Parameter Optimization and Machining Performance of Inconel 625 with Nanoparticles Dispersed in Biolubricant

• Published in: Advances in materials science and engineering Vol. 2022; pp. 1 - 14
• Main Authors: Mohanraj, T., Radhika, N., Aswin Nanda, S., Vignesh, V., Jayaraman, B., Ratana Selvan, K. R., Admassu, Yesgat
• Format: Journal Article
• Language: English
• Published: New York Hindawi 2022; Hindawi Limited; Wiley
• Subjects: Additives; Biomedical materials; Copper oxides; Costs; Design of experiments; Heat conductivity; Heat transfer; Lubricants; Lubricants & lubrication; Manufacturing; Material removal rate (machining); Mathematical analysis; Mineral oils; Morphology; Nanoparticles; Nickel base alloys; Optimization; Palm oil; Productivity; Spindles; Superalloys; Surface roughness; Taguchi methods; Titanium dioxide; Tool wear; Vegetable oils; Vibration; Viscosity; Workpieces
• ISSN: 1687-8434; 1687-8442
• DOI: 10.1155/2022/7210265

Productivity and cost-effectiveness are essential components of any long-term manufacturing system. While quantity and quality are linked to productivity, the economy focuses on energy-efficient processes that produce a high output-to-input ratio. Hard-to-cut materials have always been difficult to machine because of more significant tool wear and power losses. Inconel 625 is a hard material used in aerospace and underwater applications and is milled using biolubricants with nanoparticles. Palm oil is considered a biolubricant, and titanium dioxide (TiO2) and copper oxide (CuO) are selected as nanoparticles. When the combination of biolubricants and nanoparticles is added to the workpiece’s surface, it enhanced some properties while machining. Experiments involving four factors with four levels were carried out using the Taguchi design of experiments (DoE). The feed, depth of cut, speed, and coolant with nanoparticle additives were all factors. The responses were surface roughness, spindle vibration along X, Y, and Z axes, and material removal rate. Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) was used to alter the multiresponse optimization problem to a single-response optimization problem. The S/N of TOPSIS closeness coefficients was calculated, and the optimal machining conditions were determined. Surface roughness, material removal rate, and spindle vibration were reduced by 3.10%, 6.14%, 7.54% (Vx), and 6.78% (Vz), respectively, due to the TOPSIS optimization.