Processing, Please wait...

  • Home
  • About Us
  • Search:
  • Advanced Search

Growing Science » International Journal of Industrial Engineering Computations » Modeling and optimization of surface roughness and tool vibration in CNC turning of Aluminum alloy using hybrid RSM-WPCA methodology

Journals

  • IJIEC (726)
  • MSL (2637)
  • DSL (649)
  • CCL (508)
  • USCM (1092)
  • ESM (404)
  • AC (562)
  • JPM (247)
  • IJDS (912)
  • JFS (91)
  • HE (26)
  • SCI (26)

IJIEC Volumes

    • Volume 1 (17)
      • Issue 1 (9)
      • Issue 2 (8)
    • Volume 2 (68)
      • Issue 1 (12)
      • Issue 2 (20)
      • Issue 3 (20)
      • Issue 4 (16)
    • Volume 3 (76)
      • Issue 1 (9)
      • Issue 2 (15)
      • Issue 3 (20)
      • Issue 4 (12)
      • Issue 5 (20)
    • Volume 4 (50)
      • Issue 1 (14)
      • Issue 2 (10)
      • Issue 3 (12)
      • Issue 4 (14)
    • Volume 5 (47)
      • Issue 1 (13)
      • Issue 2 (12)
      • Issue 3 (12)
      • Issue 4 (10)
    • Volume 6 (39)
      • Issue 1 (7)
      • Issue 2 (12)
      • Issue 3 (10)
      • Issue 4 (10)
    • Volume 7 (47)
      • Issue 1 (10)
      • Issue 2 (14)
      • Issue 3 (10)
      • Issue 4 (13)
    • Volume 8 (30)
      • Issue 1 (9)
      • Issue 2 (7)
      • Issue 3 (8)
      • Issue 4 (6)
    • Volume 9 (32)
      • Issue 1 (9)
      • Issue 2 (6)
      • Issue 3 (7)
      • Issue 4 (10)
    • Volume 10 (34)
      • Issue 1 (8)
      • Issue 2 (10)
      • Issue 3 (8)
      • Issue 4 (8)
    • Volume 11 (36)
      • Issue 1 (9)
      • Issue 2 (8)
      • Issue 3 (9)
      • Issue 4 (10)
    • Volume 12 (29)
      • Issue 1 (9)
      • Issue 2 (6)
      • Issue 3 (8)
      • Issue 4 (6)
    • Volume 13 (41)
      • Issue 1 (10)
      • Issue 2 (8)
      • Issue 3 (10)
      • Issue 4 (13)
    • Volume 14 (50)
      • Issue 1 (11)
      • Issue 2 (15)
      • Issue 3 (9)
      • Issue 4 (15)
    • Volume 15 (55)
      • Issue 1 (19)
      • Issue 2 (15)
      • Issue 3 (12)
      • Issue 4 (9)
    • Volume 16 (75)
      • Issue 1 (12)
      • Issue 2 (15)
      • Issue 3 (19)
      • Issue 4 (29)

Keywords

Supply chain management(163)
Jordan(161)
Vietnam(148)
Customer satisfaction(120)
Performance(113)
Supply chain(108)
Service quality(98)
Tehran Stock Exchange(94)
Competitive advantage(93)
SMEs(86)
optimization(84)
Financial performance(83)
Trust(81)
TOPSIS(80)
Job satisfaction(79)
Sustainability(79)
Factor analysis(78)
Social media(78)
Knowledge Management(77)
Genetic Algorithm(76)


» Show all keywords

Authors

Naser Azad(82)
Mohammad Reza Iravani(64)
Zeplin Jiwa Husada Tarigan(60)
Endri Endri(45)
Muhammad Alshurideh(42)
Hotlan Siagian(39)
Jumadil Saputra(36)
Dmaithan Almajali(36)
Muhammad Turki Alshurideh(35)
Barween Al Kurdi(32)
Ahmad Makui(32)
Basrowi Basrowi(31)
Hassan Ghodrati(31)
Mohammad Khodaei Valahzaghard(30)
Shankar Chakraborty(29)
Ni Nyoman Kerti Yasa(29)
Sulieman Ibraheem Shelash Al-Hawary(28)
Prasadja Ricardianto(28)
Sautma Ronni Basana(27)
Haitham M. Alzoubi(27)


