Abstract
Bir üretim yöntemli olan frezeleme, üretimin gerçekleştirildiği birçok alanda sıklıkla kullanılan önemli bir metottur. Bu yöntem ile üretilen parçaların kalitesini ve üretim performansını iyileştirmek için yapılan çalışmalarda, frezeleme dinamiğinin anlaşılması önemlidir. Frezeleme operasyonunda kullanılan kesici takımlar birçok farklı geometriye sahiptir ve kesici geometrisi kesme işlemi sırasında oluşan kuvvetleri doğrudan etkiler. Bu yüzden, kesme sırasında oluşan kuvvetler takım tasarımı için temel parametrelerdendir. Bu çalışmada, kesme kuvvetlerini tahmin etmek için, optimize edilen verilerin kullanıldığı mekanistik bir model geliştirilmiştir. Ölçümü yapılan kuvvet sinyalleri, Fourier yaklaştırması yöntemi ile optimize edilmiştir. Kesme katsayılarının kalibrasyonu için, ön frezeleme deneyleriyle yedi farklı ilerleme hızı parametre olarak belirlenmiştir. Belirlenen her bir ilerleme parametresi ile sabit kesme hızı ve eksenel derinlikte üç tekrarlı kalibrasyon deneyleri yapılmıştır. Deney koşullarının özdeş olabilmesi için numunelerin boyutları aynı boyutlara işlenmiş ve yüzeyleri taşlanmıştır. İş parçası olarak sıklıkla kullanılan mühendislik malzemesi AISI 4140 ıslah çeliği tercih edilmiştir. Frezeleme deneyleri, 3350 dev/dk iş mili hızı ve 10 kHz örnekleme aralığında, AlCrN kaplı Tungsten karbür(WC) alaşımından üretilmiş 38° helis açılı parmak frezeler ile 500 μm sabit eksenel derinlikte gerçekleştirilmiştir. Geliştirilen model ile yapılan kuvvet tahminleri deneysel ölçümlerle karşılaştırılmış ve tahminlerin %80-90 doğruluk aralığında deneysel verilerle uyum gösterdiği görülmüştür.
Keywords
Supporting Institution
Gazi Üniversitesi
Project Number
BAP-FYL-2021-7274
Thanks
Yazarlar, BAP-FYL-2021-7274 nolu proje ile sağlanan finansal destek için Gazi Üniversitesi ve takımların temin edilmesindeki katkılarından dolayı kesici takım üreticisi Karcan Kesici Takım Sanayi ve Ticaret A.Ş firmasına teşekkürlerini sunar.
References
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- [2] M. Ö. Neslihan Özsoy, “Optimization of Surface Roughness of AISI 1040 Stainless Steel in Milling Process Using Taguchi Method,” Sakarya University Journal of Science, vol. 23, no. 1. pp. 113–120, 2018, doi: 10.16984/saufenbilder.466053.
- [3] E. Kuram and B. Ozcelik, “Multi-objective optimization using Taguchi based grey relational analysis for micro-milling of Al 7075 material with ball nose end mill,” Meas. J. Int. Meas. Confed., vol. 46, no. 6, pp. 1849–1864, 2013, doi: 10.1016/j.measurement.2013.02.002.
- [4] İ. Korkut and M. A. Dönertaş, “Kesme Parametrelerinin Frezelemede Oluşan Kesme Kuvvetleri Üzerindeki Etkileri,” Politek. Derg., vol. 6, pp. 385–389, 2003, [Online]. Available: https://dergipark.org.tr/en/download/article-file/385965.
- [5] S. S. Park and M. Malekian, “Mechanistic modeling and accurate measurement of micro end milling forces,” CIRP Ann. - Manuf. Technol., vol. 58, no. 1, pp. 49–52, 2009, doi: 10.1016/j.cirp.2009.03.060.
- [6] Y. V. Srinivasa and M. S. Shunmugam, “Mechanistic model for prediction of cutting forces in micro end-milling and experimental comparison,” Int. J. Mach. Tools Manuf., vol. 67, pp. 18–27, 2013, doi: 10.1016/j.ijmachtools.2012.12.004.
- [7] Y. Altintas, Manufacturing Automation: Metal Cutting Mechanics, Machine Tool Vibrations, and CNC Design (2nd ed.), vol. 73, no. 6. 2012.
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- [9] W. B. Palmer and P. L. B. Oxley, “Mechanics of Orthogonal Machining,” Proc. Inst. Mech. Eng., vol. 173, no. 1, pp. 623–654, 1959, doi: 10.1243/pime_proc_1959_173_053_02.
- [10] M. E. Merchant, “Basic mechanics of metal cutting process,” J. Appl. Mech., vol. 11(A), pp. 168–175, 1944.
