Fuzzy logic-based approach to investigate the novel uses of nano suspended lubrication in precise machining of aerospace AL tempered grade 6061
Temper-grade aluminum alloy Al-6061-T6 is commonly used for many engineering purposes owing to its superior mechanical properties. Due to the practical importance, machining Al-6061-T6 alloy is crucial for different applications. The development of computer numerical control (CNC) of milling machine...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2015
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| Subjects: | |
| Online Access: | http://eprints.um.edu.my/13847/1/Fuzzy_logic-based_approach_to_investigate_the_novel_uses_of.pdf http://eprints.um.edu.my/13847/ http://www.sciencedirect.com/science/article/pii/S0959652614011767 |
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| Summary: | Temper-grade aluminum alloy Al-6061-T6 is commonly used for many engineering purposes owing to its superior mechanical properties. Due to the practical importance, machining Al-6061-T6 alloy is crucial for different applications. The development of computer numerical control (CNC) of milling machines is in progress by researchers worldwide for its noteworthy advantages. The quality of machining determines the product's appearance, function and reliability. Appropriate lubrication at the machining zone improves the tribological characteristic of Al-6061-T6 alloy, leading to higher product quality. For reasons of ambiguity during machining, the soft computing technique is chosen to predict the output. In this particular research scope, a new fuzzy logic-based approach is adopted to determine the machining performance while milling Al-6061-T6 alloy using SiO2 nanoparticles added to the lubricant. The effects of nanoparticle concentration, nozzle angle and air pressure are investigated to determine the optimum machining conditions, such as lowest cutting force, cutting temperature and surface roughness. Four membership functions are designated to connect with each input. The predicted results are computed by fuzzy logic and compared with the experimental results. The proposed fuzzy model exhibits high degree of reliability according to the experimental results. The computed results showed 96.195, 98.27 and 91.37 accuracy with experimental results for cutting force, cutting temperature and surface roughness. (C) 2014 Elsevier Ltd. All rights reserved. |
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