Experimentation investigation of abrasive water jet machining parameters using Taguchi and Evolutionary optimization techniques

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• 作者：Rajkamal Shukla ; ^{rajkamalshukla2013@gmail.com} ; Dinesh Singh ^{dineshsinghmed@gmail.com}
• 关键词：Abrasive water jet machining ; Optimization ; Particle swarm optimization ; Firefly algorithm ; Artificial bee colony ; Simulated annealing ; Blackhole ; Biogeography-based optimization
• 刊名：Swarm and Evolutionary Computation
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：32
• 期：Complete
• 页码：167-183
• 全文大小：3135 K
• 卷排序：32

文摘

The paper demonstrates the applications of the some important optimization techniques. Selection of the optimal AWJM process parameters is significant. The experimentation is conducted on material “AA6351 Al-alloy” with abrasive water jet machining (AWJM) to get the optimum values of performance parameters “kerf top width and taper angle” for the given range of process parameters. Based on experimental results, the regression models for the performance parameters are developed. This paper compares the performance of seven optimization algorithms and confirmatory tests are conducted to validate the results.