- [11] E. Budak, “Analytical models for high performance milling. Part I: Cutting forces, structural deformations and tolerance integrity,” Int. J. Mach. Tools Manuf., vol. 46, no. 12–13, pp. 1478–1488, 2006, doi: 10.1016/j.ijmachtools.2005.09.009.
- [12] F. Koenigsberger and A. J. P. Sabberwal, “An Investigation into The Cutting Force Pulsations During Milling Operations,” vol. I, no. 3, pp. 15–33, 1961.
- [13] S. Smith and J. Tlusty, “Overview of modeling and simulation of the milling process,” J. Eng. Ind., vol. 113, no. 2, pp. 169–175, 1991, doi: 10.1115/1.2899674.
- [14] W. A. Kline, R. E. DeVor, and I. A. Shareef, “The Prediction of Surface Accuracy in End Milling,” J. Eng. Ind., vol. 104, no. 3, pp. 272–278, Aug. 1982, doi: 10.1115/1.3185830.
- [15] E. J. A. Armarego and N. P. Deshpande, “Computerized Predictive Cutting Models for Forces in End-Milling Including Eccentricity Effects,” CIRP Ann., vol. 38, no. 1, pp. 45–49, 1989, doi: https://doi.org/10.1016/S0007-8506(07)62649-3.
- [16] E. Budak, Y. Altintaş, and E. J. A. Armarego, “Prediction of milling force coefficients from orthogonal cutting data,” J. Manuf. Sci. Eng. Trans. ASME, vol. 118, no. 2, pp. 216–224, 1996, doi: 10.1115/1.2831014.
- [17] Y. Altintas, A. Spence, and J. Tlusty, “End Milling Force Algorithms for CAD Systems,” CIRP Ann. - Manuf. Technol., vol. 40, no. 1, pp. 31–34, 1991, doi: 10.1016/S0007-8506(07)61927-1.
- [18] P. Lee and Y. Altintaş, “Prediction of ball-end milling forces from orthogonal cutting data,” Int. J. Mach. Tools Manuf., vol. 36, no. 9, pp. 1059–1072, 1996, doi: 10.1016/0890-6955(95)00081-X.
- [19] M. A. Rubeo and T. L. Schmitz, “Milling Force Modeling: A Comparison of Two Approaches,” Procedia Manuf., vol. 5, pp. 90–105, 2016, doi: 10.1016/j.promfg.2016.08.010.
- [20] A.J.P. Sabberwal, “An investigation into the chip section and cutting force during milling operation,” Victoria Universty of Manchester, 1961.
- [21] M. Wang, L. Gao, and Y. Zheng, “An examination of the fundamental mechanics of cutting force coefficients,” Int. J. Mach. Tools Manuf., vol. 78, pp. 1–7, 2014, doi: 10.1016/j.ijmachtools.2013.10.008.
Abstract
Milling is an important production method that is frequently used in many areas. It is important to understand the dynamics of the milling process to improve the quality and production performance of the parts. The cutting tools used in the milling operation have many different geometries. The geometry directly affects the occurred forces during the cutting process. Therefore, the occurred forces are essential parameters for tool design. In this study, a mechanistic model was developed using optimized data to predict shear forces. The measured force signals were optimized by the Fourier approximation method. For the calibration of the cutting coefficients, seven different feed rates were determined as parameters by preliminary tests. Three repetitive calibration experiments were performed at constant cutting speed and axial depth with each feed rate. In order to have identical test conditions, the samples were machined to the same dimensions and their surfaces were ground. AISI 4140 tempered steel was preferred for samples. Milling experiments were carried out with 38° helix angled end mills made of AlCrN coated Tungsten carbide (WC) alloy at a fixed axial depth of 500 μm. The spindle speed was at 3350 rpm, and the sampling rate was at 10 kHz. The force estimations from the developed model were compared with the experimental results and it was seen that the estimations were following the experimental results in accuracy between 80% and 90%.
Keywords
Project Number
BAP-FYL-2021-7274
References
- [1] M. F. Kahraman, H. Bilge, and S. Öztürk, “Uncertainty analysis of milling parameters using Monte Carlo simulation, the Taguchi optimization method and data-driven modeling,” Mater. Test., vol. 61, no. 5, pp. 477–483, 2019, doi: doi:10.3139/120.111344.
- [2] M. Ö. Neslihan Özsoy, “Optimization of Surface Roughness of AISI 1040 Stainless Steel in Milling Process Using Taguchi Method,” Sakarya University Journal of Science, vol. 23, no. 1. pp. 113–120, 2018, doi: 10.16984/saufenbilder.466053.
- [3] E. Kuram and B. Ozcelik, “Multi-objective optimization using Taguchi based grey relational analysis for micro-milling of Al 7075 material with ball nose end mill,” Meas. J. Int. Meas. Confed., vol. 46, no. 6, pp. 1849–1864, 2013, doi: 10.1016/j.measurement.2013.02.002.
