Optimasi Nilai Surface Roughness dan Material Removal Rate Pemesinan Milling Hauw Gan ZX 7550Z Menggunakan Metode Taguchi dan Grey Relational Analysis

Authors

  • Nadila Attin Miftah Telkom University
  • Denny Sukma Eka Atmaja Telkom University
  • Ayudita Oktafiani Telkom University

Abstract

Abstrak-Pada proses milling, produk yang dihasilkan harus memiliki kualitas tinggi dalam waktu yang singkat. Kualitas berhubungan dengan surface roughness sedangkan produktivitas berhubungan dengan material removal rate. Keduanya saling ketergantungan dan korelasi yang kompleks sehingga sulit untuk dipahami karena banyak faktor yang mempengaruhi seperti parameter pemesinan. Sebagian besar parameter pemotongan dipilih berdasarkan pengalaman atau mengacu pada handbook sehingga tidak menjamin bahwa yang dipilih adalah parameter yang optimum. Apabila yang dipilih salah atau tidak optimal maka menyebabkan kerugian ekonomi. Penelitian ini bertujuan untuk optimasi multi-respon pada proses pemesinan milling material alumunium alloy 6061 T6 menggunakan metode Taguchi dan grey relational analysis. Eksperimen dilakukan dengan menggunakan tiga parameter input yaitu spindle speed, feed rate, dan depth of cut berdasarkan L9 orthogonal array yang dirancang menggunakan metode Taguchi. Nilai surface roughness (Ra = 0,395 µm) dan material removal rate (MRR = 105 mm3/min) optimum dicapai pada kombinasi parameter  spindle speed 1400 rpm, feed rate 15 mm/min, dan depth of cut 0,7 mm.

Kata kunci- surface roughness, material removal rate, Taguchi, grey relational analysis

References

Kemenperin, “Laju Sektor Manufaktur Lampaui Pertumbuhan Ekonomi,” May 09, 2022. Accessed: Sep. 03, 2022. [Online]. Available: https://www.google.com/search?q=Laju+Sektor+Manufaktur+Lampaui+Pertumbuhan+Ekonomi&oq=Laju+Sektor+Manufaktur+Lampaui+Pertumbuhan+Ekonomi&aqs=chrome..69i57j69i60.1142j0j7&sourceid=chrome&ie=UTF-8

A. Shahin, “The Relationship Between Quality And Productivity: A New Perspective,” Int. J. Productivity and Quality Management, vol. 3, no. 2, pp. 206–222, 2008.

O. G. & Ehibor and B. N. G. Aliemeke, “Optimization of Process Parameters of Surface Roughness and Material Removal Rate in Orthogonal Turning of AISI 1045 Carbon Steel Using Taguchi Technique,” Industrial Engineering Letters, vol. 10, no. 4, pp. 16–25, 2021, doi: 10.7176/IEL/10-4-03.

S. K. Shihab and E. M. M. Mubarak, “Evaluation of Surface Roughness and Material Removal Rate in End Milling of Complex Shape,” Universal Journal of Mechanical Engineering, vol. 4, no. 3, pp. 69–73, Jun. 2016, doi: 10.13189/ujme.2016.040303.

S. Moshat, S. Datta, A. Bandyopadhyay, and P. K. Pal, “Optimization of CNC end milling process parameters using PCA-based Taguchi method,” International Journal of Engineering, Science and Technology, vol. 2, no. 1, pp. 92–102, 2010, [Online]. Available: www.ijest-ng.com

Sredanovic B, Cica D, Tesic S, and Kramar D, “Optimization Of Cutting Parameters For Minimizing Specific Cutting Energy And Maximizing Productivity In Turning Of AISI 1045 Steel,” International Scientific Journal - Machines, Technologies, Materials, vol. 13, no. 11, pp. 491–494, 2019.

S. Agrawal, M. kumar Gaur, D. kumar Kasdekar, and S. Agrawal, “Optimization Of Machining Parameters Of Hard Porcelain On A CNC Machine by Taguchi-and RSM Method,” International Journal of Engineering, Science and Technology, vol. 10, no. 1, pp. 13–22, Feb. 2018, doi: 10.4314/ijest.v10i1.2.

L. Bouzid, S. Boutabba, M. A. Yallese, S. Belhadi, and F. Girardin, “Simultaneous Optimization of Surface Roughness and Material Removal Rate for Turning of X20Cr13 Stainless Steel,” International Journal of Advanced Manufacturing Technology, vol. 74, no. 5–8, pp. 879–891, Sep. 2014, doi: 10.1007/s00170-014-6043-9.

P. Kotler and K. L. Keller, Marketing Management. United States of America: Perason, 2012.

X. Zhang, X. Li, H. Wang, and T. Zhang, “Multi-Objective Optimization of Machining Parameters During Milling of Carbon-Fiber-Reinforced Polyetheretherketone Composites Using Grey Relational Analysis,” Advances in Mechanical Engineering, vol. 12, no. 10, 2020, doi: 10.1177/1687814020966232.

