Hardness Of Workpiece Material Research Articles

The Effect of Cutting Speed of Nitrogen Laser Cutting on the Surface Texture of SUS 304 Plate

The focus of today’s machining industry is on how to maintain high productivity and low cost achieved by high tool life during the operation. Laser cutting is considered the right solution because it offers cutting speeds of up to 170000 mm/min through a non-contact process regardless of the workpiece material hardness. The aim of this study is to analyze the effect of cutting speed on the surface texture aspects namely surface roughness, kerf shape, and dross height on the stainless steel 304 plate after laser cutting. The nitrogen laser was utilized with the cutting speed of 400, 1700, and 2000 mm /min and the average roughness (Ra) was then measured using a surface roughness tester. On the other hand, the top, middle, and bottom area of the kerf surface as well as the dross height were analyzed by scanning electron microscopy (SEM). The highest Ra value was resulted at cutting speed of 2000 mm/min with 2.965 ± 0.05 μm while the lowest was at 1400 mm/min with 2.522 ± 0.16 μm. In parallel, the Ra was found to be higher when subjected gradually from the top to bottom zone. The kerf surface also proved that the top zone is dominated by the cutting zone, while the middle and bottom zone are characterized by the transition and deformation zone respectively. The width between kerf lines increased when the higher cutting speed was performed. Additionally, the larger dross height was found at the cutting speed of 1400 mm/min with 32.75 ± 5.21 μm and then degraded gradually at the higher cutting speed. The heat input and laser capability in exposing the material thickness are responsible for determining the corresponding surface texture aspects.

Research on the relationship between workpiece surface machining quality and turning tool wear

In order to apply the workpiece surface machining quality detection data to tool wear prediction, an experiment on the relationship between workpiece surface machining quality and turning tool wear was carried out. Firstly, the experimental parameters are selected, and the workpiece surface quality is determined as the parameter to study the tool wear law; Secondly, by changing the tool material and workpiece material, the change law of tool wear is analyzed, and the internal reason of blade initial wear is revealed; Finally, the relationship between workpiece surface machining quality and tool wear is analyzed by measuring workpiece surface machining quality parameters. The experimental results show that the relative hardness of workpiece material and tool is the main factor determining the wear speed of tool flank, and the tool geometry is the main factor of rapid tool wear in the initial stage. The workpiece surface roughness increases gradually with tool wear. When the tool enters the severe wear stage, it decreases slightly and then continues to increase. The outer diameter of the workpiece decreases with the tool wear in the initial stage, and then fluctuates and increases gradually. The influence of tool wear on the cylindricity error of shaft parts can be ignored.

Experimental investigation of milling process under optimum lubricant use

Performance of the machining and the efficiency of milling operation depend on several process variables among which hardness of work material is of great significant. In this study, experimentation was carried out to investigate the effect of work hardness on end milling process. Workpiece material hardness is used as a noise factor. Input parameters used are spindle speed, feed; depth of cut and tool diameter.The experiments performed under wet and minimum Quantity lubrication and results of both compared. further for getting optimal lubricant conditions the experiments performed for various levels of flow rates of minimum quantity lubrication to get the best optimal setting. Output parameters are surface roughness, material removal rate, cutting force and tool wear. Design of Experiment (DOE) with Taguchi L27 Orthogonal Array (OA) has been explored to produce 27 specimens on Al2024 aluminium by end milling operation at three different levels of hardness of material. The experiments performed under wet and minimum quantity lubrication condition and results compared. Further For optimal lubricant condition the experiments performed at various flow rate of Minimum Quantity Lubrication and “best” optimal setting is identified.

Modelling and combined effect analysis of electric discharge Machining process using response surface methodology

Electrical discharge machining (EDM) is a contactless machining process based on the erosive impact of the electrical discharges. It has shown considerable usage in the machining of composites of extreme hardness and strength. The hybrid metal matrix composite (HMMC) is one such type of hard material. HMMCs have a parent metal with reinforcement materials added in varying weight percentages (% wt.) to improve the chemical and physical properties of the base metal. The electrode consumption increases with the increase in workpiece material hardness. The Industries are facing problems relating to high electrode consumption. This study provides the modeling and investigation of EDM of Aluminum-based HMMC, developed under strict environmental conditions by stir casting method. Current (Ip), pulse on time (Ton), pulse off time (Toff), voltage (V) and spark gap (Sg) were the selected machining parameters. Response surface method (RSM) utilised to evaluate the effect of selected parameters on electrode wear rate (EWR) using a pure copper (Cu) electrode. Second-order mathematical model for EWR developed using RSM and validated using analysis of variance (ANOVA). The ANOVA confirmed the model to be 95% significant. The combined effect of process variables on EWR studied through 3D surface plots. The current followed by pulse on time and spark gap adjudged to be the significant parameters on which EWR depends. The optimized setting of Input parameters noted out to be Ip = 3A, Ton = 50 µs, Toff = 6 µs, V = 40 V, and Sg = 5 mm.

