaction of Mode-Coupling and Regenerative Chatter in Machining,” Journal of Manufacturing Processes 27:252-260, 2017.
- Zhang, X. and Ding, H. , “Note on a Novel Method for Machining Parameters Optimization in a Chatter-Free Milling Process,” International Journal of Machine Tools and Manufacture 72:11-15, 9/2013.
- Graham, E., Mehrpouya, M., and Park, S. , “Robust Prediction of Chatter Stability in Milling Based on the Analytical Chatter Stability,” Journal of Manufacturing Processes 15(4):508-517, 2013.
- Ozoegwu, C.G., Ofochebe, S.M., and Omenyi, S.N. , “A Method of Improving Chatter-Free Conditions with Combined-Mode Milling,” Journal of Manufacturing Processes 21:1-13, 2016.
- Budak, E. and Tekeli, A. , “Maximizing Chatter Free Material Removal Rate in Milling through Optimal Selection of Axial and Radial Depth of Cut Pairs,” CIRP Annals-Manufacturing Technology 54(1):353-356, 2005.
- Xiong, Y., Wu, J., Deng, C., and Wang, Y. , “Machining Process Parameters Optimization for Heavy-Duty CNC Machine Tools in Sustainable Manufacturing,” The International Journal of Advanced Manufacturing Technology 87(5-8):1237-1246, 2016.
- Benardos, P. and Vosniakos, G.-C. , “Predicting Surface Roughness in Machining: A Review,” International Journal of Machine Tools and Manufacture 43(8):833-844, 2003.
- Lin, S. and Chang, M. , “A Study on the Effects of Vibrations on the Surface Finish Using a Surface Topography Simulation Model for Turning,” International Journal of Machine Tools and Manufacture 38(7):763-782, 1998.
- Altintas, Y. , Manufacturing Automation: Metal Cutting Mechanics, Machine Tool Vibrations, and CNC Design (Cambridge University Press, 2000).
- Tlusty, J. , Manufacturing Processes and Equipment (Prentice Hall, 2000).
- Altintas, Y. , Manufacturing Automation: Metal Cutting Mechanics, Machine Tool Vibrations, and CNC Design (Cambridge University Press, 2012).
- Insperger, T. and Stépán, G. , “Updated Semi-Discretization Method for Periodic Delay-Differential Equations with Discrete Delay,” International Journal for Numerical Methods in Engineering 61(1):117-141, 2004.
- Sohani, A., Sayyaadi, H., and Hoseinpoori, S. , “Modeling and Multi-Objective Optimization of an M-Cycle Cross-Flow Indirect Evaporative Cooler Using the GMDH Type Neural Network,” International Journal of Refrigeration 69:186-204, 2016/09/01/.
- Sohani, A. and Sayyaadi, H. , “Design and Retrofit Optimization of the Cellulose Evaporative Cooling Pad Systems at Diverse Climatic Conditions,” Applied Thermal Engineering 123:1396-1418, 2017/08/01/.
- Sohani, A., Sayyaadi, H., and Mohammadhosseini, N. , “Comparative Study of the Conventional Types of Heat and Mass Exchangers to Achieve the Best Design of Dew Point Evaporative Coolers at Diverse Climatic Conditions,” Energy Conversion and Management 158:327-345, 2018/02/15/.
- Boran, F.E., Genç, S., Kurt, M., and Akay, D. , “A Multi-Criteria Intuitionistic Fuzzy Group Decision Making for Supplier Selection with TOPSIS Method,” Expert Systems with Applications 36(8):11363-11368, 2009.
- Sohani, A., Farasati, Y., and Sayyaadi, H. , “A Systematic Approach to Find the Best Road Map for Enhancement of a Power Plant with Dew Point Inlet Air Pre-Cooling of the Air Compressor,” Energy Conversion and Management 150:463-484, /10/15/2017.
- Khodaygan, S. , “An Interactive Method for Computer-Aided Optimal Process Tolerance Design Based on Automated Decision Making,” International Journal on Interactive Design and Manufacturing (IJIDeM) 1-16, 2018.
- Khodaygan, S. and Golmohammadi, A. , “Multi-Criteria Optimization of the Part Build Orientation (PBO) through a Combined Meta-Modeling/NSGAII/TOPSIS Method for Additive Manufacturing Processes,” International Journal on Interactive Design and Manufacturing (IJIDeM) 1-15, 2017.