Multi-Criteria Decision-Making when Surface Grinding 9XC Steel with a Segmented Grinding Wheel

Do Duc Trung; Duong Van Duc; Hoang Xuan Thinh

doi:10.4028/p-297vsk

Paper Titles

Transient Numerical Simulation the Friction Stir Welding Process of Aa 2017 Alloys, Contact Parameter Effects on Thermal History and Material Flow
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Multi-Criteria Decision-Making when Surface Grinding 9XC Steel with a Segmented Grinding Wheel
p.11

On the Effect of Wave Signal Input via Zero Charge Corrosion Protection in 3.5% NaCl Solution
p.21

Influence of Ti on Oxide Formation During Isothermal Oxidation of 800H Ni-Based Alloys
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Reduction of Life Time Expectation of Standard Duplex Stainless Steel Exposed to Hydrogen under Corrosion Fatigue Conditions
p.35

Comparative Studies on the Electrical Properties of PEDOT:PSS Doped SNP Films and Hydrogels for Medical Electrode Applications
p.43

Study on the Surface Area of Electrospun Magnesium Oxide (MgO) Nanofibers
p.51

Surface Characterization of Lüders Band on NiTi Shape Memory Alloy
p.57

HomeKey Engineering MaterialsKey Engineering Materials Vol. 929Multi-Criteria Decision-Making when Surface...

Multi-Criteria Decision-Making when Surface Grinding 9XC Steel with a Segmented Grinding Wheel

Abstract:

9XC steel is a steel alloy of the commonly used tool to make a variety of products. When manufacturing such products, surface grinding method is commonly used as the final machining method for critical surfaces. Therefore, it is very necessary to research for improving surface quality and machining productivity when grinding this steel. In this study, Multi-Criteria Decision-Making (MCDM) is presented when surface grinding 9XC steel with a segmented grinding wheel. Taguchi method has been chosen to design the experimental matrix. MCDM has been performed using Proximity Indexed Value (PIV). This study has determined the value of workpiece velocity, feed rate and depth of cut to simultaneously ensure the minimum surface roughness and the maximum Material Removal Rate (MRR). The effect of cutting parameters on surface roughness has been also discussed.

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Periodical:

Key Engineering Materials (Volume 929)

Pages:

11-17

DOI:

https://doi.org/10.4028/p-297vsk

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Online since:

August 2022

Authors:

Do Duc Trung*, Duong Van Duc, Hoang Xuan Thinh

Keywords:

9XC Steel, MCDM, PIV, Segmented Grinding Wheel, Surface Grinding, Taguchi

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* - Corresponding Author

References

[1] L. A. Tung, Research to improve the efficiency of final surface grinding process, Doctoral thesis in engineering, Thainguyen University, (2020).

Google Scholar

[2] T. T. Hong, N. V. Cuong, L. H. Ky, N. Q. Tuan, B. T. Long, L. A. Tung, N. T. Tu, and V. N. Pi, Multi-Criteria Optimization of Dressing Parameters for Surface Grinding 90CrSi Tool Steel Using Taguchi Method and Grey Relational Analysis, Materials Science Forum 998 (2020) 61-68.

DOI: 10.4028/www.scientific.net/msf.998.61

Google Scholar

[3] L. A. Tung, V. N. Pi, V. T. Lien, T. T. Hong, L. X. Hung, B.T. Long, Optimization of dressing parameters of grinding wheel for 9CrSi tool steel using the taguchi method with grey relational analysis, IOP Conf. Series: Materials Science and Engineering 635(012030) (2019) 1-8.

DOI: 10.1088/1757-899x/635/1/012030

Google Scholar

[4] V. N. Pi, L. A. Tung, T. T. Hong, N. T. T. Nga, L. X. Hung, and B. T. Long, An optimization of exchanged grinding wheel diameter when surface grinding alloy tool steel 9CrSi, Materials Today: Proceedings 18 (2019) 2225-2233.

DOI: 10.1016/j.matpr.2019.07.002

Google Scholar

[5] H. J. D. Mello, D. R. D. Mello, E. C. Bianchi, P. R. de Aguiar, D. M. D. Addona, Grinding of AISI 4340 steel with interrupted cutting by aluminum oxide grinding wheel, Rem Revista Escola de Minas 68(2) (2015) 229-238.

DOI: 10.1590/0370-44672015680070

Google Scholar

[6] E. C. Bianchi, B. K. Sato, A. R. Saless, J. C. Lopes, H. J. de Mello, L. E. de Angelo Sanchez, A. E.Diniz, P. R. Aguiar, Evaluating the effect of the compressed air wheel cleaning in grinding the AISI 4340 steel with CBN and MQ L with water, The International Journal of Advanced Manufacturing Technology 95 (2018) 2855–2864.

DOI: 10.1007/s00170-017-1433-4

Google Scholar

[7] M. Manikandan, S. Prabagaran, N. M. Sivaram, S. D. Milon, Producing Optimum Quality Grinding Spindle Using Hardened AISI 4340 Steel through a Cylindrical Grinding Process, International Journal of Innovative Technology and Exploring Engineering 9(2) (2019) 447-454.

DOI: 10.35940/ijitee.b6437.129219

Google Scholar

[8] D.X. Jin, Z. Meng, Research for discontinuous grinding wheel with multi- porous grooves, Key Engineering Materials 259 (2004) 117–121.

DOI: 10.4028/www.scientific.net/kem.259-260.117

Google Scholar

[9] M.S. Phadke, Quality Engineering Using Robust Design, Printice Hall, (1989).

Google Scholar

[10] S. Mufazzal, S. M. Muzakkir, A New Multi-Criterion Decision Making (MCDM) Method Based on Proximity Indexed Value for Minimizing Rank Reversals, Computers & Industrial Engineering 119 (2018) 427-438.

DOI: 10.1016/j.cie.2018.03.045

Google Scholar

[11] D. D. Trung, N. V. Thien, N. T. Nguyen, Application of TOPSIS Method in Multi-Objective Optimization of the Grinding Process Using Segmented Grinding Wheel, Tribology in industry 43(1) (2021) 12-22.

DOI: 10.24874/ti.998.11.20.12

Google Scholar

[12] D. D. Trung, N. T. Nguyen, D. H. Tien, H. L. Dang, A research on the multi-objective optimization of the grinding process using segmented grinding wheel by Taguchi-Dear method, EUREKA: Physics and Engineering 2021(1) (2021) 67-77.

DOI: 10.21303/2461-4262.2021.001612

Google Scholar

[13] Z.-H. Zou, Y. Yun, J.-N. Sun, Entropy method for determination of weight of evaluating indicators in fuzzy synthetic evaluation for water quality assessment, Journal of Environmental Sciences 18(5) (2006) 1020-1023.

DOI: 10.1016/s1001-0742(06)60032-6

Google Scholar

[14] E. K. Zavadskas, J. Antucheviciene, P. Chatterjee, Multiple-Criteria Decision Making (MCDM) Techniques for Business Processes Information Management, information 10(4) (2020) 1-7.

DOI: 10.3390/info10010004

Google Scholar