» Show all authors

Countries

Iran(2177)
Indonesia(1278)
Jordan(784)
India(782)
Vietnam(500)
Saudi Arabia(440)
Malaysia(438)
United Arab Emirates(220)
China(182)
Thailand(151)
United States(110)
Turkey(103)
Ukraine(102)
Egypt(97)
Canada(92)
Pakistan(84)
Peru(83)
Morocco(79)
United Kingdom(79)
Nigeria(77)


» Show all countries

International Journal of Industrial Engineering Computations

ISSN 1923-2934 (Online) - ISSN 1923-2926 (Print)
Quarterly Publication
Volume 8 Issue 3 pp. 385-398 , 2017

Modeling and optimization of surface roughness and tool vibration in CNC turning of Aluminum alloy using hybrid RSM-WPCA methodology Pages 385-398 Right click to download the paper Download PDF

Authors: Priyabrata Sahoo, Ashwani Pratap, Asish Bandyopadhyay

DOI: 10.5267/j.ijiec.2016.11.003

Keywords: CNC turning, Surface roughness, Tool vibration, RSM, WPCA, ANOVA

Abstract: This paper suggests an advanced hybrid multi output optimization technique by applying weighted principal component analysis (WPCA) incorporated with response surface methodology (RSM). This investigation has been carried out through a case study in CNC turning of Aluminum alloy 63400 for surface roughness (Ra) and tool vibration (db) optimization. Primarily, input parameters such as spindle speed (N), feed rate (S) and depth of cut (t) are designed for experiment by using RSM Box-Behnken methodology. The aluminum alloy workpieces are machined by using coated carbide tool (inserts) in dry environment. Secondly, the empirical model for the responses as the functions of cutting parameters are obtained through RSM technique and the adequacy of the models have been checked using analysis of variance (ANOVA). Finally, the process parameters are optimized using WPCA technique. The confirmatory experiment has been performed using optimized result and it reveals that multiple response performance index (MPI) value was increased by 0.2908 from initial setting. The increases in MPI value indicates that the aforesaid optimization methodology is suitably acceptable for multi response optimization for turning process.

How to cite this paper
Sahoo, P., Pratap, A & Bandyopadhyay, A. (2017). Modeling and optimization of surface roughness and tool vibration in CNC turning of Aluminum alloy using hybrid RSM-WPCA methodology.International Journal of Industrial Engineering Computations , 8(3), 385-398.

