NDLI: Genetic Algorithm and Simulated Annealing to estimate optimal process parameters of the abrasive waterjet machining

Content Provider	Springer Nature Link
Author	Zain, Azlan Mohd Haron, Habibollah Sharif, Safian
Copyright Year	2010
Abstract	In this study, two computational approaches, Genetic Algorithm and Simulated Annealing, are applied to search for a set of optimal process parameters value that leads to the minimum value of machining performance. The objectives of the applied techniques are: (1) to estimate the minimum value of the machining performance compared to the machining performance value of the experimental data and regression modeling, (2) to estimate the optimal process parameters values that has to be within the range of the minimum and maximum coded values for process parameters of experimental design that are used for experimental trial and (3) to evaluate the number of iteration generated by the computational approaches that lead to the minimum value of machining performance. Set of the machining process parameters and machining performance considered in this work deal with the real experimental data of the non-conventional machining operation, abrasive waterjet. The results of this study showed that both of the computational approaches managed to estimate the optimal process parameters, leading to the minimum value of machining performance when compared to the result of real experimental data.
Starting Page	251
Ending Page	259
Page Count	9
File Format	PDF
ISSN	01770667
Journal	Engineering with Computers
Volume Number	27
Issue Number	3
e-ISSN	14355663
Language	English
Publisher	Springer-Verlag
Publisher Date	2010-07-25
Publisher Place	London
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Optimization Optimal process parameters Minimum machining performance Computer-Aided Engineering (CAD, CAE) and Design Math. Applications in Chemistry Systems Theory, Control Mechanics Calculus of Variations and Optimal Control; Optimization ApplicationMathematics/Computational Methods of Engineering
Content Type	Text
Resource Type	Article
Subject	Engineering Computer Science Applications Modeling and Simulation Software

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