J. T. Black and R. A. Kohser, Materials and Processes in Manufacturing, 10th ed. United States of America: Wiley, 2008.

H. Yanuar, A. Syarief, and A. Kusairi, “Pengaruh Variasi Kecepatan Potong dan Kedalaman Pemakanan Terhadap Kekasaran Permukaan Dengan Berbagai Media Pendingin Pada Proses Frais Konvensional,” Jurnal Ilmiah Teknik Mesin Unlam, vol. 03, no. 1, pp. 27–33, 2014.

Rusnaldy and B. Setiyana, “Pengaruh Pemakanan (Feed) Terhadap Geometri dan Kekerasan Geram Pada High Speed Machining Process,” ROTASI, vol. 8, no. 1, pp. 15–20, 2006.

T. C. Phokane, K. Gupta, and C. Anghel, “Optimization of Gear Manufacturing for Quality and Productivity,” Jurnal Optimasi Sistem Industri, vol. 21, no. 1, pp. 20–27, May 2022, doi: 10.25077/josi.v21.n1.p20-27.2022.

N. N. Tetelepta, “Penggunaan Pahat Ball End Mill Terhadap Kekasaran Permukaan Pada Material Baja ST 37,” J Teknol, vol. 9, no. 1, pp. 1018–1028, 2012.

M. Solanki and A. Jain, “Optimization Of Material Removal Rate And Surface Roughness Using Taguchi Based Multi-Criteria Decision Making (MCDM) Technique For Turning AL-6082,” Proceedings on Engineering Sciences, vol. 3, no. 3, pp. 303–318, 2021, doi: 10.24874/PES03.03.007.

J. Z. Zhang and J. C. Chen, “Surface roughness optimization in a drilling operation using the taguchi design method,” Materials and Manufacturing Processes, vol. 24, no. 4, pp. 459–467, Apr. 2009, doi: 10.1080/10426910802714399.

D. Thakur, B. Ramamoorthy, and L. Vijayaraghavan, “Optimization of High Speed Turning Parameters of Super Alloy Inconel 718 Material Using Taguchi Technique,” Indian Journal of Engineering & Materials Sciences, vol. 16, pp. 44–50, 2009.

A. T. Wibowo, G. D. Haryadi, and Y. Umardani, “Pengaruh Heat Treatment T6 Pada Aluminium Alloy 6061-O Dan Pengelasan Transversal Tungsten Inert Gas Terhadap Sifat Mekanik Dan Struktur Mikro,” Jurnal Teknik Mesin, vol. 2, no. 4, pp. 374–381, 2014.

N. Ahmad and T. v. Janahiraman, “A comparison on optimization of surface roughness in machining AISI 1045 steel using Taguchi method, genetic algorithm and particle swarm optimization,” Proceedings - 2015 IEEE Conference on System, Process and Control, ICSPC 2015, pp. 129–133, May 2016, doi: 10.1109/SPC.2015.7473572.

H. C. Liao, “Using PCR-TOPSIS To Optimize Taguchi’s Multi-Response Problem,” International Journal of Advanced Manufacturing Technology, vol. 22, no. 9–10, pp. 649–655, 2003, doi: 10.1007/s00170-002-1485-x.

C. Lin, “Use of the Taguchi Method and Grey Relational Analysis to Optimize Turning Operations with Multiple Performance Characteristics,” Materials And Manufacturing Processes, vol. 19, no. 2, pp. 209–220, 2004, doi: 10.1081/AMP-120029852.

K. Jangra, S. Grover, and A. Aggarwal, “Simultaneous optimization of material removal rate and surface roughness for WEDM of WCCo composite using grey relational analysis along with Taguchi method,” International Journal of Industrial Engineering Computations, vol. 2, no. 3, pp. 479–490, 2011, doi: 10.5267/j.ijiec.2011.04.005.

N. Lusi, D. Ridlo Pamuji, A. Fiveriati, A. Afandi, and G. Sandy Prayogo, “Application of Taguchi and Grey Relational Analysis for Parametric Optimization of End Milling Process of ASSAB-XW 42,” Advance in Engineering Research, vol. 198, pp. 514–517, 2020.

S. S. Warsi, M. H. Agha, R. Ahmad, S. H. I. Jaffery, and M. Khan, “Sustainable turning using multi-objective optimization: a study of Al 6061 T6 at high cutting speeds,” International Journal of Advanced Manufacturing Technology, vol. 100, no. 1–4, pp. 843–855, Jan. 2019, doi: 10.1007/s00170-018-2759-2.