Ultrafine particle emission during high-speed milling of hardened AISI 1045 steel

In this study, the effects of cutting speed, feed rate, and hardness of workpiece material on the particle number concentration ultrafine of particles in the face milling were experimentally investigated. AISI 1045 steel was hardened to 17, 38, and 48 HRC, machining using ceramic insert (honed, T-land edge preparation). Three factors (cutting speed, feed rate, and workpiece hardness) and three levels fractional experiment designs completed (L27) with statistical analysis of variance (ANOVA) were performed. The analysis of the results shows that workpiece hardness has the greatest influence on ultrafine particle (UFP) emission for both tools and that the feed rate and the cutting speed should be selected wisely for each tool edge preparation. Overall, it is shown that the use of honed edge at moderate speed and higher feed rate reduces UFP emission during milling.

A study on the vibrations in the external cylindrical grinding process of the alloy steels

The vibration during external cylindrical grinding is caused by many factors such as the rigidity of the technology system, machining modes, machining materials, cooling mode, etc. This paper employed a Taguchi method to design experiments and evaluate the influence of machining mode parameters and workpiece material hardness on the vibrations when machining some types of alloy steel in external cylindrical grinding process. The influence of machining conditions on the vibrations was investigated. Besides, the mathematical models of vibration amplitudes were also modeled. The achieved results can be used to control the vibrations through machining conditions to improve the surface quality of the product.

Parametric optimization in wire EDM of D2 tool steel using Taguchi method

Wire EDM is a non-traditional machining method which is widely used for machining of extremely hard material, and complex shapes which would not be possible using conventional machining methods. This method of machining is widely practised in mould, tool and die industries. In this process, there is no direct contact between the work piece material and wire electrode; therefore the hardness of work piece material is not a bounding factor for the machining process. In this process, removal of material to be done by producing a spark between the work piece material and the wire electrode. In the present work, the machining of AISI D2 die steel of 13 mm diameter was performed using a 0.25 mm dia wire electrode. The influence of various input process parameters (Ton, Toff, Ip, Tw) on the response characteristics (MRR, Ig, MT) was investigated by using Taguchi L9 orthogonal array. Signal to noise ratio and ANOVA will also employed in the study of response parameters.

Nanoplastic removal function and the mechanical nature of colloidal silica slurry polishing

AbstractThe nanomechanical deformations on a broad range of optical material surfaces (single crystals of Al2O3 [sapphire], SiC, Y3Al5O12 [YAG], CaF2, and LiB3O5 [LBO]; a SiO2–Al2O3–P2O5–Li2O glass‐ceramics [Zerodur]; and glasses of SiO2:TiO2 [ULE], SiO2 [fused silica], and P2O5–Al2O3–K2O–BaO [Phosphate]) near the elastic‐plastic load boundary have been measured by nanoindentation and nanoscratching to mimic the nanoplastic removal caused by a single slurry particle during polishing. Nanoindenation in air was performed to determine the workpiece hardness at various loads using a commercial nanoindenter with a Berkovich tip. Similarly, an atomic force microscope (AFM) with a stiff diamond coated tip (150 nm radius) was used to produce nanoplastic scratches in air and aqueous environments over a range of applied loads (~20‐170 μN). The resulting nanoplastic deformation of the nanoscratches were used to calculate the removal function (i.e., depth per pass) which ranged from 0.18 to 3.6 nm per pass for these materials. A linear correlation between the nanoplastic removal function and the polishing rate (using a fixed polishing process with colloidal silica slurry on a polyurethane pad) of these materials was observed implying that: (a) the polishing mechanism using colloidal silica slurry can be dominated by mechanical rather than chemical interactions; and (b) the nanoplastic removal function, as opposed to interface particle interactions, is the controlling factor for the polishing material removal rate. Furthermore, this correlation is consistent with the Ensemble Hertzian Multi‐Gap (EHMG) microscopic material removal rate model described previously. The nanoplastic removal depth was also found to correlate to the measured nanoindentation hardness (H1) of the optical material, scaling as H1−3.5. Two‐dimensional (2D) finite element analysis simulations of nanoindentation showed a similar nonlinear dependence of plastic deformation with the workpiece material hardness. The findings of this study are used to determine an effective Preston coefficient for the material removal rate expression and enhance the predictive nature of the nanoplastic polishing rate for various materials utilizing their material properties.