Refrences
Asiltürk, I., & Neşeli, S. (2012). Multi response optimisation of CNC turning parameters via Taguchi method-based response surface analysis. Measurement, 45(4), 785-794.
Datta, S., Nandi, G., Bandyopadhyay, A., & Pal, P. K. (2009). Application of PCA-based hybrid Taguchi method for correlated multicriteria optimization of submerged arc weld: a case study. The International Journal of Advanced Manufacturing Technology, 45(3-4), 276-286.
Feng, C. X. (2001). An experimental study of the impact of turning parameters on surface roughness. In Proceedings of the industrial engineering research conference (Vol. 2036).
Gupta, A., Singh, H., & Aggarwal, A. (2011). Taguchi-fuzzy multi output optimization (MOO) in high speed CNC turning of AISI P-20 tool steel. Expert Systems with Applications, 38(6), 6822-6828.
Kirby, E. D., Zhang, Z., & Chen, J. C. (2004). Development of an accelerometer-based surface roughness prediction system in turning operations using multiple regression techniques. Journal of Industrial Technology, 20(4), 1-8.
Knight, W. A., & Boothroyd, G. (2005). Fundamentals of metal machining and machine tools (Vol. 198). CRC Press.
Liao, H. C. (2006). Multi-response optimization using weighted principal component. The International Journal of Advanced Manufacturing Technology, 27(7-8), 720-725.
Makadia, A. J., & Nanavati, J. I. (2013). Optimisation of machining parameters for turning operations based on response surface methodology. Measurement, 46(4), 1521-1529.
Montgomery, D. C. (1997) Design and analysis of experiments, 4th ed., John wiley & Sons Inc., New York.
Phadke, M. S. (1995). Quality engineering using robust design. Prentice Hall PTR.
Palanikumar, K. (2010). Modeling and analysis of delamination factor and surface roughness in drilling GFRP composites. Materials and Manufacturing Processes, 25(10), 1059-1067.
Risbood, K. A., Dixit, U. S., & Sahasrabudhe, A. D. (2003). Prediction of surface roughness and dimensional deviation by measuring cutting forces and vibrations in turning process. Journal of Materials Processing Technology, 132(1), 203-214.
Roy, P., Sarangi, S. K., Ghosh, A., & Chattopadhyay, A. K. (2009). Machinability study of pure aluminium and Al–12% Si alloys against uncoated and coated carbide inserts. International Journal of Refractory Metals and Hard Materials, 27(3), 535-544.
Rudrapati, R., Pal, P. K., & Bandyopadhyay, A. (2016). Modeling and optimization of machining parameters in cylindrical grinding process. The International Journal of Advanced Manufacturing Technology, 82(9-12), 2167-2182.
Routara, B. C., Mohanty, S. D., Datta, S., Bandyopadhyay, A., & Mahapatra, S. S. (2010). Combined quality loss (CQL) concept in WPCA-based Taguchi philosophy for optimization of multiple surface quality characteristics of UNS C34000 brass in cylindrical grinding. The International Journal of Advanced Manufacturing Technology, 51(1-4), 135-143.
Routara, B. C., Sahoo, A. K., Parida, A. K., & Padhi, P. C. (2012). Response surface methodology and genetic algorithm used to optimize the cutting condition for surface roughness parameters in CNC turning. Procedia Engineering, 38, 1893-1904.
Senthilkumar, N., Tamizharasan, T., & Anandakrishnan, V. (2014). Experimental investigation and performance analysis of cemented carbide inserts of different geometries using Taguchi based grey relational analysis. Measurement, 58, 520-536.
Siddhpura, M., & Paurobally, R. (2012). A review of chatter vibration research in turning. International Journal of Machine tools and manufacture, 61, 27-47.
Su, C. T., & Tong, L. I. (1997). Multi-response robust design by principal component analysis. Total Quality Management, 8(6), 409-416.
Tobias, S. A. (1961). Machine tool vibration research. International Journal of Machine Tool Design and Research, 1(1), 1-14.
Wang, Z., Meng, H., & Fu, J. (2010). Novel method for evaluating surface roughness by grey dynamic filtering. Measurement, 43(1), 78-82.
  • 34
  • 1
  • 2
  • 3
  • 4
  • 5

Journal: International Journal of Industrial Engineering Computations | Year: 2017 | Volume: 8 | Issue: 3 | Views: 3493 | Reviews: 0

Related Articles:
  • Multi-attribute decision making parametric optimization and modeling in har ...
  • Response surface and artificial neural network prediction model and optimiz ...
  • Analysis of machining characteristics in drilling of GFRP composite with ap ...
  • Optimization of multiple performance characteristics in turning using Taguc ...
  • Effect of machining conditions on MRR and surface roughness during CNC Turn ...

Add Reviews

Name:*
E-Mail:
Review:
Bold Italic Underline Strike | Align left Center Align right | Insert smilies Insert link URLInsert protected URL Select color | Add Hidden Text Insert Quote Convert selected text from selection to Cyrillic (Russian) alphabet Insert spoiler
winkwinkedsmileam
belayfeelfellowlaughing
lollovenorecourse
requestsadtonguewassat
cryingwhatbullyangry
Security Code: *
Include security image CAPCHA.
Refresh Code

® 2010-2025 GrowingScience.Com