References
- T. A. Harris, Rolling Bearing Analysis. New York: John Wiley and Sons, 2001.
- W.Changsen, Analysis of Rolling Element Bearings. London: Mechanical Engineering Pubs. Ltd., 1991.
- K. Deb, Optimization for Engineering Design: Algorithms and Examples. New Delhi: PHI Learning Pvt. Ltd., 2012.
- D. E. Goldberg, Genetic Algorithms in Search, Optimization and Machine Learning. Boston, USA: Addison-Wesley Longman Publishing Company, 1989.
- I. Chakraborty, V. Kumar, S. B. Nair, and R. Tiwari, “Rolling element bearing design through genetic algorithms,” Eng. Optim., vol. 35, no. 6, pp. 649–659, 2003. DOI: https://doi.org/10.1080/03052150310001624403.
- B. Rajeswara Rao and R. Tiwari, “Optimum design of rolling element bearings using genetic algorithms,” Mech. Mach. Theory, vol. 42, no. 2, pp. 233–250, 2007. DOI: https://doi.org/10.1016/j.mechmachtheory.2006.02.004.
- S. Gupta, R. Tiwari, and S. B. Nair, “Multi-objective design optimisation of rolling bearings using genetic algorithms,” Mechanism Mach. Theory, vol. 42, no. 10, pp. 1418–1443, 2007. DOI: https://doi.org/10.1016/j.mechmachtheory.2006.10.002.
- S. Panda, S. N. Panda, P. Nanda, and D. Mishra, “Comparative study on optimum design of rolling element bearing,” Tribology Int., vol. 92, pp. 595–604, 2015. DOI: https://doi.org/10.1016/j.triboint.2015.07.034.
- K. S. Kumar, R. Tiwari, and P. V. V. N. Prasad, “An optimum design of crowned cylindrical roller bearings using genetic algorithms,” J. Mech. Design, vol. 131, no. 5, pp. 051011, 2009. DOI: https://doi.org/10.1115/1.3116344.
- R. Tiwari, K. K. Sunil, and R. S. Reddy, “An optimal design methodology of tapered roller bearings using genetic algorithms,” Int. J. Comput. Methods Eng. Sci. Mech., vol. 13, no. 2, pp. 108–127, 2012. DOI: https://doi.org/10.1080/15502287.2011.654375.
- R. Tiwari and R. M. P. Chandran, “Multitude of objectives based optimum designs of cylindrical roller bearings with evolutionary methods,” J. Tribol., vol. 137, no. 4, pp. 041504, 2015. DOI: https://doi.org/10.1115/1.4030166.
- M. Kalyan and R. Tiwari, “Multi-objective optimization of needle roller bearings based on fatigue and wear using evolutionary algorithm,” Proc. Inst. Mech. Eng. Part J: J. Eng. Tribol., vol. 230, no. 2, pp. 170–185, 2016. DOI: https://doi.org/10.1177/1350650115594639.
- V. Waghole and R. Tiwari, “Optimization of needle roller bearing design using novel hybrid methods,” Mech. Mach. Theory, vol. 72, pp. 71–85, 2014. DOI: https://doi.org/10.1016/j.mechmachtheory.2013.10.001.
- R. Tiwari and V. Waghole, “Optimization of spherical roller bearing design using artificial bee colony algorithm and grid search method,” Int. J. Comput. Methods Eng. Sci. Mech., vol. 16, no. 4, pp. 221–233, 2015. DOI: https://doi.org/10.1080/15502287.2015.1045998.
- A. Jat and R. Tiwari, “Multi-objective optimization of spherical roller bearings based on fatigue and wear using evolutionary algorithm,” J. King Saud Univ. Eng. Sci., vol. 32, no. 1, pp. 58–68, 2020. DOI: https://doi.org/10.1016/j.jksues.2018.03.002.
- R. D. Dandagwhal and V. D. Kalyankar, “Design optimization of rolling element bearings using advanced optimization technique,” Arab. J. Sci. Eng., vol. 44, no. 9, pp. 7407–7422, 2019. DOI: https://doi.org/10.1007/s13369-019-03767-0.
- H. B. Shaikh and A. G. Kamble, “Optimization of dynamic load carrying capacity of deep groove ball bearing using Jaya algorithm,” International Conference on Advances in Thermal Systems, Materials and Design Engineering (ATSMDE2017), Dec. 21, 2017. Sinhgad Institute of Technology, Lonavala, University of Pune, India.
- A. Solanki, P. Patel, and B. Parmar, “Design formulation and optimum load carrying capacity of hydrodynamic journal bearing by using genetic algorithm,” Int. J. Res. Appl. Sci. Eng. Technol. (IJRASET), vol. 2, pp. 132–138, 2014.
