Optimization of machining parameters using fuzzy Taguchi method for reducing tool wear

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Abstract

Manufacturing industries are gradually changing to green production due to the increasing production cost. Reducing tool wear in production can not only decrease production cost but also the effect the environment. Thus, it becomes a crucial issue for the machining industry. This study investigates the optimal machining parameters for the computer numerical controlled turning process of S45C steel in minimizing tool wear. The correlation between control parameters (speed, cutting depth, and feed rate) and production quality were constructed by using semantic rules and fuzzy quantification. The Taguchi method was additionally employed to determine the optimal turning parameters. Under the consideration of environmental protection and tool cost, the optimal machining parameters were furthermore derived from the fuzzy semantic rules. The practicability of the optimal parameters was moreover verified through turning experiments. It is found that the proposed method in this study is appropriate and applicable to universal applications.

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Lan, T. S., Chuang, K. C., & Chen, Y. M. (2018). Optimization of machining parameters using fuzzy Taguchi method for reducing tool wear. Applied Sciences (Switzerland), 8(7). https://doi.org/10.3390/app8071011

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