Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
International Journal on Interactive Design and Manufacturing (IJIDeM)
Published in: International Journal on Interactive Design and Manufacturing (IJIDeM) 2/2019

03-01-2019 | Technical Paper

Optimization of machining parameters of 2.25Cr1Mo0.25V steel based on response surface method and genetic algorithm

Authors: Wei Zhang, Lei Zhang, Shuqi Wang, Baichen Ren, Shuai Meng

Published in: International Journal on Interactive Design and Manufacturing (IJIDeM) | Issue 2/2019

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

High-strength steel 2.25Cr–1Mo–0.25V is an important material for making large pressure vessels due to its superior performance. First, study the effect of the interaction between cutting parameters on cutting force and material removal rate (MRR). The central composite response surface method was used to establish the prediction model of cutting force and MRR during the process of turning high strength steel 2.25Cr–1Mo–0.25V. Secondly, the variance analysis method was used to test the predictive model and the significance of each input parameter. The influence of the interaction between cutting parameters on the cutting force and MRR is analyzed, and the accuracy of the prediction model was further verified. Finally, the genetic algorithm is used to obtain the optimal combination of cutting parameters and the minimum cutting force and maximum MRR.
previous article Effect of friction stir welding (FSW) parameters on the peak temperature and the residual stresses of aluminum alloy 6061-T6: numerical modelisation

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
Literature
1.
Özel, T., Hsu, T.K., Zeren, E.: Effects of cutting edge geometry, workpiece hardness, feed rate and cutting speed on surface roughness and forces in finish turning of hardened AISI H13 steel. Int. J. Adv. Manuf. Technol. 25(3–4), 262–269 (2005)CrossRef
2.
Subramanian, M., Sakthivel, M.: Optimization of cutting parameters for cutting force in shoulder milling of Al7075-T6 using response surface methodology and genetic algorithm. Procedia Eng. 64(12), 690–700 (2013)CrossRef
3.
Asiltürk, İ., Akkuş, H.: Determining the effect of cutting parameters on surface roughness in hard turning using the Taguchi method. Measurement 44, 1697–1704 (2011)
4.
Nalbant, M., Gökkaya, H., Sur, G.: Application of Taguchi method in the optimization of cutting parameters for surface roughness in turning. Mater. Des. 28(4), 1379–1385 (2006)CrossRef
5.
Chen, X., Ma, L., Li, C., et al.: Experimental study and genetic algorithm-based optimization of cutting parameters in cutting engineering ceramics. Int. J. Adv. Manuf. Technol. 74(5–8), 807–817 (2014)CrossRef
6.
Kosaraju, S., Anne, V.G.: Optimal machining conditions for turning Ti–6Al–4V using response surface methodology. Adv. Manuf. 1(4), 329–339 (2013)CrossRef
7.
Dong, M., Wang, N.: Adaptive network-based fuzzy inference system with leave-one-out cross-validation approach for prediction of surface roughness. Appl. Math. Model. 35(3), 1024–1035 (2010)CrossRefMATH
8.
Zain, A.M., Haron, H.: Prediction of surface roughness in the end milling machining using fuzzy rule-based. Expert Syst. Appl. 37(2), 1755–1768 (2010)CrossRef
9.
Zain, A.M., Haron, H., Sharif, S.: Application of GA to optimize cutting conditions for minimizing surface roughness in end milling machining process. Expert Syst. Appl. 37(6), 4650–4659 (2009)CrossRef
10.
Palanisamy, P., Rajendran, I., Shanmugasundaram, S.: Optimization of machining parameters using genetic algorithm and experimental validation for end-milling operations. Int. J. Adv. Manuf. Technol. 32(7–8), 644–655 (2007)CrossRef
11.
Mandal, N., Doloi, B., Mondal, B.: Force prediction model of zirconia toughened alumina (ZTA) inserts in hard turning of AISI 4340 steel using response surface methodology. Int. J. Precis. Eng. Manuf. 13(9), 1589–1599 (2012)CrossRef
12.
Bouacha, K., Yallese, M.A., Mabrouki, T., et al.: Statistical analysis of surface roughness and cutting forces using response surface methodology in hard turning of AISI 52100 bearing steel with CBN tool. Int. J. Refract. Met. Hard Mater. 28(3), 349–361 (2009)CrossRef
13.
Liao, Y.S., Lin, H.M., Wang, J.H.: Behaviors of end milling Inconel 718 superalloy by cemented carbide tools. J. Mater. Process. Technol. 201, 460–465 (2007)CrossRef
14.
Chunjing, L., Dunbing, T., Hua, H., et al.: Analysis of surface roughness robustness based on response surface turning. J. Nanjing Univ. Aeronaut. Astronaut. 44(4), 520–525 (2012)
15.
Yongshou, L., Yaoyao, S., Junxue, R., et al.: Research on GH4169 milling force prediction model based on response surface methodology. Mech. Sci. Technol. 29(11), 1547–1552 (2010)
16.
Feng, J., Jiafei, Z., Ying, N., et al.: Optimization of cutting parameters of cemented carbide machining based on response surface methodology. Mech. Des. Res. 4, 112–115 (2015)
Metadata
Title
Optimization of machining parameters of 2.25Cr1Mo0.25V steel based on response surface method and genetic algorithm
Authors
Wei Zhang
Lei Zhang
Shuqi Wang
Baichen Ren
Shuai Meng
Publication date
03-01-2019
Publisher
Springer Paris
Published in
International Journal on Interactive Design and Manufacturing (IJIDeM) / Issue 2/2019
Print ISSN: 1955-2513
Electronic ISSN: 1955-2505
DOI
https://doi.org/10.1007/s12008-018-00525-8

Other articles of this Issue 2/2019

International Journal on Interactive Design and Manufacturing (IJIDeM) 2/2019 Go to the issue

Original Paper

Optimization of flexural strength of CFRP hybrid nano composites containing nanoZnO and nanoclay particles

Original paper

Computation of the stress intensity factor KI for external longitudinal semi-elliptic cracks in the pipelines by FEM and XFEM methods

Original paper

Dynamic effects on cutting forces with highly positive versus highly negative cutting edge geometries

Original Paper

The numerical study of the effect of design parameters on EWOD actuation in microchannels of rectangular cross section

Original Paper

Non-contact auxiliary fixture for machining stability improvement of thin flexible workpieces using eddy currents

Original Paper

Exploratory study on the perception of additively manufactured end-use products with specific questionnaires and eye-tracking

Premium Partner

    Image Credits