Influence of AA7075 crystallographic orientation on micro-grinding force

In micro-grinding, the depth of cut is smaller than the grain size of workpiece material. Since the micro-grinding wheel cuts through the grain boundaries, the crystallographic effects become more significant in the micro-grinding than that in macro-machining. To quantify the effect of crystallographic orientation on the flow stress of polycrystalline material, the Taylor factor model is developed by examining the number and type of the activated slip systems. Then, the shear force model is developed based on the flow stress model considering the effect of crystallographic orientation. Moreover, the plowing force is predicted based on the Vickers hardness of workpiece material and the plowing friction coefficient. A comprehensive model is then proposed to predict micro-grinding force by consolidating the mechanical, thermal, crystallographic, and size effect. Micro-grinding experiments adopting Taguchi’s method were conducted to verify the model, and the results indicated that the predictions agree well with the experimental data. Besides, single-factorial experiments were conducted with the only variable being Taylor factor and the results suggest that the Taylor factor model is capable of capturing the effect of crystallographic orientation on grinding force.

Audio-Based Tool Condition Monitoring in Milling of the Workpiece Material With the Hardness Variation Using Support Vector Machines and Convolutional Neural Networks

Machining industry has been evolving toward implementation of automation into the processes for higher productivity and efficiency. Although many studies have been conducted in the past to develop intelligent monitoring systems in various application scenarios of machining processes, most of them just focused on cutting tools without considering the influence of the nonuniform hardness of workpiece material. This study develops a compact, reliable, and cost-effective tool condition monitoring (TCM) system to detect the cutting tool wear in machining of the workpiece material with hardness variation. The generated audible sound signals during the machining process are analyzed by state-of-the-art artificial intelligent techniques, support vector machine (SVM) and convolutional neural network (CNN), to predict the tool wear and the hardness variation of the workpiece. A four-level classification model is developed for the system to detect the tool wear condition based on the width of the flank wear land and the hardness variation of the workpiece. This study also involves the comparative analysis between two employed artificial intelligent techniques to evaluate the performance of the model in prediction. The proposed TCM system has shown a high prediction accuracy in detecting the tool wear from the audible sound into the proposed multiclassification wear level in end milling of the nonuniform hardened workpiece.

The research and modelling about plastic flow measurement of machined surface in precision turning of hardened steel GCr15

Under some conditions, there are more serious plastic flow measurements, have a great effect on surface roughness, on the surface which is formed by hard cutting. A mathematical model, explained the relationship between surface plastic flow measurement and surface roughness, was established. The dependence of formed of surface plastic flow measurement on feed rate, corner radius and other factors was researched by finite element, simulation cutting test and observing the surface of workpiece microscopic. All the increase of the hardness of workpiece material, cutting temperature and cutting force, is vertical with the surface of workpiece, will reduce the height of plastic flow measurement. With the decrease of feed rate and the increase of corner radius, the surface roughness will decrease, meanwhile, the degree of plastic flow measurement aggravates. Effected by the plastic flow measurement, after the feed rate reduces to 0.036 mm/r, an increase trend will be shown.

Machinability Study on Finish Turning of AISI H13 Hot Working Die Tool Steel With Cubic Boron Nitride (CBN) Cutting Tool Inserts Using Response Surface Methodology (RSM)

