Evaluation of palm kernel oil as cutting lubricant in turning AISI 1039 steel using Taguchi-grey relational analysis optimization technique

Abstract

Cutting fluids have a known negative impact on productivity, human health, and the environment in the manufacturing sector. A suitable method for reducing the effect of cutting fluids on human health and the environment is minimum quantity lubrication (MQL). In this experiment, AISI 1039 steel was machined using vegetable oil lubricant and MQL. A chemical method was used to extract vegetable oil from palm kernel seeds. Then, using established techniques, the physicochemical and lubricity properties of palm kernel oil (PKO) were ascertained. The Taguchi L₉ (3³) orthogonal array served as the basis for the planning of the experimental design. Process parameters such as surface roughness, chip thickness ratio, cutting temperature, and material removal rate were measured during the turning operations. The multi-response outputs from TGRA were considered to simultaneously optimize the cutting parameters namely depth of cut, feed rate, and spindle speed. At a temperature of 55°C, 180 min, and particle sizes of 0.2–0.5 mm, an oil yield of 55% by weight was obtained. The viscosity at 40°C, specific gravity, pour, fire, cloud, and flash points of the raw PKO were 117.6 mm²/s, 0.8940 mg/ml, 21°C, 231°C, 22.3 $°C$ and 227°C, respectively. The surface roughness and cutting temperature of PKO improved by 44% and 12%, respectively, when compared with mineral oil. The findings of this research confirmed the effectiveness of the integrated Taguchi-grey relational analysis (TGRA) optimization method and established an experimental foundation for the use of PKO minimum quantity lubrication turning.