Article
Licensed
Unlicensed Requires Authentication

Optimization of the milling parameters for an Al/Si3N4 functionally graded composite using grey relational analysis

  • , , and
Published/Copyright: July 3, 2018
Become an author with De Gruyter Brill
Submit Manuscript Author Information
Materials Testing
From the journal Materials Testing Volume 60 Issue 2

Abstract

This study involves the multi-objective optimization of end milling process parameters during machining of Al-Si5Cu3/Si3N4 functionally graded metal matrix composite that was fabricated using centrifugal casting route. The dimension of the cast sample was 150 × 150 × 20 mm3. The hardness of the sample was measured along the radial direction. It was found that the hardness at the outer periphery was greater than that of other points along the radial direction. Therefore, the machining experiment was carried out only at the outer periphery. Taguchi's design of experiments method was employed and sixteen levels of experiments were conducted by varying the input parameters namely the cutting speed (355, 500, 710 and 1000 rpm), the depth of cut (0.5, 0.9, 1.2 and 1.5 mm) and the feed rate (250, 315, 400 and 500 mm × min−1). Multi-objective optimization using grey relational analysis was performed and the optimal set of input parameters were found to be cutting speed of 1000 rpm, feed rate of 250 mm × min−1 and depth of cut of 1.5 mm. Using analysis of variance technique, it was found that cutting speed, depth of cut and feed rate have an influence of 63.57, 16.83 and 8 %, respectively, on the optimal solution.

Kurzfassung

Der vorliegende Beitrag behandelt die mehrdimensionale Optimierung von Prozessparametern des Endfräsens während der Bearbeitung eines funktionsgradierten Komposites vom Typ Al-Si5Cu3/Si3N4, das mittels Zentrifugalgießens hergestellt wurde. Die Dimensionen des Gussstückes betrugen 150 × 150 × 20 mm3. Die Härte der Probe wurde in radialer Richtung gemessen. Es stellte sich heraus, dass die Härte in der äußeren Peripherie höher als an anderen Punkten in radialer Richtung war. Daher wurde das Bearbeitungsexperiment nur an der äußeren Peripherie durchgeführt. Es wurde das Taguchi-Verfahren für das Design der Experimente angewandt und dabei 16 Experimentebenen durchgeführt, in dem die Inputparameter variiert wurden, und zwar die Schnittgeschwindigkeit (355, 500, 710 und 1000 U × min−1), die Schnitttiefe (0,5, 0,9, 1,2 und 1,5 mm) und die Vorschubrate (250, 315, 400 und 500 mm × min−1). Es wurde eine mehrdimensionale Optimierung mittels der Grey-Relationsanalyse durchgeführt und als optimaler Parametersatz zeigten sich eine Schnittgeschwindigkeit von 1000 U × min−1, eine Vorschubrate von 250 mm × min−1 und eine Schnitttiefe von 1,5 mm. Mittels der Varianzanalyse wurde bestimmt, dass die Vorschubgeschwindigkeit, die Schnitttiefe und die Vorschubrate einen entsprechenden Einfluss von 63,57, 16,83 bzw. 8 % haben.

*Correspondence Address, Associate Prof. Dr. N. Radhika, Department of Mechanical Engineering, Amrita School of Engineering, Amrita University, Coimbatore 641 112, Tamil Nadu, lndia, E-mail:

Aravindh Venkatachalam, born in 1995, is a BTech student in Mechanical Engineering at Amrita School of Engineering, Coimbatore, Tamil Nadu, India.

Palakollu Venkata Sai Anurag, born in 1996, is a BTech student in Mechanical Engineering at Amrita School of Engineering, Coimbatore, Tamil Nadu, India.

Toppey Dhuruvan Sadanand, born in 1995, is a BTech student in Mechanical Engineering at Amrita School of Engineering, Coimbatore, Tamil Nadu, India.

Assoc. Prof. Dr. Radhika Nachimuthu is working as Associate Professor in the Department of Mechanical Engineering at Amrita School of Engineering, Coimbatore Campus, Tamil Nadu, India. She completed her PhD in Mechanical Engineering at Anna University, Coimbatore. Her areas of research include composite materials, metal matrix composite and functionally graded materials.

