Journal of Rubber Research

, Volume 22, Issue 4, pp 187–193 | Cite as

Optimisation of elastomeric bearings’ vulcanisation process using response surface methodology and desirability function approach

  • Ali İhsan BoyacıEmail author
  • Kasım Baynal
Original Paper


In this study, response surface methodology and desirability function approach (DFA) were used to optimise the vulcanisation process of elastomeric bearings to obtain better quality products. For this purpose, compressive stiffness and vertical deflection under maximum load were determined as response variables with a target at 198 kN/mm and 3.46 mm, respectively, in accordance with customer’s request. Time, temperature and pressure were considered as control variables of the process. Experimental combinations were determined using Box–Behnken design and two repetitions were made in each combination. The experimental design was randomised for removing bias and other uncontrollable sources of extraneous variation. As a result of the statistical analysis, linear, quadratic, and interaction effects of factors on response variables were obtained. For simultaneous optimisation of multiple responses, the DFA was used and optimum factor levels were obtained. Finally, the optimum conditions were verified by confirmation experiments.


Elastomeric bearing Vulcanisation process Response surface methodology Box–Behnken design Desirability function approach 


Compliance with ethical standards

Conflict of interest

The authors have no conflict of interest.


  1. 1.
    Ulu KN, Huneau B, Verron E, Béranger AS, Heuillet P (2017) True stress controlled fatigue life experiments for elastomers. Int J Fatigue 104:171–182. CrossRefGoogle Scholar
  2. 2.
    Nıgız FU, Unlu D, Hilmioglu N (2017) Carbon black loaded composite poly (dimethyl siloxane) membrane preparation and application for hazardous chemical removal from water. Acta Phys Pol A 132:693–696. CrossRefGoogle Scholar
  3. 3.
    Syed MB, Patisson L, Curtido M, Slee B, Diaz S (2014) The challenging requirements of the ITER anti seismic bearings. Nucl Eng Des 269:212–216. CrossRefGoogle Scholar
  4. 4.
    Osgooei PM, Konstantinidis D, Tait MJ (2016) Variation of the vertical stiffness of strip-shaped fiber-reinforced elastomeric isolators under lateral loading. Compos Struct 144:177–184. CrossRefGoogle Scholar
  5. 5.
    Tsai HC (2006) Compression stiffness of circular bearings of laminated elastic material interleaving with flexible reinforcements. Int J Solids Struct 43:3484–3497. CrossRefGoogle Scholar
  6. 6.
    EN 1337-3 (2005) Structural bearing part 3—elastomeric bearings. Association Francaise de Normalisation (AFNOR—French Standard Institute), FranceGoogle Scholar
  7. 7.
    Nasir M, Teh GK (1988) The effects of various types of crosslinks on the physical properties of natural rubber. Eur Polym J 24(8):733–736. CrossRefGoogle Scholar
  8. 8.
    Zaimova D, Bayraktar E, Miskioglu I (2016) Design and manufacturing of new elastomeric composites: mechanical properties, chemical and physical analysis. Compos B Eng 105:203–210. CrossRefGoogle Scholar
  9. 9.
    Flory PJ, Rabjohn N, Shaffer MC (1949) Dependence of elastic properties of vulcanized rubber on the degree of cross linking. J Polym Sci Banner 4(3):225–245. CrossRefGoogle Scholar
  10. 10.
    Yavari S, Malakahmad A, Sapari NB, Yavari S (2017) Sorption properties optimization of agricultural wastes-derived biochars using response surface methodology. Process Saf Environ Prot 109:509–519. CrossRefGoogle Scholar
  11. 11.
    Tang X, Luo J, Liu F (2017) Aerodynamic shape optimization of a transonic fan by an adjoint-response surface method. Aerosp Sci Technol 68:26–36. CrossRefGoogle Scholar
  12. 12.
    Tiryaki AE, Kozan R, Adar NG (2015) Prediction of sheet drawing characteristics with square drawbead elements using response surface methodology. Acta Phys Pol A 128:344–347. CrossRefGoogle Scholar
  13. 13.
    Boyaci AI, Hatipoğlu T, Balci E (2017) Drilling process optimization by using fuzzy-based multi-response surface methodology. Adv Prod Eng Manag 12:163–172. CrossRefGoogle Scholar
  14. 14.
    Özsoy N, Özsoy M, Mimaroğlu A (2017) Taguchi approach to tribological behaviour of chopped carbon fiber-reinforced epoxy composite materials. Acta Phys Pol A 132:846–848. CrossRefGoogle Scholar
  15. 15.
    Assarzadeh S, Ghoreishi M (2015) Mathematical modeling and optimization of the electro-discharge machining (EDM) parameters on tungsten carbide composite: combining response surface methodology and desirability function technique. Sci Iran B 22(2):539–560Google Scholar
  16. 16.
    Derringer G, Suich R (1980) Simultaneous optimization of several response variables. J Qual Technol 12:214–219CrossRefGoogle Scholar
  17. 17.
    Salmasnia A, Ameri E, Ghorbanian A, Mokhtari H (2017) A multi-objective multi-state degraded system to optimize maintenance/repair costs and system availability. Sci Iran 24(1):355–363. CrossRefGoogle Scholar
  18. 18.
    Costa NR, Lourenço J, Pereira ZL (2011) Desirability function approach: a review and performance evaluation in adverse conditions. Chemom Intell Lab Syst 107:234–244. CrossRefGoogle Scholar

Copyright information

© The Malaysian Rubber Board 2019

Authors and Affiliations

  1. 1.Industrial Engineering DepartmentKocaeli UniversityKocaeliTurkey
  2. 2.Management DepartmentKyrgyz-Turkish Manas UniversityBishkekKyrgyzstan

Personalised recommendations