Optimization of Tool Geometry and Cutting Parameters for Hard Turning

In the hard-turning process, tool geometry and cutting conditions determine the time and cost of production which ultimately affect the quality of the final product. So reliable models and methods are required for the prediction of the output performance of the process. In the present work, experimental investigation has been conducted to see the effect of the tool geometry (effective rake angle and nose radius) and cutting conditions (cutting speed and feed) on the surface finish during the hard turning of the bearing steel. First- and second-order mathematical models were developed in terms of machining parameters by using the response surface methodology on the basis of the experimental results. The surface roughness prediction model has been optimized to obtain the surface roughness values by using genetic algorithms. The genetic algorithm program gives minimum values of surface roughness and their respective optimal conditions.     

An application of goal programming technique in metal cutting

This paper outlines the use of the goal programming technique in selecting levels of machining parameters in a fine turning operation on A1S1 4140 steel using cemented tungsten carbide tools. Goals that are proposed to be achieved are: (i) to finish turning the required depth in one pass, mid (ii) to finish turning within a stipulated time. Constraints used are: R.M.S. surface finish values, cutting horse power of the machine, ranges for cutting speed, feed and depth of cut. A predictive equation to predict the R.M.S. Surface roughness values from the machining variables, cutting speed, feed, depth of cut, and time of cut was used. This mathematical model was developed using stepwise regression analysis on the experimental data for 1/64 in. nose radius cemented tungsten carbide cutting tool. Experiment with the machining variables at different levels were performed to obtain the data. A statistically designed experiment called the rotatable design was used for the experimental design     

Performance of alumina-based ceramic inserts in high-speed machining of nimonic 80A

The study of machining forces and cutting tool wear during the machining is important for designing and selection of machining system and improving the productivity. This study reports the machinability of Nimonic 80A superalloy with alumina-based ceramic inserts. The objective is to analyze the reason for higher cutting forces generated during machining and tool wear mechanism on machining parameters. The cutting forces and tool wear are found to be mainly influenced by the cutting speed. The main causes of tool failure while machining Nimonic 80A are adhesion and abrasion. The role of tool wear is more dominant on the surface finish at lower cutting speed. Also, with an increase in cutting speed, thermally activated wear quietly increases at tool surfaces. The mechanistic approach is used to model the main cutting force. Developed cutting force model agrees well with experimental cutting force values.     

High-speed turning experiments on metal matrix composites

The hard abrasive ceramic component which increases the mechanical characteristics of metal matrix composites (MMC) causes quick wear and premature tool failure in the machining operations. The aim of the paper is to compare the behaviour of high rake angle carbide tools with their diamond coated versions in high-speed machining of an Al₂O₃Al 6061 MMC. The influence of the cutting parameters, in particular cutting feed and speed, on tool wear and surface finish has been investigated. The higher abrasion resistance of the coatings results in increased tool life performances and different chip formation mechanisms.     

Performance Improvement of End Milling Using Graphite as a Solid Lubricant

In any machining operation, the use of coolants is essential to dissipate heat generated during machining and hence to improve productivity, machinability, etc. However, the use of cutting fluids in machining operations may seriously degrade the quality of environment. New cutting techniques are to be investigated to alleviate the problems associated with wet machining. To overcome some of the problems, an attempt has been made to use graphite as a solid lubricant. This paper deals with an investigation on using graphite as a solid lubricant to reduce the heat generated at the milling zone. An experimental setup has been developed to direct graphite powder continuously onto the workpiece and tool interface at the required flow rate. Experimental studies have been conducted to see the effect of tool geometry (radial rake angle and nose radius) and cutting conditions (cutting speed and feed rate) on the machining responses such as cutting forces, specific energy, and surface finish in solid lubricant assisted machining using four fluted solid coated carbide end mill cutters. Results indicate that there is a considerable improvement in the performance of milling AISI 1045 steel using graphite as a solid lubricant when compared with machining using cutting fluids in terms of specific energy requirements, cutting force, and surface finish.     

