A coolant supply strategy based on cutting temperature prediction during the 3-axis end-milling of Ti-6Al-4V. (December 2022)

• Record Type: Journal Article
• Authors: Lee, Woo-Jun; Park, Seong-Hyun; Yoon, Hae-Sung
• Is Part Of: Journal of manufacturing processes. Volume 84(2022)
• Page Start: 272
• Page End: 281
• Publication Date: 2022-12
• Subjects: Titanium alloys -- End-milling -- Energy-saving -- Coolant supply -- Cutting temperature -- Sustainable machining; Production management -- Data processing -- Periodicals; Manufacturing processes -- Periodicals; Procestechnologie; Productietechniek; Production -- Gestion -- Informatique -- Périodiques; Fabrication -- Périodiques; Manufacturing processes; Production management -- Data processing; Periodicals; 670.5
• DOI: 10.1016/j.jmapro.2022.10.010
• Languages: English
• ISSNs: 1526-6125

Abstract

Abstract: Due to serious environmental concerns, the need to reduce energy consumption is emerging in many industries, including manufacturing. In this study, an energy-saving strategy is proposed by controlling the coolant supply in end-milling based on cutting temperature prediction. For cutting temperature prediction, various attempts have been made based on numerical simulation or empirical modeling, both requiring significant efforts. This study aimed to construct a simple but accurate temperature prediction model by analyzing temperature behaviors in end-milling. Here, two sets of experiments were conducted. First, the change in cutting temperature according to the cutting length was observed. Second, Nathan Cook's model, which is the cutting temperature prediction model for orthogonal cutting, was analyzed and applied to the end-milling. The model and experimental results showed that the heat was not accumulated according to the cutting length and the feed was the dominant factor influencing the cutting temperature. The temperature prediction model could be easily constructed with a small number of experiments. As a proof of concept, the coolant supply control based on the temperature prediction was shown. The suggested strategy reduced the energy consumption by 20.9 % without a sudden drop in temperature or surface quality. It is expected that this research can contribute to the development of the coolant supply strategy in industrial fields with ease of temperature prediction and implementation of the strategy. Highlights: This paper presents a coolant supply strategy for energy-efficient machining. Temperature behaviors in titanium alloy machining were analyzed. Cook's model was modified and verified in end-milling. The coolant supply was controlled based on the cutting temperature prediction. The suggested model could be easily constructed and was effective in energy-saving.