Process Design for Milling Operation of Titanium Alloy (Ti6Al4V) Using Artificial Neural Network.
Daniyan, Ilesanmi Afolabi Mpofu, Khumbulani Tlhabadira, Isaac Ramatsetse, Boitumelo Innocent
Daniyan, Ilesanmi Afolabi
Mpofu, Khumbulani
Tlhabadira, Isaac
Ramatsetse, Boitumelo Innocent
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Abstract
Titanium alloy is characterized with excellent mechanical properties such as lightweight, and good corrosion resistance ability, hence, it finds application in many industrial and engineering applications. This study considers the process design of the milling operation of titanium alloy using artificial intelligence. The numerical experimentation involves the use of the Artificial Neural Network (ANN) back propagation and Levenberg Marquardt algorithm for the correlation of the process parameters while the physical experiments were investigated using a DMU80monoBLOCK Deckel Maho 5-axis CNC milling machine and carbide-cutting inserts of 12 and 14 mm (RCKT1204MO-PM S40T) under the cooling and dry
machining conditions. The developed network was used to obtain a regression analysis which is suitable for the prediction of the feasible range of the process parameters. The results obtained from the physical experiments indicate
significant reduction in the rate of tool wear under the cooling conditions as opposed to the dry machining. The findings of this work will find suitable application as a decision making tool in the manufacturing industries most
especially the manufacturing industries, which employs titanium alloy for component part development.
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Date
2021-08-21
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Publisher
JMIR Publications
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Keywords
Artificial Neural Network (ANN), Milling operation, Process design,, Process parameters, Titanium alloy