Papers by Keyword: Machining Optimization

Abstract: A simple approach to multi-objective optimization of machining parameters is presented. Regression analysis of experimental data is carried out to obtain the correlation between cutting parameters and response variables. Finally, Genetic Algorithm (GA) toolbox of MATLAB is used to carry out multi-objective optimization of two objective functions (surface roughness “Ra” & material removal rate “MRR”). Genetic algorithm is found to be a powerful tool for multi-objective optimization of machining parameters in this study.

Abstract: Turning operation is fundamental in the manufacturing industry to produce cylindrical parts especially for producing near-nett shape, and aesthetic requirements with good dimensional accuracy. This present research chapter, an attempt has been made to investigate the machining characteristics of titanium alloys. The investigation has been carried out to measure the effect of tool flank wear, surface roughness, cutting force and temperature on different cutting tools by adopting Taguchi’s design of experiment concept. This investigation was set to analyse and develop a mathematical model using response surface methodology, fuzzy logic. The observed responses were optimized using grey relational grade algorithm. Except for a few cases, the experimental results have close proximity (95%) to the predicted value. This validates the model developed in this work. Orthogonal array with grey relational analysis has been successfully implemented for the optimization of the machining parameters. The optimized cutting conditions evolved in this research study will help to achieve better machinability of these advanced materials like titanium alloy.

Abstract: In the paper,a new hybrid optimization technique for multi-objective optimization of surface milling is proposed. The developed approach is based on enhanced Pareto particle swarm optimization algorithm. The optimization of double-station milling is investigated basing on the available model in terms of two objectives: spindle power and production time. The final result is not a single solution but a whole set. In order to obtain satisfied Pareto set, multi-objective evolutionary algorithm for rail milling problem (MOEA-RMP) is used. An illustrative example was used to demonstrate effectiveness and applicability of the proposed approach.

Abstract: The machining process produces high local temperatures in the tool-chip and tool-workpiece contact areas, normally lead to negative influence on the machine performance. This paper presents a study on optimizing the internal micro channel structure of a tungsten carbide (WC) cutting tool in order to enhance heat transfer rate when applied with internal cooling fluid. Inspired by water jet impingement theory, the efficiency and heat transfer rate of single phase micro channel mainly depends on the fluid velocity as well as temperature difference between the cooling fluid and hot surface. In this study three variables, i.e. the space between channel and internal wall of the insert, channel diameter and fluid temperature, have been tested with design of experiments (DoE) to study the significance of the factors and interactions between them on cutting temperature. A 3-D finite element (FE) model has been developed to observe the effects of these factors on heat transfer rate. The simulation results show the most dominant factor to affect the cutting temperature is the temperature of the cooling fluid followed by the space between channel and tool insert internal wall.

Abstract: In this paper, based on analyzing the properties of medical Ti-6Al-4V Titanium alloy, the author takes the purpose of studying the machinability of the medical Ti-6Al-4V Titanium alloy and aims at improving the tool durability. The study starts from the tool material, geometrical parameters of the tools, usage for the cutting and other aspects in order to achieve the suitability of selecting cutting tool as well as the optimization of choosing cutting usage which lays the foundation for further investigation of the machinability of the medical Ti-6Al-4V Titanium alloy and carry out the online optimization of cutting parameters.