Parametric optimization of ultrasonic machining process using gravitational search and fireworks algorithms

Abstract

Ultrasonic machining (USM) is a mechanical material removal process used to erode holes and cavities in hard or brittle workpieces by using shaped tools, high-frequency mechanical motion and an abrasive slurry. Unlike other non-traditional machining processes, such as laser beam and electrical discharge machining, USM process does not thermally damage the workpiece or introduce significant levels of residual stress, which is important for survival of materials in service. For having enhanced machining performance and better machined job characteristics, it is often required to determine the optimal control parameter settings of an USM process. The earlier mathematical approaches for parametric optimization of USM processes have mostly yielded near optimal or sub-optimal solutions. In this paper, two almost unexplored nonconventional optimization techniques, i.e. gravitational search algorithm (GSA) and fireworks algorithm (FWA) are applied for parametric optimization of USM processes. The optimization performance of these two algorithms is compared with that of other popular population-based algorithms, and the effects of their algorithm parameters on the derived optimal solutions and computational speed are also investigated. It is observed that FWA provides the best optimal results for the considered USM processes. Ó 2014 Faculty of Engineering, Ain Shams University. Production and hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).

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“…[41][42][43] The global solution corresponds the position of the most massive agent with a high tendency of attracting agents of lower masses. [44][45][46] Supposing a search space containing kth agent in d-dimension, it is defined by Equation (9):…”

Phase partition and identification based on kernel entropy component analysis and multi-class support vector machines-fireworks algorithm for multi-phase batch process fault diagnosis

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“…Based on the results, WSN method and UT method usually give better and comparable results for USM process compared to the others. Goswami and Chakraborty (2014) introduced gravitational search algorithm (GSA) and fireworks algorithm (FWA) for the parametric optimisation of USM processes. The effects of the algorithm parameters on the optimal solutions are investigated and a comparison between the two suggested algorithm and other population based algorithms has been carried out.…”