Design optimization of a three-stage transmission using advanced optimization techniques

被引:8
作者
Maputi E.S. [1 ]
Arora R. [2 ]
机构
[1] Department of Industrial and Manufacturing Engineering, Harare Institute of Technology, Belvedere, Harare
[2] Department of Mechanical Engineering, Amity University Haryana, Gurgaon
关键词
Design preferences; Gear; Optimal design; Optimization;
D O I
10.1051/smdo/2019009
中图分类号
学科分类号
摘要
Gear transmission systems are very important machine elements and their failure can lead to losses or damage of other mechanical components that comprise a machine or device. Since gears are applied in numerous mechanical devices, there is need to design and subsequently optimize them for intended use. In the present work, two objectives, viz., volume and center distance, are minimized for a rotary tiller to achieve a compact design. Two methods were applied: (1) analytical method, (2) a concatenation of the bounded objective function method and teaching-learning-based optimization techniques, thereby improving the result by 44% for the former and 55% for the latter. Using a geometric model and previous literature, the optimal results obtained were validated with 0.01 variation. The influence of design variables on the objective functions was also evaluated using variation studies reflecting on a ranking according to objective. Bending stress variation of 12.4% was less than contact stress at 51% for a defined stress range. © E.S. Maputi and R. Arora, published by EDP Sciences, 2019.
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共 39 条
[1]  
Osyczka A., An approach to multicriterion optimization problems for engineering design, Comput. Methods Appl. Mech. Eng., 15, pp. 309-333, (1978)
[2]  
Tong B.S., Walton D., The optimisation of internal gears, Int. J. Mach. Tools Manuf., 27, pp. 491-504, (1987)
[3]  
Prayoonrat S., Walton D., Practical approach to optimum gear train design, Comput. Des., 20, pp. 83-92, (1988)
[4]  
Deb K., Pratap A., Agarwal S., Meyarivan T., A fast and elitist multiobjective genetic algorithm: NSGA-II, IEEE Trans. Evol. Comput., 6, pp. 182-197, (2002)
[5]  
Rao R.V., Teaching Learning Based Optimization Algorithm, (2016)
[6]  
Yokota T., Taguchi T., Gen M., A solution method for optimal weight design problem of the gear using genetic algorithms, Comput. Ind. Eng., 35, pp. 523-526, (1998)
[7]  
Savsani V., Rao R.V., Vakharia D.P., Optimal weight design of a gear train using particle swarm optimization and simulated annealing algorithms, Mech. Mach. Theory, 45, pp. 531-541, (2010)
[8]  
Golabi S., Fesharaki J.J., Yazdipoor M., Gear train optimization based on minimum volume/weight design, Mech. Mach. Theory, 73, pp. 197-217, (2014)
[9]  
Das D., Bhattacharya S., Sarkar B., Decision-based designdriven material selection: A normative-prescriptive approach for simultaneous selection of material and geometric variables in gear design, J. Materials Design, 92, pp. 787-793, (2016)
[10]  
Kostic N., Marjanovic N., Petrovic N., A novel approach for solving gear train optimization, Int. J. Veh. Mech. Eng. Transp. Syst., 42, pp. 67-76, (2016)