References

1 J. H.Gibbons: Advanced Materials by Design, New Structural Material Technologies, US Congress, Office of Technology Assessment, Washington, USA (1988)Search in Google Scholar

2 R. M.Mojhamood, E. T.Akinlabi, M.Shukla, S.Pityana: Functionally graded material: An overview, Proceedings of the World Congress on Engineering, London, UK (2012), pp. 1593–1597Search in Google Scholar

3 G.Udupa, S. ShrikanthRao, K. V.Gangadharan: Functionally graded composite materials: An overview, International Conference on Advances in Manufacturing and Materials Engineering5 (2014), pp. 1291–129910.1016/j.mspro.2014.07.442Search in Google Scholar

4 G. N.Praveen, J. N.Reddy: Nonlinear transient thermoelastic analysis of functionally graded ceramic metal plates, International Journal of Solid Structures35 (1997), No. 33, pp. 4457–447610.1016/S0020-7683(97)00253-9Search in Google Scholar

5 Y. D.Lee, F.Erdogan: Residual/thermal stresses in FGMs and laminated thermal barrier coatings, International Journal of Fracture69 (1994), No. 2, pp. 145–16510.1007/BF00035027Search in Google Scholar

6 J.Aboudi, M.-J.Pindera, M. S.Arnold: Microstructural optimization of functionally graded composites (FGC) subjected to thermal gradient via coupled higher-order theory, Composites Part B28 (1997), No. 7, pp. 93–10810.1016/S1359-8368(96)00034-0Search in Google Scholar

7 BalamuruganGopalasamy, BiswanathMondal, SukamalGhosh: Taguchi method and ANOVA: An approach for process parameters optimization of hard machining while machining hardened steel, Journal of Scientific and Industrial Research68 (2009), pp. 686–695Search in Google Scholar

8 A. NoorulHaq, P.Marimuthu, R.Jayapaul: Multiresponse optimization of machining parameters of drilling Al/SiC MMCs using GRA in Taguchi method, International Journal of Advanced Manufacturing Technology37 (2008), No. 3, pp. 250–25510.1007/s00170-007-0981-4Search in Google Scholar

9 J. T.Huang, Y. S.Liao: Optimization of machining parameters of wire-electro discharge machining based on GRA and statistical analysis, International Journal of Production Research41 (2008), No. 8, pp. 1707–172010.1080/1352816031000074973Search in Google Scholar

10 E.Kuram, B.Ozcelik: Multi objective optimization using Taguchi based GRA for micro milling of Al 7075 material with ball nose end mill, Measurement46 (2013), No. 6, pp. 1849–186410.1016/j.measurement.2013.02.002Search in Google Scholar

11 J. P.Davim, P.Reis: Damage and dimensional precision on milling carbon-fibre reinforced plastics using design experiments, Journal of Materials Processing Technology160 (2005), pp. 160–16710.1016/j.jmatprotec.2004.06.003Search in Google Scholar

12 N.Radhika, R.Subramanian, S. VenkatPrasat: Wear behaviour of alumiunium/alumina/graphite hybrid metal matrix composites using Taguchi's techniques, Journal of Industrial Lubrication and Tribology65 (2013), No. 3, pp. 166–17410.1108/00368791311311169Search in Google Scholar

13 J. L.Deng: Introduction to grey system theory, The Journal of Grey System1 (1989), pp. 1–24Search in Google Scholar

14 R.Sallehuddin, Siti Marriyam HjShamsuddin, Siti Zaitan MohdHashim: Application of GRA for multivariate time series, Proc. of the 8th International Conference on Intelligent Systems Design and Applications, Kaohsiung, Taiwan (2008), pp. 432–437Search in Google Scholar

15 N.Radhika, G. KishoreChandran, P.Shivaram, K. T. VijayKarthik: Multi-objective optimization of EDM parameters using grey relational analysis, Journal of Engineering Science and Technology10 (2015), No. 1, pp. 1–11Search in Google Scholar

16 A.Manna, B.Bhattacharayya: A study of machinability of Al-SiC MMC, Journal of Materials Processing Technology140 (2003), pp. 711–71610.1016/S0924-0136(03)00905-1Search in Google Scholar

17 R. ChinmayaDandekar, Y. C.Shin: Modelling of machining of composite materials: A review, International Journal of Machine Tools and Manufacture57 (2012), pp. 102–12110.1016/j.ijmachtools.2012.01.006Search in Google Scholar

