IJSRD - International Journal for Scientific Research & Development| Vol. 3, Issue 03, 2015 | ISSN (online): 2321-0613 All rights reserved by www.ijsrd.com 600 Optimization of Strength/Weight Ratio for Three Stage Helical Gear Train B. T. Vastarpara 1 R. G. Jivani 2 V.A. Pandya 3 R.C. Sanghvi 4 1 M.E Scholar 2,3 Department of Mechanical Engineering 4 Department of Mathematics Department 1,2,3 BVM Engineering College, Vallabh Vidhyanagar, India 4 GCET, Vallabh Vidhyanagar, India Abstract— Gear train is important part of the majority of mechanical power transmission system. It has to be robust enough to sustain the transmitted power over the long period of time and also light enough to reduce the overall weight of the system. But since to increase the power to be transmitted by the gear train also causes increase in weight and vice versa, these two objectives rather generate contradicting solutions. Thus, the optimization of gear becomes very significant in order to have a good trade-off between these two entities. The helical gear provides a smoother mesh and can be operated at greater speeds than a straight spur gear. So we have to minimize weight of helical gear train to increase strength/weight ratio. Key words: AGMA, Strength/Weight Ratio I. INTRODUCTION Various applications of gear trains are mechanical power transmission systems such as automobile, aerospace, machine tools and gear design is still an ongoing activity. However, design optimization for a complete mechanical assembly leads to a complicated objective function with a large number of design variables. So it is a good practice to apply optimization techniques for individual components or intermediate assemblies than a complete assembly. For example, in an automobile power transmission system, optimization of gearbox is computationally and mathematically simpler than the optimization of complete system. In recent times the gear design has become a highly complicated and comprehensive subject. A designer of a modern gear drive system must remember that the main objective of a gear drive is to transmit power with comparatively smaller over all dimensions of driving system. The preliminary design optimization of three stage helical gear reduction units has been a subject of considerable interest. Complex shape and geometry of gears lead to a large number of design parameters. A traditional gear design involves computations based on tooth bending strength, tooth surface durability, tooth surface fatigue, interference, efficiency, etc. Gear design involves empirical formulas, different graphs and tables, which lead to a complicated design. Manual design is very difficult considering above facts and there is a need for the computer aided design of gears. With the aid of computer, design can be carried out iteratively and the design variables which satisfy the given conditions can be determined. The design so obtained may not be the optimum one, because in the above process the design variables so obtained satisfy only one condition at a time e.g., if module is calculated based on bending strength, the same module is substituted to calculate the surface durability. It is accepted if it is within the strength limit of surface durability; otherwise it is changed accordingly. So optimization methods are required to determine design variables which simultaneously satisfy the given conditions II. METHODOLOGY Existing design of three stage gearbox is further optimized by Genetic algorithm & resultant weight of both design are compared & found reduction in overall system. The optimization problem involves the objective function and constraints that are not stated as explicit functions of the design variables, it is hard to solve by classical optimization methods. Moreover, increasing demand for compact, efficient, and reliable gears forces the designer to use optimal design methodology. We have to focus on the optimization of a three stage helical gear-train wherein minimization of weight considered as the objective function. The decision variables considered in this study are Face Width, module & No. of teeth of Gears. The gear-train system is subjected to constraints such as Bending Strength, wear strength, Min. No. of teeth, center distance & one more additional constraint for avoiding collision is considered. In this research we used equations for calculating various dimensions of gear and tooth bending stress & contact stress from AGMA standards. Various results from these calculations are compared with optimized parameter’s results & we make the Creo Parametric 2.0 models for showing that there is no interface between gears. For optimization we used Genetic Algorithms from matlab-13 optimization tool, GA gives solution very closer to the global solution of the function. Genetic Algorithm is an evolutionary process inspired by the biological evolution process. GAs use the evolutionary cycle as shown in fig-1 a typical genetic algorithm requires: a genetic representation of the solution domain and fitness function to evaluate the solution domain. (It’s our objective function) Fig. 1: The Evolutionary Cycle