Influence of hybrid Cryo-MQL lubri-cooling strategy on the machining and tribological characteristics of Inconel 718. (November 2021)

• Record Type: Journal Article
• Authors: Danish, Mohd; Gupta, Munish Kumar; Rubaiee, Saeed; Ahmed, Anas; Korkmaz, Mehmet Erdi
• Is Part Of: Tribology international. Volume 163(2021)
• Publication Date: 2021-11
• Subjects: Nickel-based alloy -- Hybrid lubrication -- Tool wear mechanism -- Chip morphology -- Micro-structure; Tribology -- Periodicals; 621.89
• DOI: 10.1016/j.triboint.2021.107178
• Languages: English
• ISSNs: 0301-679X

Abstract

Abstract: The poor thermal conductivity of Inconel 718 leads to higher cutting temperatures and, as a consequence, rapid tool degradation is a common phenomenon. As a result, a hybrid lubri-cooling environment for turning Inconel 718 alloys is proposed, incorporating the theory of cryogenic cooling and minimum quantity lubrication (Cryo-MQL). For improved lubri-cooling effect, Cryo-MQL integrates the application of a minimum quantity of vegetable oil and liquid nitrogen from two distinct nozzles in the cutting zone. Surface roughness, cutting temperature, tool wear, chip morphology, and micro-structure of the machined surface were evaluated for different lubri-cooling mediums: dry, MQL, Cryogenic, and Cryo-MQL. In comparison to a dry medium, the Cryo-MQL environment decreases surface roughness, cutting temperature, and tool wear by 60.6%, 37%, and 19.5%, respectively. Adhesion and abrasion were patented to be common tool wear types, as per SEM micro-graphs. Eventually, in the Cryo-MQL environment, a spike in micro-hardness value has been reported. However, during processing with Cryo-MQL, the grain structure of the working material is found to be smaller as compared to other mediums. Highlights: Turning of the aerospace alloy under sustainable lubri-cooling mediums were performed. Wear tribology of the cutting inserts was investigated using FESEM and EDX. Microstructure and micro-hardness of the machined surfaces were also examined. Hybrid cryo-MQL provides significant results.