Sustainability assessment and optimization for milling of compacted graphite iron using hybrid nanofluid assisted minimum quantity lubrication method

Abstract

The climate change packages have strict regulations to reduce fuel consumption, costs, and carbon emissions in vehicles. Automobile manufacturers tend to utilize compacted graphite iron (CGI) in vehicle engine parts due to these regulations and rising engine performance needs. However, the difficulty of CGI machining and the sustainability problem during machining are barriers to its broad application in the automobile sector. In this study, nano molybdenum disulfide (nMoS2) reinforced nanofluid-assisted MQL (nMoS2-NMQL), multi-walled carbon nanotube (MWCNT) reinforced nanofluid-assisted MQL (MWCNT-NMQL) and nMoS2/MWCNT reinforced hybrid nanofluid-assisted MQL (HNMQL) cutting conditions were used for the first time in the milling of CGI material and machining performance was investigated in terms of cutting forces, cutting temperature and surface roughness. In addition, for the first time in the milling of CGI material, sustainability assessment and optimization in terms of carbon emissions and total machining cost have been carried out using non-dominant sequencing genetic algorithm II (NSGA-II) and technique for order of preference by similarity to ideal solution (TOPSIS). Using the MWCNT-NMQL cutting condition reduced the cutting temperature, resultant force, surface roughness, carbon emissions amount, and total machining cost by 38.2%, 54.5%, 57.6%, 7.6%, and 24%, respectively. The sustainability optimization conclusion was that MWCNT-NMQL cutting condition, cutting speed values between 90 and 93 m/min, and feed values between 0.11 and 0.117 mm/rev should be used in order to obtain the values closest to the optimum result for an improved and sustainable CGI milling process.