Statistical analysis of surface roughness and cutting forces using response surface methodology in hard turning of AISI 52100 bearing steel with CBN tool

The present work concerns an experimental study of hard turning with CBN tool of AISI 52100 bearing steel, hardened at 64 HRC. The main objectives are firstly focused on delimiting the hard turning domain and investigating tool wear and forces behaviour evolution versus variations of workpiece hardness and cutting speed. Secondly, the relationship between cutting parameters (cutting speed, feed rate and depth of cut) and machining output variables (surface roughness, cutting forces) through the response surface methodology (RSM) are analysed and modeled. The combined effects of the cutting parameters on machining output variables are investigated while employing the analysis of variance (ANOVA). The quadratic model of RSM associated with response optimization technique and composite desirability was used to find optimum values of machining parameters with respect to objectives (surface roughness and cutting force values). Results show how much surface roughness is mainly influenced by feed rate and cutting speed. Also, it is underlined that the thrust force is the highest of cutting force components, and it is highly sensitive to workpiece hardness, negative rake angle and tool wear evolution. Finally, the depth of cut exhibits maximum influence on cutting forces as compared to the feed rate and cutting speed.     

3D modeling of residual stresses induced in finish turning of an AISI304L stainless steel

This paper addresses the development of a new methodology predicting residual stresses induced in finish turning of a AISI304L stainless steel. A hybrid approach combining experimental results and a numerical model is applied. The model simulates the residual stresses generation by applying equivalent thermo-mechanical loadings onto the machined surface without modeling the chip removal process, which enables rapid calculation. The shape and the intensity of equivalent thermo-mechanical loadings are identified through experimental measurements. Friction tests enable to model the thermal and mechanical loadings along the tool-workmaterial interface. Orthogonal cutting tests provide thermal and mechanical loadings below the primary and third shear zone. This model has already been presented in several papers, but only in a 2D configuration. The objective of this paper is to transfer this hybrid approach into a 3D configuration, which is closer to a concrete longitudinal turning operation. Based on this new model, the paper aims at investigating the interactions between each revolution. It is shown that around five revolutions are necessary to reach a steady state. Finally numerical results are compared with experimental measurements obtained by X-Ray diffraction. It is shown that residual stresses cannot be considered as homogeneous over the surface due to tool's feed. Additionally, the X-Ray beam is much too large to be able to quantify this heterogeneity. Based on average numerical values coherent with average values obtained by X-Ray diffraction, it is shown that the numerical model provides consistent results compared to experimental measurements for a large range of cutting speed and feed.     

A 3D modeling strategy to predict efficiently cutting tool wear in longitudinal turning of AISI 1045 steel

This work presents a numerical strategy to predict efficiently cutting tool wear in longitudinal turning. The full 3D cutting tool is discretized in elementary 2D sections. A FE based procedure is developed to compute in parallel the local contact pressure and sliding velocity along each section and update the tool profiles based on a tribologically identified wear equation. Results are merged to generate the 3D worn tool geometry while an iterative scheme is applied to achieve long simulated cutting time. Experimental cutting tests shown that a good agreement can be achieved in a reasonable computation time without any tuning parameter.     

Effects of minimum quantity lubrication on turning AISI 9310 alloy steel using vegetable oil-based cutting fluid

This paper presents the effects of minimum quantity lubrication (MQL) by vegetable oil-based cutting fluid on the turning performance of low alloy steel AISI 9310 as compared to completely dry and wet machining in terms of chip–tool interface temperature, chip formation mode, tool wear and surface roughness. The minimum quantity lubrication was provided with a spray of air and vegetable oil. MQL machining was performed much superior compared to the dry and wet machining due to substantial reduction in cutting zone temperature enabling favorable chip formation and chip–tool interaction. It was also seen from the results that the substantial reduction in tool wears resulted in enhanced the tool life and surface finish. Furthermore, MQL provides environment friendliness (maintaining neat, clean and dry working area, avoiding inconvenience and health hazards due to heat, smoke, fumes, gases, etc. and preventing pollution of the surroundings) and improves the machinability characteristics.     

