Investigation on the effect of MQL aerosol temperature on machining steels with sesame oil

Abstract

In metal machining, heat generation leads to various challenges that cutting fluids help mitigate by dissipating heat in the machining area. Minimum quantity lubrication also known as MQL technique effectively addresses heat-related issues while reducing the machining cost. Effects of reducing the aerosol temperature in MQL is not completely addressed in literature, especially with vegetable-based oils. Sesame oil exhibits exceptional qualities among different types of vegetable oils, making it a prominent candidate for use in metalworking processes. In this study, multi-objective optimization for lathe turning of AISI D2 was conducted using the Taguchi and Grey relational analysis methods. This approach allows simultaneous optimization of multiple responses, such as tool nose wear, surface roughness, energy consumption, and material removal rate. Initially, a MQL application apparatus was designed and developed to deliver MQL aerosol of sesame oil below ambient temperatures. In the experimental investigation, we have successfully lowered the aerosol temperature from 27°C to 12°C, which is the cloud point temperature of the sesame oil. Trials were conducted with dry-cutting and flood cooling at 27°C to establish control parameters. The significant factors impacting tool nose wear were identified as the cutting fluid application method and cutting speed, with optimal outcomes observed at a MQL aerosol temperature of 17°C. On average, considering all cutting speeds the reduction of tool nose wear was approximately 45% compared to dry cutting. Feed played a pivotal role in surface roughness and energy consumption, with optimal surface roughness achieved at feed of 0.13 rev/min and least energy consumption at feed of 0.35 rev/min. It is noted that, in terms of material removal rate, the applying method of cutting fluid has not shown a significant impact on machining performance. Interestingly, from the grey relational analysis, the cutting fluid applying method was identified as the most significant factor in multi-objective optimization. Additionally, achieving optimum results with MQL at an aerosol temperature of 17°C is noteworthy, especially when other factors are at their minimum levels.