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.     

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.     

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.     

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.     

CRYOGENIC MACHINING OF KEVLAR COMPOSITES

Previous attempts to machine Kevlar aramid fibre reinforced plastics (KFRP) with conventional cutting tools have proven to be extremely difficult. This has somewhat restricted the material's usage, often negating the advantages of its high strength to weight ratio and fatigue tolerance. The present paper describes a novel technique of machining KFRP under cryogenic conditions with remarkable results compared to those obtained at ambient temperatures. The investigation carried out with turning operation shows dramatic improvement of the tool performance and surface quality. The effects of various machining parameters such as workpiece temperature, cutting speed and tool geometry on the machinability of KFRP are presented and analyzed. It appears that care is necessary to judge the tool life as the typical tool wear growth and surface finish or cutting force may produce contradictory results. It is also suggested that, for KFRP, surface finish of the machined workpiece is a very good criterion to determine the tool life. To aid the understanding of the machining mechanics, a microscopic investigation of the cutting zone while actually machining a testpiece at ambient and cryogenic temperatures is also reported.     

Machining parameters optimization for satisfying the multiple objectives in machining of MMCs

The metal matrix composites (MMCs) have gained acceptance in an extensive range of applications owing to their high strength to mass ratio. Machining of such complex MMCs is often challenging. It is essential to optimize the controllable machining parameters to simultaneously attain manifold objectives. In the current work, response surface design is created for experiments, and Genetic algorithm (GA) combined with Principal Components Analysis (PCA) coupled Grey Relational Analysis (GRA) is employed to improve the straight turning process of MMCs. The procedure is demonstrated by machining aluminum-based MMC with 25% SiC particulates. The procedure aims at identifying optimal combination of machining parameters to obtain high surface quality at lower cutting force without increasing the specific power consumption. PCA is helpful in providing the individual uncorrelated quality characteristics called as quality indices that do not have any influence on other responses. Individual quality indices have been utilized to obtain the grey relational grade through GRA. GRA has been used to alter manifold quality indices into singular column of grey relational grade as a means to change the manifold objective problem into a sole objective problem. Then, GA has been used to get the optimal parameters combination. The novelty present in this work is the avoidance of correlation existing among the quality characteristics and combining of the GRA and GA. This is an endeavor to augment the performance and accuracy of GA to solve the optimization problem associated with the turning operation.     

A study on milling of glass fiber reinforced plastics manufactured by hand-lay up using statistical analysis (ANOVA)

Milling is the most practical machining (corrective) operation for removing excess material to produce a well defined and high quality surface. However, milling composite materials presents a number of problems such as surface delamination associated with the characteristics of the material and the cutting parameters used. In order to minimize these problem is presented a study with the objective of evaluating the cutting parameters (cutting velocity and feed rate) related to machining force in the workpiece, delamination factor, surface roughness and international dimensional precision in two GFRP composite materials (Viapal VUP 9731 and ATLAC 382-05). A plan of experiments, based on an orthogonal array, was established considering milling with prefixed cutting parameters. Finally an analysis of variance (ANOVA) was preformed to investigate the cutting characteristics of GFRP composite materials using a cemented carbide (K10) end mill.     

Mathematical modeling and analysis of WEDM machining parameters of nickel-based super alloy using response surface methodology

Inconel 625 is one of the most versatile nickel-based super alloy used in the aerospace, automobile, chemical processing, oil refining, marine, waste treatment, pulp and paper, and power industries. Wire electrical discharge machining (WEDM) is the process considered in the present text for machining of Inconel 625 as it can provide an effective solution for machining ultra-hard, high-strength and temperature-resistant materials and alloys, overcoming the constraints of the conventional processes. The present work is mainly focused on the analysis and optimization of the WEDM process parameters of Inconel 625. The four machining parameters, that is, pulse on time, pulse off time, spark gap voltage and wire feed have been varied to investigate their effects on three output responses, such as cutting speed, gap current, and surface roughness. Response surface methodology was used to develop the experimental models. The parametric analysis-based results revealed that pulse on time and pulse off time were significant, spark gap voltage is the least significant, and wire feed as a single factor is insignificant. Multi-objective optimization technique was employed using desirability approach to obtain the optimal parameters setting. Furthermore, surface topography in terms of machining parameters revealed that pulse on time and pulse off time significantly deteriorate the surface of the machined samples, which produce the deeper, wider overlapping craters and globules of debris.     

Cost-effective way of hard turning with newly developed HSN2-coated tool

EN-31 (AISI 52100, hardness 55 HRC) is one of the difficult-to-cut steel alloys and it is commonly used in shafts and bearings. Nowadays, it is becoming a challenge to the cutting tool material for economical machining of extremely tough and hard steels. In general, CBN and PCBN tools are used for machining hardened steel. However, machining cost using these tools becomes higher due to high tool cost. For this purpose, carbide tool using selective coatings is the best substitute having comparable tool life, while its cost is approximately one-tenth of CBN tool. In this work, the newly developed second-generation TiAlxN super nitride (i.e., HSN²) is selected for PVD coating on carbide tool insert and further characterized using thermogravimetric analysis and differential scanning calorimetry for oxidation and thermal stability at high temperature. Later, HSN²-coated carbide inserts are successfully tested for their sustainability to expected tool life for turning of AISI 52100 steel. In the present study, forces, surface finish, and tool wear are used as a measure to appraise the performance of hard turning process. Experimentally, it is found that speed, feed rate, and depth of cut have considerable impact on forces, insert wear, and surface roughness of the machined surface.     

