Ping-Yueh Chang1, Fu-I Chou1, Po-Yuan Yang2,*, Shao-Hsien Chen3
Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 23-38, 2023, DOI:10.32604/iasc.2023.031609
Abstract This paper proposes a hybrid multi-object optimization method integrating a uniform design, an adaptive network-based fuzzy inference system (ANFIS), and a multi-objective particle swarm optimizer (MOPSO) to optimize the rigid tapping parameters and minimize the synchronization errors and cycle times of computer numerical control (CNC) machines. First, rigid tapping parameters and uniform (including 41-level and 19-level) layouts were adopted to collect representative data for modeling. Next, ANFIS was used to build the model for the collected 41-level and 19-level uniform layout experiment data. In tapping center machines, the synchronization errors and cycle times are important considerations, so these two objects… More >
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