Application of Graphene Nanofluid/Ultrasonic Atomization MQL System in Micromilling and Development of Optimal Predictiv
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Application of Graphene Nanofluid/Ultrasonic Atomization MQL System in Micromilling and Development of Optimal Predictive Model for SKH-9 High-Speed Steel Using Fuzzy-Logic-Based Multi-objective Design Wei-Tai Huang1 • Fu-I Chou2 • Jinn-Tsong Tsai3 • Jyh-Horng Chou4,5,6
Received: 31 December 2019 / Revised: 1 March 2020 / Accepted: 23 July 2020 Taiwan Fuzzy Systems Association 2020
Abstract This paper focuses on using nanofluid (graphene)/ultrasonic atomization minimum quantity lubrication (MQL) in micromilling for SKH-9 high-speed steel. Utilizing the special properties of graphene, which has excellent thermal conductivity, it is found that it successfully lowers the cutting temperature generated during processing, reduces tool wear, and improves the quality of micromilling products. Using a self-developed ultrasonic atomization system effectively improves the agglomeration of nanoparticles in nanofluids and increases the lubrication efficiency of nanoparticles. The experimental plot is & Jinn-Tsong Tsai [email protected] & Jyh-Horng Chou [email protected] Wei-Tai Huang [email protected] Fu-I Chou [email protected] 1
Department of Mechanical Engineering, National Pingtung University of Science and Technology, Pingtung, Taiwan, ROC
2
Department of Automation Engineering, National Formosa University, 64, Wun-Hua Road, Yunlin, Taiwan, ROC
3
Department of Computer Science, National Pingtung University, Pingtung, Taiwan, ROC
4
Department of Electrical Engineering, National Kaohsiung University of Science and Technology, Kaohsiung, Taiwan, ROC
5
Department of Healthcare Administration and Medical Informatics, Kaohsiung Medical University, Kaohsiung, Taiwan, ROC
6
Department of Mechanical Engineering, National Chung Hsing University, Taichung, Taiwan, ROC
robustly designed, and the L18(21 9 37) orthogonal table is used to find the optimal combination of parameters. The control factors are the average thickness of the nanographene, density of nanofluid, spindle speed, distance of nozzle, feed rate, amount ultrasonic atomization, air pressure, nozzle angle, and using gray correlation analysis with fuzzy inference to find more heavy quality characteristics. Finally, the optimal parameter combination of multi-quality characteristics enhanced by nanofluid (graphene)/ultrasonic atomization MQL is compared with the base fluid/ ultrasonic atomization MQL, nanofluid (MWCNTs)/ultrasonic atomization MQL, whereas the differences in micromilling force, temperature, tool wear, and workpiece burr are discussed. The results indicate that the use of nanofluid (graphene)/ultrasonic atomization MQL has better results than other lubrication methods. Keywords Micromilling Nanofluid minimum quantity lubrication Graphene Ultrasonic atomization MQL Robust process design Fuzzy inference systems Multiple performance characteristic index (MPCI)
1 Introduction Since last several years, the development of micromachining, which is an advanced manufacturing technology has been studied, such as silicon-base
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