Optimization of Gear Manufacturing for Quality and Productivity

Main Article Content

TC Phokane
Kapil Gupta
Cristina Anghel


Fuzzy, Gear Manufacturing, Optimization, Productivity, Quality


Multi-objective optimization in manufacturing can effectively be solved using Multicriteria decision-making (MCDM) techniques. This paper presents the implementation methodology of the Fuzzy-MOORA hybrid technique for multi-objective optimization in laser machining of stainless-steel gears. Further, simultaneous optimization of gear quality and process productivity have been reported. Four important laser parameters, i.e., laser power, cutting speed, focal position, and gas pressure, have varied during twenty-nine experiments to machine gears by a laser process. The quality of miniature gear was measured in terms of average surface roughness, mean roughness depth, and dimensional deviation. The productivity of the laser machining process was estimated via material removal rate. An optimum set of laser machining parameters obtained after Fuzzy-MOORA optimization is laser power 2000 W, cutting speed 3 m/min, focal position -2.5 mm, and gas pressure 16 bar. This work encourages researchers and scholars to make further attempts using such MCDM techniques to develop intelligent processes in industrial and manufacturing engineering.


Download data is not yet available.


[1] P. Agarwal, L. Bajpai, C.P. Singh, K. Gupta, J. P. Davim, “Manufacturing and Industrial Engineering: Theoretical and Advanced Technologies”, CRC Press, 2021.

[2] J.R Davis, “Gear Materials, Properties, and Manufacture”, ASM International: Materials Park, OH, 2005.

[3] C. Anghel, K. Gupta, T.C. Jen, “Analysis and Optimization of Surface Quality of Stainless Steel Miniature Gears Manufactured by CO2 Laser Cutting,” Opt. - Int. J. Light Electron Opt., vol. 203, no. 164049, 2020.

[4] C. Anghel, “Investigation on Manufacturing of Miniature Gears by Laser Beam Cutting,” PhD Thesis Univ. Johannesbg., 2020.

[5] N.A. Zolpakar, M.F. Yasak, S. Pathak, “A review: use of evolutionary algorithm for optimisation of machining parameters,” Int. J. Adv. Manuf. Technol., vol. 115, pp. 31–47, 2021

[6] K. Gupta and N.K. Jain, “Near Net Shape Manufacturing of Miniature Spur Gears by Wire Spark Erosion Machining”, Springer, 2016.

[7] C. Anghel, K. Gupta, T. C. Jen, “Optimization of laser machining parameters and surface integrity analysis of the fabricated miniature gears,” Procedia Manuf., vol. 51, no. 2019, pp. 878–884, 2020, doi: 10.1016/j.promfg.2020.10.123.

[8] T.C. Phokane, K. Gupta, M.K. Gupta, “Investigations on Surface Roughness and Tribology of Miniature Brass Gears Manufactured by Abrasive Water Jet Machining,” Proc. IMechE, Part C J. Mech. Eng. Sci., vol. 232, no. 22, pp. 4193–4202, 2018.

[9] W.K.M. Brauers and E.K. Zavadskas, “The MOORA method and its application to privatization in a transition economy,” Control Cybern, vol. 35, no. 2, pp. 445–469, 2006.

[10] P. Karande and S. Chakraborty, “Application of multi-objective optimization on the basis of ratio analysis (MOORA) method for materials selection,” Mater. Des., vol. 37, pp. 317–324, 2012, doi: 10.1016/j.matdes.2012.01.013.

[11] Y. I. Tansel and S. Yldrm, “MOORA-based Taguchi optimisation for improving product or process quality,” Int. J. Prod. Res., vol. 51, no. 11, pp. 3321–3341, 2013, doi: 10.1080/00207543.2013.774471.

[12] V. S. Gadakh, V. B. Shinde, and N. S. Khemnar, “Optimization of welding process parameters using MOORA method,” Int. J. Adv. Manuf. Technol., vol. 69, no. 9–12, pp. 2031–2039, 2013, doi: 10.1007/s00170-013-5188-2.

[13] Z. Siddiqui, K. Tyagi, “Application of fuzzy-MOORA method: Ranking of components for reliability estimation of component-based software systems”, Decision Science Letters, Vol. 5, no. 1, pp. 169-188, 2016.

[14] L.B. Abhang, M. Iqbal, M. Hameedullah, “Optimization of Machining Process Parameters Using Moora Method”, Defect and Diffusion Forum, vo. 402, pp. 81–89, 2020.

[15] M. Kiyak, B. Kaner, I. Sahin, B. Aldemir, O. Cakir, “The dependence of tool overhang on surface quality and tool wear in the turning process,” Int. J. Adv. Manuf. Technol, vol. 51, no. 5–8, pp. 431–438, 2010.