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#7008. Process Design for Milling Operation of Titanium Alloy (Ti6Al4V) Using Artificial Neural Network
| December 2026 | publication date |
| Proposal available till | 05-06-2025 |
| 4 total number of authors per manuscript | 0 $ |
| The title of the journal is available only for the authors who have already paid for |
| Journal’s subject area: |
| Modeling and Simulation; Applied Mathematics; Mechanical Engineering; Electrical and Electronic Engineering; Software; Artificial Intelligence; |
| place 1 | place 2 | place 3 | place 4 |
| Free | Free | Free | Free |
| 2350 $ | 1200 $ | 1050 $ | 900 $ |
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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 LevenbergMarquardt 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.
Keywords:
ANN; milling operation; process design; process parameters; titanium alloy
Contacts :
2 place - free (for sale)
3 place - free (for sale)
4 place - free (for sale)
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 LevenbergMarquardt 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.
Keywords:
ANN; milling operation; process design; process parameters; titanium alloy
Contacts :