Numerical simulation of finish hard turning for AISI H13 die steel

A coupled thermo-mechanical model of plane-strain orthogonal turning of hardened steel was presented. In general, the flow stress models used in computer simulation of machining processes are a function of effective strain, effective strain rate and temperature developed during the cutting process. However, these models do not adequately describe the material behavior in hard machining, where the workpiece material is machined in its hardened condition. This hardness modifies the strength and work hardening characteristics of the material being cut. So, the flow stress of the work-material was taken with literature [H. Yan, J. Hua, R. Shivpuri, Development of flow stress model for hard machining of AISI H13 work tool steel. The Fourth International Conference on Physical and Numerical Simulation of Materials Processing, Shanghui in China, 2004, p. 5] in order to take into account the effect of the large strain, strain-rate, temperature and initial workpiece hardness. Then a series of numerical simulations had been done to investigate the effect of machining parameters on the machinability of hardened steel AISI H13 in finish turning process. The results obtained are helpful for optimizing process parameters and improving the design of cutting inserts in finish turning of hardened steel AISI H13.     

Machinability studies on 17-4 PH stainless steel under cryogenic cooling environment

Under higher cutting conditions, machining of 17-4 precipitation hardenable stainless steel (PH SS) is a difficult task due to the high cutting temperatures as well as accumulation of chips at the machining zone, which causes tool damage and impairment of machined surface finish. Cryogenic machining is an efficient, eco-friendly manufacturing process. In the current work, cutting temperature, tool wear (flank wear (V_b) and rake wear), chip morphology, and surface integrity (surface topography, surface finish (R_a), white layer thickness (WLT)) were considered as investigative machinability characteristics under the cryogenic (liquid nitrogen), minimum quantity lubrication (MQL), wet and dry environments at varying cutting velocities while machining 17-4 PH SS. The results show that the maximum cutting temperature drop found in cryogenic machining was 72%, 62%, and 61%, respectively, in contrast to dry, wet, and MQL machining conditions. Similarly, the maximum tool wear reduction was found to be 60%, 55%, and 50% in cryogenic machining over the dry, wet, and MQL machining conditions, respectively. Among all the machining environments, better surface integrity was obtained by cryogenic machining, which could produce the functionally superior products.     

Multiple Performance Optimization of Machining Parameters on the Machining of GFRP Composites Using Carbide (K10) Tool

The present investigation focuses on the multiple performance machining characteristics of GFRP composites produced through filament winding. Grey relational analysis was used for the optimization of the machining parameters on machining GFRP composites using carbide (K10) tool. According to the Taguchi quality concept, a L27, 3-level orthogonal array was chosen for the experiments. The machining parameters namely work piece fiber orientation, cutting speed, feed rate, depth of cut and machining time have been optimized based on the multiple performance characteristics including material removal rate, tool wear, surface roughness and specific cutting pressure. Experimental results have shown that machining performance in the composite machining process can be improved effectively by using this approach.     

Effect of Machining Parameters on Surface Integrity in High Speed Milling of Super Alloy GH4169/Inconel 718

Control of surface integrity is a vital consideration in the machining of components subjected to fatigue loading, for example, critical components of aerospace engines. In this research, three important aspects of surface integrity of a machined part—surface roughness, micro-hardness, and residual stresses—were analyzed for their variations with the cutting parameters. Finish milling of super alloy GH4169/Inconel 718 was carried out using coated cemented carbide and whisker-reinforced coated ceramic inserts. All of the three machining parameters—cutting speed, feed rate, and depth of cut—were found to have a substantial effect on the surface integrity of the finished part. Although different cutting parameters gave different effects for the two types of cutting inserts, overall better surface integrity was obtained at minimum cutting feed and medium cutting speed and depth of cut value. Moreover, carbide inserts produced better surface integrity of the finished part, whereas ceramic inserts generated very high surface tensile stresses and poor surface finish due to back striking of the adhered metal chips.     

Near-Cryogenic Machining of Polymethyl Methacrylate for Micromilling Tool Development

Micromilling tools with a diameter of 22 micrometers were developed to machine polymethyl methacrylate (PMMA) for micro systems applications. Due to the small diameter of the tool, and therefore its slow cutting speed, the specific cutting energy of PMMA in the near-brittle state was needed so the micromilling feed could be estimated. To determine the specific cutting energy in the near-brittle state, PMMA was cooled with liquid nitrogen and machined with diamond tools under normal machining conditions. Cutting forces and surface finish were measured from room temperature down to -53°C. It was found that as the temperature of the PMMA was reduced, the specific cutting energy increased linearly to approximately that of oxygen-free high conductivity copper. It was also found that the surface finish became rougher as the temperature decreased. Using these results, micromilling tools were fabricated using focused ion beam machining. The tools were used to micromachine PMMA electroforming molds with high precision, small features, and excellent surface finish. Using the feed indicated from the cryogenic machining and other tests, the micromilling tools did not break after extended periods of machining.