18 K.Palanikumar, R.Karthikeyan: Assessment of factors influencing surface roughness on the machining of aluminium silicon-carbide particulate composite, Materials and Design28 (2007), No. 5, pp. 1584–159110.1016/j.matdes.2006.02.010Search in Google Scholar

19 S. C.Black, V.Chiles, A. J.Lissaman, S. J.Martin: Principles of Engineering Manufacture, 3rd Ed., Elsevier Science, Amsterdam, Netherland (1998)Search in Google Scholar

20 N.Radhika, P.Shivaram, K. T. VijayKarthik: Multi-objective optimization in electric discharge machining of aluminium composite, Tribology in Industry36 (2014), No. 4, pp. 428–436Search in Google Scholar

Published Online: 2018-07-03
Published in Print: 2018-02-02

© 2018, Carl Hanser Verlag, München

Articles in the same Issue

  1. Inhalt/Contents
  2. Contents
  3. Fachbeiträge/Technical Contributions
  4. SteBLife – A new short-time procedure for the calculation of S-N curves and failure probabilities
  5. Surface treatment for effective bonding in the sports industry
  6. Effect of different rotational speeds on mechanical and metallurgical properties of friction welded dissimilar steels
  7. Comparison of titanium and FGM dental implants with different coating types
  8. Weld quality and productivity of AISI 4140 steel welded by unpulsed and pulsed GMAW
  9. Corrosion behavior of Hastelloy® C–4® Ni–Cr–Mo–Fe alloys for coal gasification syngas plants
  10. Application of FactSage® thermodynamic modeling for predicting the ash transformation with temperatures under partial slagging entrained flow coal gasification condition
  11. Röntgen- und Neutronentomographie am knöchernen Innenohr der Bartenwale
  12. Partial repair of thermally sprayed and sealed corrosion protection – Organic coating material or thermal spraying?
  13. Experimental study on solidification of Cu(II)-contaminated soil using red mud with cement and Ca(OH)2
  14. Tribological study of sintered iron based and copper based brake materials by pin-on-disc method
  15. Influence of drilling parameters on temperature and surface roughness of AISI O2 steel
  16. Multi-fractal characteristics of particle size distribution of granular backfilling materials under different loads
  17. Dry sliding behavior of aluminum alloy 8011 with 4 % fly ash
  18. Optimization of the milling parameters for an Al/Si3N4 functionally graded composite using grey relational analysis
https://doi.org/10.3139/120.111128

Articles in the same Issue

  1. Inhalt/Contents
  2. Contents
  3. Fachbeiträge/Technical Contributions
  4. SteBLife – A new short-time procedure for the calculation of S-N curves and failure probabilities
  5. Surface treatment for effective bonding in the sports industry
  6. Effect of different rotational speeds on mechanical and metallurgical properties of friction welded dissimilar steels
  7. Comparison of titanium and FGM dental implants with different coating types
  8. Weld quality and productivity of AISI 4140 steel welded by unpulsed and pulsed GMAW
  9. Corrosion behavior of Hastelloy® C–4® Ni–Cr–Mo–Fe alloys for coal gasification syngas plants
  10. Application of FactSage® thermodynamic modeling for predicting the ash transformation with temperatures under partial slagging entrained flow coal gasification condition
  11. Röntgen- und Neutronentomographie am knöchernen Innenohr der Bartenwale
  12. Partial repair of thermally sprayed and sealed corrosion protection – Organic coating material or thermal spraying?
  13. Experimental study on solidification of Cu(II)-contaminated soil using red mud with cement and Ca(OH)2
  14. Tribological study of sintered iron based and copper based brake materials by pin-on-disc method
  15. Influence of drilling parameters on temperature and surface roughness of AISI O2 steel
  16. Multi-fractal characteristics of particle size distribution of granular backfilling materials under different loads
  17. Dry sliding behavior of aluminum alloy 8011 with 4 % fly ash
  18. Optimization of the milling parameters for an Al/Si3N4 functionally graded composite using grey relational analysis
Downloaded on 13.4.2026 from https://www.degruyterbrill.com/document/doi/10.3139/120.111128/html
Scroll to top button