Finish turning of hardened die tool steel offers an economical alternative to grinding process. This study investigated the effects of machining parameters including workpiece hardness in a range of 45–55 HRC on cutting forces (F c & F t ), surface roughness (R a ) and cutting edge temperature (T) in finish turning of AISIH13 die tool steel with CBN inserts. Workpiece material AISIH13 has been selected on the basis of its wide applications in die making industries in the range of hardness 45–60 HRC. A central composite design has been used for the design of experimentation, and by using response surface methodology, a mathematical model has been developed. This study reported that the cutting forces are primarily influenced by the hardness of workpiece material. The work material hardness, feed rate and depth of cut are also statistically significant on cutting forces. Also, cutting forces increases, with the increase in workpiece hardness, feed and depth of cut, whereas the cutting speed has least impact on cutting forces. In fact, increase in hardness of work material resulted in better surface roughness as well as increase in tool tip temperature. Furthermore, optimum parameters are obtained through multi-response optimization technique using desirability function approach. The novelty aspect of the present study is that it contributes to practical industrial application of finish turning for the die and mold makers to select the optimum cutting conditions in a range of hardness of 45–55 HRC.

Dependence between Workpiece Material Hardness and Face Lapping Results of Steel C45

The high demands required today by manufacturing engineers for machine parts and tools necessitate very precise machining. The finishing processes are an important perspective to be considered today for meeting the goals like parallelism, tolerances, flatness, and smooth surface. These processes are high-precision abrasive processes used to generate surfaces of desired characteristic such as geometry, form, tolerances, surface integrity, and roughness characteristics. A leading importance in this perspective has the lapping process. It leads to a surface with low roughness and high precision. The topographical structure resulting from lapping is very advantageous in sliding joints, because of the high ability of lubricant retention, as well as in nonsliding joints because of the high load-carrying ability. Many materials can be lapped, including glass, ceramic, plastic, metals and their alloys, sintered materials, satellite, ferrite, copper, cast iron, steel, etc.This paper reports the observations of steel C45 elements lapping process results. Workpieces were rollers with diameter 17 mm and height 10 mm placed in the conditioning rings with use of workholdings. Samples were divided to three groups according to their Vicker’s hardness: 160, 440, and 650 HV. After grinding, lapping process was conducted. Experiments were carried out with an angular speed of the lapping plate set at 65 RPM, and lapping velocity was v = 49 m/min. The lapping pressure was provided by dead weights and during experiments executing p = 0.04 MPa. Samples were lapped during 10, 15 and 20 minutes. Abrasive slurry was composed of silicon carbide grains mixed with kerosene and machine oil. Abrasive grains size was F400/17.The material removal rate (MRR) and specimens surface characteristic are studied in the light of workpiece material hardness. Test results show that applied process parameters are the best for steel which hardness is 440 HV. In that case, the lowest values of Raparameter were obtained in conjunction with satisfactory values of material removal rate. It can be also seen, as could be predicted, that lapping time influenced on lapping results. MRR increases and surface roughness decreases with time. The worst lapping results were obtained for normalized steel (160HV). It can be the effect of surface damage, like scratching and grooving by harder abrasive grains.

Fitting of Constitutive Material Parameters for FE-Based Machining Simulations for Functionally Graded Steel Components

The composition of different materials and their specific properties like tensile strength and toughness is one way to achieve workpiece characteristics which are tailored to the later application. Another approach is the subsequent local heat treatment of workpieces made of homogeneous materials. However, both ways are costly and go along with several subsequent process steps. Therefore, mono-material workpieces which were manufactured by thermo-mechanical forming processes may provide such tailored properties in the form of functional gradations. Furthermore, the process chain is shortened by the combination of forming and heat treatment, but nevertheless machining processes are still needed for proper workpiece finish. This puts the challenge of varying process conditions due to hardness alterations within a single process step, e.g. turning. In addition to experimental investigations simulative analysis techniques are desired to evaluate mechanical as well as thermal loads on tool and workpiece. In the case of FE-based microscopic chip formation simulations proper material behaviour needs to be determined with respect to material hardness. This paper describes the approach of fitting Johnson-Cook material parameters as a function of workpiece material hardness. In order to achieve realistic stress states within the process zone, this approach considers the yield strength as a linear function of the hardness. It is shown how the hardness influences the cutting conditions and how the Johnson-Cook parameters are identified. Then these parameters are validated in three-dimensional simulations of exterior dry turning by comparison of simulated process forces and chip formation to experimentally achieved ones.

