Authors: S. Saravana Sankar, S.G. Ponnambalam
Addresses: School of Mechanical Engineering, Kalasalingam University, Anand Nagar, Krishnan koil-626 190, India. ' School of Engineering, Monash University, 46150, Petaling jaya, Selangor, Malaysia
Abstract: With the advent of more and more sophisticated technologies it is very imperative now to focus on the overall economy of the manufacturing process and evolve methods to optimise the machining operations even at the micro level. In this work, a model for optimising machining conditions such as speed and feed, for minimum production cost of a spur gear has been developed and a simulated annealing algorithm (SAA) based heuristic procedure referred to as aggravated simulated annealing algorithm (AGSAA) is developed. The proposed methodology possesses a unique mechanism to augment the explorative and exploitative capabilities of the SAA during the search process. The performance of the proposed AGSAA is also compared with that of a normal SAA methodology and that of another optimisation technique namely kangaroo algorithm (KA), found in the literature. The results show that AGSAA is outperforming both methodologies for the problem considered in this work.
Keywords: gear milling; machining optimisation; aggravated SAA; simulated annealing algorithm; kangaroo algorithm; spur gears.
International Journal of Advanced Mechatronic Systems, 2008 Vol.1 No.1, pp.53 - 62
Published online: 17 Oct 2008 *Full-text access for editors Access for subscribers Purchase this article Comment on this article