M. K. Das, K. Kumar, T. K. Barman, P. Sahoo, M. K. Das, and K. Kumar, “Optimisation of EDM process parameters using grey-Taguchi technique,” Int. J. Machining and Machinability of Materials, vol. 15, pp. 28–30, 2014.

K. Shi, D. Zhang, and J. Ren, “Optimization of process parameters for surface roughness and microhardness in dry milling of magnesium alloy using Taguchi with grey relational analysis,” International Journal of Advanced Manufacturing Technology, vol. 81, no. 1–4, pp. 645–651, Oct. 2015, doi: 10.1007/s00170-015-7218-8.

P. Sivaiah and D. Chakradhar, “Multi-objective optimisation of cryogenic turning process using Taguchi-based grey relational analysis,” 2017.

M. P. Groover, Fundamentals of Modern Manufacturing: Materials, Processes, and Systems, 5th ed. United States of America: Wiley, 2013.

J. Paulo. Davim, Modern Machining Technology: A Practical Guide. New Delhi: Woodhead Publishing, 2011.

A. Mufarrih, H. Istiqlaliyah, and M. M. Ilha, “Optimization of Roundness, MRR and Surface Roughness on Turning Process using Taguchi-GRA,” in Journal of Physics: Conference Series, Aug. 2019, vol. 1179, no. 1. doi: 10.1088/1742-6596/1179/1/012099.

S. Kalpakjian and S. R. Schmid, Manufacturing Engineering And Technology, 6th ed. New York: Pearson, 2009.

R. K. Roy, Design of Experiments Using The Taguchi Approach 16 Steps to Product and Process Improvement. United States of America: John Wiley & Sons Inc, 2001.

D. C. S. Summers, Quality, 6th ed. United States of America: Pearson, 2018.

H. Dave, S. Vallabhbhai, S. Kumar, and K. P. Desai, “Study on Micro Hole Accuracy And Electrode Depletion during Micro EDM Process Through Grey Based Taguchi Approach,” International Conference on Production and Industrial Engineering, pp. 999–1004, 2013, [Online]. Available: https://www.researchgate.net/publication/236014396

K. Soorya Prakash, P. M. Gopal, and S. Karthik, “Multi-objective optimization using Taguchi based grey relational analysis in turning of Rock dust reinforced Aluminum MMC,” Measurement (Lond), vol. 157, Jun. 2020, doi: 10.1016/j.measurement.2020.107664.

R. S. Pawade and S. S. Joshi, “Multi-objective optimization of surface roughness and cutting forces in high-speed turning of Inconel 718 using Taguchi grey relational analysis (TGRA),” International Journal of Advanced Manufacturing Technology, vol. 56, no. 1–4, pp. 47–62, Sep. 2011, doi: 10.1007/s00170-011-3183-z.

S. Winarni and S. W. Indratno, “Application of multi response optimization with grey relational analysis and fuzzy logic method,” J Phys Conf Ser, vol. 948, no. 1, 2018, doi: 10.1088/1742-6596/948/1/012075.

A. N. Haq, P. Marimuthu, and R. Jeyapaul, “Multi Response Optimization of Machining Parameters of Drilling Al/SiC Metal Matrix Composite Using Grey Relational Analysis in The Taguchi Method,” International Journal of Advanced Manufacturing Technology, vol. 37, no. 3–4, pp. 250–255, May 2008, doi: 10.1007/s00170-007-0981-4.

M. Gupta and S. Kumar, “Multi-objective optimization of cutting parameters in turning using grey relational analysis,” International Journal of Industrial Engineering Computations, vol. 4, no. 4, pp. 547–558, 2013, doi: 10.5267/j.ijiec.2013.06.001.

J. Kundu and H. Singh, “Friction Stir Welding of AA5083 Aluminium Alloy: Multi-Response Optimization Using Taguchi-Based Grey Relational Analysis,” Advances in Mechanical Engineering, vol. 8, no. 11, pp. 1–10, Nov. 2016, doi: 10.1177/1687814016679277.

L. M. Maiyar, R. Ramanujam, K. Venkatesan, and J. Jerald, “Optimization of Machining Parameters For End Milling of Inconel 718 Super Alloy Using Taguchi Based Grey Relational Analysis,” Procedia Eng, vol. 64, pp. 1276–1282, 2013, doi: 10.1016/j.proeng.2013.09.208.

D. S. E. Atmaja and M. K. Herliansyah, “Optimasi Parameter Pengukuran Dimensi dan Defect Ubin Keramik dengan Metode Taguchi,” Jurnal Sistem Cerdas, vol. 4, no. 3, pp. 171–179, 2021.

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,” Measurement, vol. 46, no. 6, pp. 1849–1864, Jul. 2013, doi: 10.1016/J.MEASUREMENT.2013.02.002.

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Published

2023-06-26

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Program Studi S1 Teknik Industri