Modeling the effect of variable work piece hardness on surface roughness in an end milling using multiple regression and adaptive Neuro fuzzy inference system

Article history: Received July 2 2013 Received in revised format September 7 2013 Accepted November 23 2013 Available online November 26 2013 The aim of this study is to correlate work piece material hardness with surface roughness in prediction studies. The proposed model is for prediction of surface roughness of tool steel materials of hardness 55 HRC to 62 HRC (±2 HRC). The machining experiments are performed under various cutting conditions using work piece of different hardness. The surface roughness of these specimens is measured. The result showed that the influence of work piece material hardness on surface finish is significant for cutting speed and feed in CNC end milling operation. It is also observed that the surface roughness prediction accuracy of Adaptive neuro fuzzy inference system using triangular membership function is better than Gaussian, bell shape membership function and regression analysis. Surface roughness prediction accuracy with material hardness as input parameter is 97.61%. © 2014 Growing Science Ltd. All rights reserved

A rule-based system for trade-off among energy consumption, tool life, and productivity in machining process

With ever-increasing understanding of environmental and societal concerns, the focus of manufacturing industries, worldwide, is fast changing from mere profit-making to ensuring sustainability. The companies are striving hard to make their manufacturing processes more environment-friendly, in addition to being cost effective and time- and resource-efficient. The paper presents an experimental investigation and an application of fuzzy modeling for trade-off among energy consumption, tool life, and productivity of a metal cutting (machining) process. A total of 54 grooving experiments are performed under various pre-determined combinations of the workpiece material hardness, cutting speed, cutting feed, and width of cut. The respective measurements are taken for tool damage, energy consumed, and cutting and feed forces. A fuzzy rule-based system is developed that consists of two modules: optimization and prediction. The former suggests the most suitable settings for the cutting parameters that would lead to accomplishment of various combinations of the objectives related to energy consumption, tool life, and machining productivity. The prediction module works out the predicted values of all the responses based on the finalized values of the four input parameters.

Modeling and Optimization of Micro Electro Discharge Machining Process: A Review

Micro Electrical discharge machining (µEDM) is an electro thermal process, the cutting force is negligibly small and material removal occurs irrespective of hardness of work piece material .Micro electrical discharge machining process is capable of machining of complex shape, which is difficult to machine in conventional machining process. Last decade, the EDM process involved demand for machining requirements with short period. Since the major risk of wire breakage, deflections of electrodes were affecting the performance accuracy of EDM operation. This paper describe about a comprehensive review of micro electro discharge machining process and its process optimization techniques used for last 10 years. Micro electro discharge machining has more important given to difficult to machine materials. In order to improve the surface integrity and performance of process, need to select proper process parameters. It reports on the Micro EDM research involving the optimization of the process parameters surveying the influence of the various factors affecting the machining performance and productivity.

Machinability Prediction of Workpiece Material with a Diagraph Method

This work presents a diagraph method for the description and predication of the potential machinability of work materials. In the method, a radar chart with five axes was used to examine the machinability of different work materials and each axis representing a behavior or property, i.e. abrasiveness or hardness of workpiece material by grading the 5 different machinability properties. Such charts are seen to be helpful in the setup work to machine the new materials or unknown materials when choosing suitable tool properties and the cutting data suitable for the new material machining.

Fuzzy Rules for Surface Roughness of Ground Steels

This paper presents a comprehensive model for predicting surface roughness due to grinding. Fuzzy rules are provided, to estimate roughness for any practical combination of (1) wheel hardness grade, (2) abrasive grain size, (3) dressing condition, (4) table speed, (5) wheel depth of cut, and (6) coolant application. The rule-base can be adapted to account for the effect of (7) different workpiece material hardness, (8) wheel rotational speed, and (9) equivalent wheel diameter. The 86 rules are intuitive, and are particularly useful for production and/or embedded control applications.

Influence of Cutter’s Helix Angle, Workpiece Hardness, Milling Orientation, and MQL in High-Speed Side Milling of AISI D2

Rapid tool wear is a major demerit of high-speed milling (HSM) applied to cutting of hardened steels, especially the AISI D2. This paper presents an attempt to maximize the tool life by experimentally investigating the effects of cutter’s helix angle, workpiece material hardness, milling orientation, and minimum quantity of lubrication upon tool wear in high-speed side milling of AISI D2, using coated carbide cutters. Effects of these four parameters were studied also upon surface roughness. Statistical analysis upon experimental data revealed that milling orientation was the most significant factor for tool life as well as for surface roughness. The paper also describes the mechanisms of wear undergone by the tools, by making use of SEM photographs and EDS microanalysis. The major wear mechanisms were chipping, adhesion, and diffusion.