Multi-attribute optimization of end milling epoxy granite composites using TOPSIS

Epoxy granite composites are identified and recognized as better materials for machine tool applications due to inherent damping properties. However, end milling of these composites has not been explored much. Milling of epoxy granite composites presents a number of problems, namely, cutting forces and surface roughness appear during machining. This research work focuses on end milling of epoxy granite composite specimens using high-speed steel end mill cutter by varying the cutting conditions such as spindle speed and feed with a uniform depth of cut and selection of optimal machining parameters. The experimental runs of 27 different trials were carried out and three different attributes such as thrust force, tangential force, and surface roughness were analyzed. This research work presents a sequential procedure for machining parameters selection. Selection of optimal machining parameters is done on the basis of Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method.     

Improvement of Machinability using Laser-Aided Hybrid Machining for Inconel 718 Alloy

Hybrid machining is an emerging technique for difficult-to-cut materials to overcome the problems associated with conventional machining (CM). Inconel 718, a super alloy of nickel, is a high-temperature alloy commonly used in aircraft and thermal industries and categorized as one among the difficult-to-cut materials. In this study, the influence of cutting conditions of Inconel 718 alloy during laser-assisted hybrid machining (LAHM) is investigated and the results are compared with CM. During LAHM, the process parameters of cutting speed, feed rate, approach angle, and laser power are varied. The present work is carried out in two phases: (i) determination of effective heat-affected depth (HAD) during laser preheating (using central composite design (CCD) in response surface methodology); (ii) optimization of cutting conditions during machining (using Taguchi's method). Compared with CM, the LAHM shows the following reduction benefits: (i) 33% in feed force (Fx), 42% in thrust force (Fy), and 28% in cutting force; (ii) improved surface finish (surface roughness, Ra) of 28%; and (iii) reduction in tool wear by 50%. The chip morphology reveals the decrease in shear angle and increase in chip thickness during LAHM. No change in the hardness value of the machined surface after LAHM indicates the absence of subsurface damage.     

Optimization of multipass turning operations with genetic algorithms

The paper proposes a new optimization technique based on genetic algorithms for the determination of the cutting parameters in multipass machining operations. The cutting process simultaneously considers multipass rough machining and finish machining. The optimum machining parameters are determined by minimizing the unit production cost subject to practical machining constraints. The cutting model formulated is a non-linear-constrained programming (NCP) problem with 20 machining parameter constraints. Experimental results show that the proposed genetic algorithm-based procedure for solving the NCP problem is both effective and efficient, and can be integrated into an intelligent manufacturing system for solving complex machining optimization problems.     

Optimization of Machining Characteristics for Al／SiCp Composites using ANN／GA

The present work is focused on optimization of machining characteristics of Al/SiCp composites.The machining characteristics such as specific energy,tool wear and surface roughness were studied.The parameters such as volume fraction of SiC,cutting speed and feed rate were considered.Artificial neural networks(NN) was used to train and simulate the experimental data.Genetic algorithms(GA) was interfaced with ANN to optimize the machining conditions for the desired machining characteristics .Validation of optimized results was also performed by confirmation experiments.     

Effect of machining parameters on turning of VAT32® superalloy with ceramic tool

The objective of this research was to study the machining of superalloy VAT32® using alumina-based ceramic tool without cutting fluid, applying different machining parameters to evaluate the surface finish of parts, vibration and main wear of tools. For this, a turning process with a linear trajectory of 30 mm was performed, in which were collected data vibration and surface roughness of the stretch, as well as wear and damage in the tools. The turning tests were performed utilizing cutting speeds of 270, 280 and 300 m/min, a feed of 0.10, 0.18 and 0.25 m/rev and a cutting depth of 0.50 mm. With results, it was identified that the feed influenced significantly both the vibration and the system, since the cutting speed influenced only the vibration. Being that the best results happened for the smaller feed and greater cutting speed. It concludes that the machining of superalloy VAT32® with ceramic tool introduced herself promising.