Abstract
The selection of parameters in grinding process remains as a crucial role to guarantee that the machined product quality is at the minimum production cost and maximum production rate. Therefore, it is required to utilize more advance and effective optimization methods to obtain the optimum parameters and resulting an improvement on the grinding performance. In this paper, three optimization algorithms which are particle swarm optimization (PSO), gravitational search, and Sine Cosine algorithms are employed to optimize the grinding process parameters that may either reduce the cost, increase the productivity or obtain the finest surface finish and resulting a higher grinding process performance. The efficiency of the three algorithms are evaluated and comparedwith previous results obtained by other optimization methods on similar studies.The experimental results showed that PSO algorithm achieves better optimization performance in the aspect of convergence rate and accuracy of best solution.Whereas in the comparison of results of previous researchers, the obtained result of PSO proves that it is efficient in solving the complicated mathematical model of surface grinding process with different conditions.
Highlights
Grinding process remains as an important conventional machining process that is performed on various kind of surfaces for the shaping and finishing purpose in order to manufacture precision finished products [1]
The best solution obtained by particle swarm optimization (PSO) in this paper shows an improvement of results when compared with the previous research paper that presented by Pawar and Rao (2013) which may influenced by using different value of the parameters and optimzation problem is achieved by the average best solution of 50 independent runs which resulting a more accurate and better results
An experiment had conducted to evaluate the efficiency of these proposed algorithms as well as obtain results that are more reliable According to the obtained results from the experiment, it can be observed that PSO algorithm shows superior results when compared to the proposed gravitational search (GSA) and Sine and Cosine Algorithm (SCA)
Summary
Grinding process remains as an important conventional machining process that is performed on various kind of surfaces for the shaping and finishing purpose in order to manufacture precision finished products [1]. By reviewing the previous works with different methods, it can be seen that many researchers have conducted the optimization of grinding process using combinedobjective functions as one single-objective problem to optimize the process parameters [2, 4,5,6,7,8,9,10]. ISSN: 2302-9285 because these optimization methods are having difficulties to expand to real multi objective problems since they are not introduced to solve the multiple ideal solutions These optimization methods are lacking from the drawback that the decision maker needs to have detailed information to make decision on the ranking of the objective functions. The findings of this study are analyzed and discussed to suggest the most efficient algorithm for grinding process problem
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