Experimental and Metamodel Based Optimization of Cutting Parameters for Milling Inconel-800 Superalloy Under Nanofluid MQL Condition

Abstract

Machining of Inconel-800, a superalloy material that is difficult-to-cut materials, has received the special attention of many scientists worldwide. This paper adopts the advanced and industry-accepted lubrication method that is minimum quantity lubrication technique (MQL) which enhances nanoparticle particles to improve the machinability of Inconel-800 superalloy material and reduce the quantity of conventional cutting fluids. The metamodel namely Radial basis function (RBF) was used for expressing the relationship between cutting velocity, feed per tooth, depth of cut, and corner radius to two quality factors, including cutting force and specific cutting force. A combination of the RBF approximate model and Non-dominated Sorting Genetic Algorithm II (NSGA-II) algorithm was applied to find out optimal global solutions for the multi-objective optimization problem. The results show that this study plays a part in supporting scientists and engineers to understand machining difficult-tocut materials better and minimize waste to the environment towards sustainable and environmentally friendly machining.

Optimizing SKD-61 steel machining for marine component manufacture: A grey-Taguchi study on nanofluid minimum quantity lubrication

“…Researchers have investigated several machining procedures to increase the hard milling performance of SKD-61 steel, aligning with the maritime industry's stringent requirements. Among these techniques, Minimum quantity lubrication (MQL) and nanofl uid MQL have received much attention [3,4]. MQL is a machining method that employs little lubricant to minimize friction and heat during machining, resulting in less tool wear, better surface quality, and improved machining performance suitable for maritime equipment [5].…”