Predictive modeling of surface roughness and tool wear in hard turning using regression and neural networks

In machining of parts, surface quality is one of the most specified customer requirements. Major indication of surface quality on machined parts is surface roughness. Finish hard turning using Cubic Boron Nitride (CBN) tools allows manufacturers to simplify their processes and still achieve the desired surface roughness. There are various machining parameters have an effect on the surface roughness, but those effects have not been adequately quantified. In order for manufacturers to maximize their gains from utilizing finish hard turning, accurate predictive models for surface roughness and tool wear must be constructed. This paper utilizes neural network modeling to predict surface roughness and tool flank wear over the machining time for variety of cutting conditions in finish hard turning. Regression models are also developed in order to capture process specific parameters. A set of sparse experimental data for finish turning of hardened AISI 52100 steel obtained from literature and the experimental data obtained from performed experiments in finish turning of hardened AISI H-13 steel have been utilized. The data sets from measured surface roughness and tool flank wear were employed to train the neural network models. Trained neural network models were used in predicting surface roughness and tool flank wear for other cutting conditions. A comparison of neural network models with regression models is also carried out. Predictive neural network models are found to be capable of better predictions for surface roughness and tool flank wear within the range that they had been trained.Predictive neural network modeling is also extended to predict tool wear and surface roughness patterns seen in finish hard turning processes. Decrease in the feed rate resulted in better surface roughness but slightly faster tool wear development, and increasing cutting speed resulted in significant increase in tool wear development but resulted in better surface roughness. Increase in the workpiece hardness resulted in better surface roughness but higher tool wear. Overall, CBN inserts with honed edge geometry performed better both in terms of surface roughness and tool wear development.     

Multi-physics modeling and simulations of surface microstructure alteration in hard turning

Surface microstructure alteration is a major concern in industry to implement hard turning for bearing steels. The formation of white layer in hard turning can be attributed to two main factors: thermally driven phase transformation and mechanical grain refinement due to severe plastic deformation. The purpose of this study is to quantitatively disseminate the underlying mechanisms through prediction of the microstructure change using a multi-physics model, which considers both phase transformation and grain refinement. 3D hard turning simulations are undertaken via AdvantEdge FEM software incorporating these two mechanisms as user-defined subroutines to investigate the surface microstructure alteration for AISI 52100 steel. Comparisons with the experimental data at various cutting conditions prove that the proposed model can accurately predict the critical surface microstructural attributes such as phase compositions, grain size, microhardness, and residual stress during hard turning of AISI 52100 steel.     

A multivariate robust parameter design approach for optimization of AISI 52100 hardened steel turning with wiper mixed ceramic tool

This paper presents an experimental study of AISI 52100 hardened steel turned with wiper mixed ceramic (Al₂O₃ + TiC) inserts coated with TiN, using Multivariate Robust Parameter Design (MRPD). The main characteristic of this new optimization approach consists of considering both controllable (x_i) and noise (z_i) variables of the hard turning process to find out the parameter levels which minimize the distance of each response (y_i) from its respective targets (T_i) while keeps each variance caused by the noise variables as low as possible. Using a crossed array, a response surface design formed by cutting speed (Vc), feed rate (f) and depth of cut (d) is submitted to the influence of four scenarios built with an 2² full factorial design of two noise factors — workpiece hardness decreasing (Z₁) and tool flank wear (Z₂). This experimental arrangement allows the generating of mean, variance and mean square error (MSE) of five surface roughness parameters (Ra, Rz, Ry, Rt and Rq). As these responses are highly correlated, to extract and employ this information, Principal Component Analysis (PCA) was used. Adopting the Multivariate Mean Square Error (MMSE) as optimization criteria, a robust solution could be found. Theoretical and experimental results were convergent and confirmed. With Vc = 199.9 m/min, f = 0.191 mm/rev and d = 0.190 mm, the five surface roughness parameters and respective variances were minimal, with better results than those obtained with individual optimization.     

