Abstract
AbstractThe milling of aluminium silicon carbide reinforcement metal matrix composites (Al/SiCp MMCs) under two machining environments (one is dry and second is MQL) are analysed. The objective of this work is to reduce the flank wear during milling of Al/SiCp MMCs by the application of MQL. The paper not working only to reduce the tool wear but also worked on milling input parameters like feed rate, speed and depth of cut on tool wear. The forecast of the optimum value of the tool wear during milling of Al/SiCpMMCs plays a crucial role in analysing the working surface and tool life through the latest optimization techniques. The forecast model represented the impact of milling responses on tool wear (Vbmax). Then, the forecast-model result was compared with the experimental result of milling of Al/SiCp MMCs and observed to be almost same with them. The forecast and experimental results show that predicted model helps in to set the milling input parameters to minimizing flank wear Vbmax, during milling of Al/SiCp MMCs. Also, the results showed that application of minimum quantity lubrication helps in reduction of flank wear during milling of Al/SiCp MMCs.KeywordsMillingAl/SiCp MMCsTool flank wearMQL
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