AN OPTIMUM DRILL BIT SELECTION TECHNIQUE USING ARTIFICIAL NEURAL NETWORKS AND GENETIC ALGORITHMS TO INCREASE THE RATE OF PENETRATION

AN OPTIMUM DRILL BIT SELECTION TECHNIQUE USING ARTIFICIAL NEURAL NETWORKS AND GENETIC ALGORITHMS TO INCREASE THE RATE OF PENETRATION

Drill bit is the most essential tool in drilling and drill bit selection plays a significant role in drilling process planning. This paper discusses bit selection by employing a method of combining Artificial Neural Network (ANN) and the computation of Genetic Algorithm (GA). In this method, offset...

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Bibliographic Details
Main Authors: MOHAMMADSADEGH MOMENI, SEYED JAVAD HOSSEINI, SYAHRIR RIDHA, MOACYR BARTHOLOMEU LARUCCIA, XIANHUA LIU
Format: Article
Language:English
Published: Taylor's University 2018-02-01
Series:Journal of Engineering Science and Technology
Subjects:
Artificial Neural Network
Bit Selection
Genetic Algorithm
Mean Squared Error
Drilling Data Optimization
Online Access:http://jestec.taylors.edu.my/Vol%2013%20issue%202%20February%202018/13_2_6.pdf

Internet

http://jestec.taylors.edu.my/Vol%2013%20issue%202%20February%202018/13_2_6.pdf

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