- V. K. Dewangan and L. Rajput, “Design optimization of plain journal bearing to minimize the power loss using genetic algorithm,” Int. J. Res. Appl. Sci. Eng. Technol. (IJRASET), vol. 4, pp. 687–693, 2016.
- H. Saruhan, K. Rouch, and C. Roso, “Design optimization of tilting-pad journal bearing using a genetic algorithm,” Int. J. Rotating Machinery, vol. 10, no. 4, pp. 301–307, 2004. DOI: https://doi.org/10.1155/S1023621X04000314.
- S. W. Kim, K. Kang, K. Yoon, and D. H. Choi, “Design optimization of an angular contact ball bearing for the main shaft of a grinder,” Mechanism Mach. Theory, vol. 104, pp. 287–302, 2016. DOI: https://doi.org/10.1016/j.mechmachtheory.2016.06.006.
- R. Lostado-Lorza, R. Escribano-Garcia, R. Fernandez-Martinez, M. Illera-Cueva, and B. J. Mac Donald, “Using the finite element method and data mining techniques as an alternative method to determine the maximum load capacity in tapered roller bearings,” J. Appl. Logic, vol. 24, pp. 4–14, 2017. DOI: https://doi.org/10.1016/j.jal.2016.11.009.
- A. S. Reddy, P. K.Agarwal, and S. Chand, “An adaptive multipopulation genetic algorithm for the optimization of active magnetic bearings,” IOP Conf. Ser.: Mater. Sci. Eng., vol. 691, no. 1, pp. 012009, 2019. DOI: https://doi.org/10.1088/1757-899X/691/1/012009.
- A. Messac and A. Ismail-Yahaya, “Multiobjective robust design using physical programming,” Struct. Multidisc. Optim., vol. 23, no. 5, pp. 357–371, 2002. DOI: https://doi.org/10.1007/s00158-002-0196-0.
- W. Chen, A. Sahai, A. Messac, and G. J. Sundararaj, “Exploration of the effectiveness of physical programming in robust design,” ASME J. Mech. Des., vol. 122, no. 2, pp. 155–163, 2000. DOI: https://doi.org/10.1115/1.533565.
- A. Giassi, F. Bennis, and J. J. Maisonneuve, “Multidisciplinary design optimisation and robust design approaches applied to concurrent design,” Struct Multidisc. Optim., vol. 28, no. 5, pp. 356–371, 2004. DOI: https://doi.org/10.1007/s00158-004-0417-9.
- C. Zang, M. I. Friswell, and J. E. Mottershead, “A review of robust optimal design and its application in dynamics,” Comput. Struct., vol. 83, no. 4–5, pp. 315–326, 2005. DOI: https://doi.org/10.1016/j.compstruc.2004.10.007.
- G. Emch and A. Parkinson, “Robust optimal design for worst case tolerances,” J. Mech. Des., vol. 116, no. 4, pp. 1019–1025, 1994. DOI: https://doi.org/10.1115/1.2919482.
- K. Kang, S. W. Kim, K. Yoon, and D. H. Choi, “Robust design optimization of an angular contact ball bearing under manufacturing tolerance,” Struct. Multidisc. Optim., vol. 60, no. 4, pp. 1645–1665, 2019. DOI: https://doi.org/10.1007/s00158-019-02335-2.
- E. Guenat and J. Schiffmann, “Multi-objective optimization of grooved gas journal bearings for robustness in manufacturing tolerances,” Tribol. Trans., vol. 62, no. 6, pp. 1041–1050, 2019. DOI: https://doi.org/10.1080/10402004.2019.1642547.
- S. K. Verma and R. Tiwari, “Robust optimum design of tapered roller bearings based on maximization of fatigue life using evolutionary algorithm,” Mech. Mach. Theory, vol. 152, pp. 103894, 2020. DOI: https://doi.org/10.1016/j.mechmachtheory.2020.103894.
- B. J. Hamrock and D. Brewe, “Simplified solution for stresses and deformations,” J. Lubrication Technol., vol. 105, no. 2, pp. 171–177, 1983. DOI: https://doi.org/10.1115/1.3254558.
- D. Data, Databook of Engineers, Compiled by PSG College of Technology Coimbatore, Coimbatore: Kalaikathir Achchagam Coimbatore, 1968.
- F. Herrera, M. Lozano, and J. L. Verdegay, “Tackling real-coded genetic algorithms: Operators and tools for behavioural analysis,” Artificial Intell. Rev., vol. 12, no. 4, pp. 265–319, 1998. DOI: https://doi.org/10.1023/A:1006504901164.
- J. Nocedal and S. J. Wright, Numerical Optimization, New York, NY: Springer Series in Operations Research, Springer Verlag, 2006.