Surface finish generated in hard turning of quenched alloy steel parts using conventional and wiper ceramic inserts

Significant progress has already been achieved in green manufacturing including dry and hard, often high-speed, machining technologies. For instance, the demand for higher productivity has resulted in the wider application of ceramic and PCBN tools with special multi-radii (wiper) geometry. This paper reports some important characteristics of the surface roughness produced in the turning of a hardened low-chromium alloy steel using mixed alumina–titanium carbon (TiC) ceramic cutting tools equipped with both conventional and wiper inserts. The characteristic geometrical features of surfaces obtained in both these turning operations have been assessed by means of representative two-dimensional (2D) surface roughness parameters, and some 3D visualizations, which allowed more complete characterization of the surface topography and prediction of its service properties. Results show that keeping equivalent feed rates, i.e. 0.1 mm/rev for conventional and 0.2 mm/rev for wiper tools, the surfaces obtained have similar 3D height roughness parameters, and comparable values of skew and kurtosis. At defined cutting parameters, surfaces produced by wiper tools contain blunt peaks with distinctly smaller slopes resulting in better bearing properties. Only marginal changes of Ra parameter were recorded during 15 min machining trials.     

Evaluation of layer adhered on PCBN tools during turning of AISI D2 steel

Polycrystalline cubic boron nitride (PCBN) tools have high abrasion resistance and are thus suitable for application in the machining of steels with a high volume fraction of primary carbides in their microstructure. These tools are usually applied in the machining of steels with hardness above 45–50 HRC and in the case of application to steels with hardness below 45 HRC, the formation of an adhered layer on the rake face of the tools often occurs. This paper reports a study on the impact of the layer adhered on PCBN tools during the turning of AISI D2 steel, with 35 and 50 HRC. The microhardness and microstructure of the adhered material were determined, as well as the tool wear based on volumetric wear parameters. The layer adhered on the PCBN tool rake face has the same chemical elements as the machined steel alloy. Its microstructure is oriented in the direction of the chip flow and the primary carbides were fragmented. For the sample with 35 HRC the amount of material adhered (W_AM) on the rake face of the PCBN tool was approximately 360% higher than the steel with 50 HRC. The material layer adhered on the PCBN tool rake surface in the case of the 35 HRC steel acts as an edge (assuming the cutting function), while for the 50 HRC steel, the adhered layer intensifies the adhesion wear mechanism through spalling on the tool rake face. The results obtained provide important information for the selection of materials and grades for the development of new cutting tools.     

Cryogenic machining as an alternative turning process of normalized and hardened AISI 52100 bearing steel

Environmental and health friendly technologies with economic justification have nowadays an increasing importance in global industrial trends. Idea of global sustainable development dictates cleaner and less health hazardous machining processes. With these limitations in mind, the main issue is now to change the way mechanical components are being machined and move to alternative technologies that could moreover increase the machining performance. Cryogenic machining is one possibility to reach this goal. It consists of a system for cutting (turning, milling, etc.) assisted by liquid nitrogen, which enables a clean process with possible lower production costs and higher productivity. This article presents the results of turning hardened and normalized bearing steel AISI 52100 (DIN 100Cr6), comparing conventional flood and dry with cryogenic machining. Turning results show drastic improvements in tool lifetime (up to 370%) for cryogenic machining of normalized bearing steel 100Cr6 and reduction of thermal residual stress inducements in case of hardened bearing steel 100Cr6, while tool life is also extended.     