- [4] İ. Korkut and M. A. Dönertaş, “Kesme Parametrelerinin Frezelemede Oluşan Kesme Kuvvetleri Üzerindeki Etkileri,” Politek. Derg., vol. 6, pp. 385–389, 2003, [Online]. Available: https://dergipark.org.tr/en/download/article-file/385965.
- [5] S. S. Park and M. Malekian, “Mechanistic modeling and accurate measurement of micro end milling forces,” CIRP Ann. - Manuf. Technol., vol. 58, no. 1, pp. 49–52, 2009, doi: 10.1016/j.cirp.2009.03.060.
- [6] Y. V. Srinivasa and M. S. Shunmugam, “Mechanistic model for prediction of cutting forces in micro end-milling and experimental comparison,” Int. J. Mach. Tools Manuf., vol. 67, pp. 18–27, 2013, doi: 10.1016/j.ijmachtools.2012.12.004.
- [7] Y. Altintas, Manufacturing Automation: Metal Cutting Mechanics, Machine Tool Vibrations, and CNC Design (2nd ed.), vol. 73, no. 6. 2012.
- [8] M. E. Merchant, “Mechanics of the metal cutting process. I. Orthogonal cutting and a type 2 chip,” J. Appl. Phys., vol. 16, no. 5, pp. 267–275, 1945, doi: 10.1063/1.1707586.
- [9] W. B. Palmer and P. L. B. Oxley, “Mechanics of Orthogonal Machining,” Proc. Inst. Mech. Eng., vol. 173, no. 1, pp. 623–654, 1959, doi: 10.1243/pime_proc_1959_173_053_02.
- [10] M. E. Merchant, “Basic mechanics of metal cutting process,” J. Appl. Mech., vol. 11(A), pp. 168–175, 1944.
- [11] E. Budak, “Analytical models for high performance milling. Part I: Cutting forces, structural deformations and tolerance integrity,” Int. J. Mach. Tools Manuf., vol. 46, no. 12–13, pp. 1478–1488, 2006, doi: 10.1016/j.ijmachtools.2005.09.009.
- [12] F. Koenigsberger and A. J. P. Sabberwal, “An Investigation into The Cutting Force Pulsations During Milling Operations,” vol. I, no. 3, pp. 15–33, 1961.
- [13] S. Smith and J. Tlusty, “Overview of modeling and simulation of the milling process,” J. Eng. Ind., vol. 113, no. 2, pp. 169–175, 1991, doi: 10.1115/1.2899674.
- [14] W. A. Kline, R. E. DeVor, and I. A. Shareef, “The Prediction of Surface Accuracy in End Milling,” J. Eng. Ind., vol. 104, no. 3, pp. 272–278, Aug. 1982, doi: 10.1115/1.3185830.
- [15] E. J. A. Armarego and N. P. Deshpande, “Computerized Predictive Cutting Models for Forces in End-Milling Including Eccentricity Effects,” CIRP Ann., vol. 38, no. 1, pp. 45–49, 1989, doi: https://doi.org/10.1016/S0007-8506(07)62649-3.
- [16] E. Budak, Y. Altintaş, and E. J. A. Armarego, “Prediction of milling force coefficients from orthogonal cutting data,” J. Manuf. Sci. Eng. Trans. ASME, vol. 118, no. 2, pp. 216–224, 1996, doi: 10.1115/1.2831014.
- [17] Y. Altintas, A. Spence, and J. Tlusty, “End Milling Force Algorithms for CAD Systems,” CIRP Ann. - Manuf. Technol., vol. 40, no. 1, pp. 31–34, 1991, doi: 10.1016/S0007-8506(07)61927-1.
- [18] P. Lee and Y. Altintaş, “Prediction of ball-end milling forces from orthogonal cutting data,” Int. J. Mach. Tools Manuf., vol. 36, no. 9, pp. 1059–1072, 1996, doi: 10.1016/0890-6955(95)00081-X.
- [19] M. A. Rubeo and T. L. Schmitz, “Milling Force Modeling: A Comparison of Two Approaches,” Procedia Manuf., vol. 5, pp. 90–105, 2016, doi: 10.1016/j.promfg.2016.08.010.
- [20] A.J.P. Sabberwal, “An investigation into the chip section and cutting force during milling operation,” Victoria Universty of Manchester, 1961.
- [21] M. Wang, L. Gao, and Y. Zheng, “An examination of the fundamental mechanics of cutting force coefficients,” Int. J. Mach. Tools Manuf., vol. 78, pp. 1–7, 2014, doi: 10.1016/j.ijmachtools.2013.10.008.
Details
| Primary Language | Turkish |
|---|---|
| Subjects | Engineering |
| Journal Section | Tasarım ve Teknoloji |
| Authors | |
| Project Number | BAP-FYL-2021-7274 |
| Publication Date | December 30, 2022 |
| Submission Date | March 21, 2022 |
| Published in Issue | Year 2022 Volume: 10 Issue: 4 |
