Optimization of production time in the multi-pass milling process via a Robust Grey Wolf Optimizer

In order to optimize multi-pass milling process, selection of optimal values for the parameters of the process is of great importance. The mathematical model for optimization of multi-pass milling process is a multi-constrained nonlinear programing formulation which is hard to be solved. Therefore, a novel robust meta-heuristic algorithm named Robust Grey Wolf Optimizer (RGWO) is proposed. In order to develop a RGWO, a robust design methodology named Taguchi method is utilized to tune the parameters of the algorithm. Therefore, in contradiction to previous researches, there is no need to design costly experiments to obtain the optimal values of the parameters of the GWO. In addition, an efficient constraint handling approach is implemented to handle complex constraints of the problem. A real-world problem is adopted to show the effectiveness and efficiency of the proposed RGWO in optimizing the milling process within different strategies. The results indicated that the RGWO outperforms the other solution methods in the literature as well as two novel meta-heuristic algorithms by obtaining better and feasible solutions for all cutting strategies.

     

Investigation of the effects of alumina nanoparticles on spur gear surface roughness and hob tool wear in hobbing process

Hobbing process is one of the machining methods in manufacturing spur gears. In machining processes, selecting a suitable lubricant is one of the significant factors in enhancing machining productivity and improving the characteristics of manufactured workpieces. This study has used the nanolubricant including alumina nanoparticles dispersed in mineral-based oil 25W-50 in hobbing process. Then, hobbing process using the lubricant including both nanoparticles, and none has been done utilizing with the similar hob tools. Two spur gears with DIN1.7131 material have been manufactured using each of two lubricants. Then, the hob tool wear and surface roughness values of manufactured spur gears were investigated. Comparing the results show that using lubricant including alumina nanoparticles in hobbing process causes an expressive decrease in the hob tool crater and flank wear. Also, arithmetic surface roughness value in spur gears manufactured with nanolubricant has decreased.     

Design and manufacturing of a straight bevel gear in hot precision forging process using finite volume method and CAD/CAE technology

Forging simulation offers significant cost and time advantages by providing detailed insight into the forging process before tool selection and process decisions are made on the shop floor. Process data such as material flow, stresses, strains and temperature are readily accessible to a user at any point throughout the simulation process, as well as at any location within the forged part. Potential defects such as laps and under-fill of die cavities can be easily identified and corrected before part production begins. In addition, the influence of the process conditions such as lubrication and pre-form can be easily quantified and assessed. In the present work, hot precision forging process of the straight bevel gear is simulated numerically using finite volume method and computer-aided design/computer-aided engineering technology. The required force for the forging process, as well as the final shape of the bevel gear, is determined through numerical estimation. The simulation results are confirmed through the comparison with the experimental data available in DIN standards. Finally, the pre-form dies, the final die, and the bevel gear are manufactured. It is concluded that this method can be effectively used to optimize the forging process to maximize the mechanical strength, minimize material scrap, and hence reduce the overall cost of manufacture.