Residual stresses in surface layer after dry and MQL turning of AISI 316L steel

Residual stresses in the surface layer exert a significant impact on functional aspects of machined parts. Their type and value depend on the workpiece and tool material properties, cutting parameters and cooling and lubrication conditions in the tool-chip-machined surface interface. As the effects of material properties and cutting parameters have been widely studied, the influence of cooling and lubrication conditions, especially minimum quantity lubrication (MQL) on the surface layer residual stresses and the relationships between them have not been investigated. In this paper the effects of dry, MQL cutting and cutting with emulsion conditions together with cutting parameters on residual stresses after turning AISI 316L steel were investigated. X-ray diffraction method was used for measuring superficial residual stresses in the cutting (hoop) and feed (axial) directions. Tensile residual stresses were detected in both directions and the values in the cutting direction turned out to be higher than in the feed direction. The effects of cooling and lubrication conditions largely depend on the selected cutting parameters, whose influence is linked to the cutting zone cooling and lubrication mode. Elaborated regression functions allow calculation and optimization of residual stresses in turning AISI 316L steel, depending on cooling and lubrication conditions as well as cutting parameters.     

Nonlinear constitutive behavior of soft and hard PZT: experiments and modeling

This work characterizes and models the nonlinear inelastic behavior of lead zirconate–titanate (PZT) ceramics. A detailed investigation of the hysteresis loop of the stress–strain curve shows that the process of ferroelastic non-180° polarization switching and of switching saturation are, respectively, a smooth softening process and a gradual hardening process. The inflection point in the curve is found to be a boundary point that distinguishes the transition from a softening process to a hardening one. Based on underlying physical mechanisms, this nonlinear behavior is simulated by a mechanical model, consisting of several parallel-arranged Maxwell chains with each chain taking a main role in a different, successive stage of the switching process. Each chain includes a nonlinear spring and a frictional slider. The generalized displacement of the slider, indicating an internal variable, is introduced to describe the local process of the cooperative switching of the corresponding grain group. The hardening and softening processes are controlled by variations of stiffness of the nonlinear springs. Furthermore, the observed similarities between the hysteresis loop of the stress–strain curve and that of stress–electric displacement curve are used to develop an equivalent stress concept and to formulate constitutive laws for PZT ceramics. Comparisons between the experimental hysteresis loops and those calculated by the proposed model show satisfactory agreement for both hard PZT and C5800 and soft C5500.     

White layer formation in hard turning of H13 tool steel at high cutting speeds using CBN tooling

White layers formed during machining have negative effects on surface finish and fatigue strength of products. The white layer is generally a hard phase and leads to the surface becoming brittle causing crack permeation and product failure. This is a major concern with respect to service performance especially in the aerospace and automotive industries. Numerous authors have investigated the formation of white layer under different manufacturing processes. In turning, it was suggested that the white layer structure is a martensitic phase whose formation is correlated to tool wear. Past studies have tended to concentrate on the formation of white layers at conventional cutting speeds, but never examined the formation at high cutting speeds. This paper reports on an investigation of white layer formation for wide range of cutting speeds in hard turning of 54-56 HRC H13 tool steel. The specimens were analysed using a micro hardness tester, SEM with EDAX software and Electron Micro-Probe. In addition tool wear and workpiece temperature were studied. The machined surface showed an increase in hardness with respect to the bulk material. Compositional gradients were noted for the white layer in terms of depletion of the elements iron and chromium coupled with an enrichment of carbon and oxygen content. The results showed that despite tool wear increasing with cutting speed, white layer depth and hardness actually reduced. This finding suggests that there may not be a direct relationship between white layer formation and wear, the correlation maybe linked to wear mode.     

Comparison of rotational turning and hard turning regarding surface generation

In this paper, two different turning processes namely rotational turning and hard turning are compared to each other regarding surface generation aspects. By experiments it is shown that, with higher feed rates, rotational turning yields same surface quality as hard turning. Feed rates can be chosen six times higher in rotational turning than in conventional hard turning without losses in the surface roughness quality. Also experiments reveal that the tool wear in rotational turning has a beneficial effect on the surface roughness. A corresponding explanation model is thereby presented which takes the specific tool/work piece engagement in rotational turning into account. Furthermore, it is shown that rotational turning has negative effects on the surface integrity. The phase transformation zones (“white layers”) are thicker in rotational turned parts than in hard turned parts. Also the level of tensile residual stress in rotational turning is higher than in hard turning. Both effects are probably caused by high thermal material loads in rotational turning due to increased friction. However, the results of this paper show that rotational turning has a high potential to become an efficient alternative to hard turning, especially when it comes to large scale production of simple shaped parts.     

SAE6150盘条表面花斑缺陷原因分析及改进措施

针对客户反馈的SAE6150工具钢表面花斑形貌问题,对其宏观形貌和成分进行了检测分析,发现产生花斑形貌的直接原因是由于原料盘条表面存在不平整的微凹坑,平面和凹坑面在光的反射作用下呈现明暗不同的视觉色差,从而形成肉眼可见的花斑形貌。微凹坑产生的原因是盘条在轧制过程中表面残留氧化铁皮轧制压入而造成的;另外,盘条拉拔前的鳞皂化处理致使大量皂化液进入凹坑凝固后形成塞积物,盘条拉拔后凹坑难以去除而形成黑白相间的花斑形貌。为此,提出了相应改进措施,从根本上解决了热轧盘条表面缺陷问题。     

Accurate modeling and prediction of surface roughness by computer vision in turning operations using an adaptive neuro-fuzzy inference system

Modeling and prediction of surface roughness of a workpiece by computer vision in turning operations play an important role in the manufacturing industry. This paper proposes a method using an adaptive neuro-fuzzy inference system (ANFIS) to accurately establish the relationship between the features of surface image and the actual surface roughness, and consequently can effectively predict surface roughness using cutting parameters (cutting speed, feed rate, and depth of cut) and gray level of the surface image. Experimental results show that the proposed ANFIS-based method outperforms the existing polynomial network-based method in terms of modeling and prediction accuracy.     

Modification of surface finish produced by hard turning using superfinishing and burnishing operations

In this study the surface finish produced by hard turning of a 41Cr4 low-alloy steel quenched to about 60 HRC hardness, using mixed Al₂O₃-TiC ceramic inserts, was subsequently modified by superfinishing and multipass burnishing operations. In the case of hard turning surfaces were produced by conventional and Wiper cutting tool inserts. The main goal of this study was to examine how additional abrasive and non-removal technological operations change 2D and 3D roughness parameters and enhance service properties of the machined surfaces. It was documented that both superfinishing and burnishing operations allow to obtain smoother surfaces with lower surface roughness and better bearing characteristics.     

Characterization of the sensitization degree in the AISI 304 stainless steel using spectral analysis and conventional ultrasonic techniques

Specimens of AISI 304 stainless steels exposed to sensitization and carbide solution heat treatment employing ultrasonic testing have been evaluated. The study involved measurements of the longitudinal wave velocity, attenuation and spectral analysis. Despite the large size difference between the ultrasonic wave length and the precipitated carbides, the results showed a clear attenuating effect in the sensitized specimens. This effect suggests a relation between carbide precipitation in the material and the attenuation coefficient of the ultrasonic wave. The attenuation increase is mainly attributed to the continuous distribution and possible coalescence of the carbide along the grain boundaries. Power spectra exhibit an increase of the amplitude at specific frequencies in specimens with the longest sensitization times. Ultrasonic velocity measurements did not provide significant information in order to predict any sensitization grade of the evaluated materials. The combined assessment by spectral analysis and attenuation measurements is discussed.     

基于单片机的双头车床控制系统设计

本文分析了双头车床控制系统的特点,提出了基于单片机构成的嵌入式控制方案,采用步进电动机实现对刀具的拖动定位,简化了控制系统结构。为了提高刀具的定位精度,通过编写相应的控制程序,实现了步进电动机的自动加减速控制。