scholarly journals Surface Texture Analysis of Hardened Shafts after Ceramic Ball Burnishing

Materials ◽  
2019 ◽  
Vol 12 (2) ◽  
pp. 204 ◽  
Author(s):  
Stefan Dzionk ◽  
Bogdan Scibiorski ◽  
Wlodzimierz Przybylski
Keyword(s):  
Hydraulic System ◽  
Hard Turning ◽  
Surface Condition ◽  
Cubic Boron Nitride ◽  
Machining Process ◽  
Machining Parameters ◽  
Ceramic Ball ◽  
Burnishing Process ◽  
Force Range ◽  
Surface Texture Analysis

This article represents the results of testing the surface condition of shafts manufactured by the burnishing process. The shafts with a hardness of approximately 62 HRC (Rockwell C). were burnished with a ceramic ball (Si3N4), where the force range was controlled by the means of a hydraulic system. The machining process consisted of hard turning shafts with cubic boron nitride (CBN) inserts, followed by burnishing with the use of various machining parameters, such as feed and force. The research focused on the examination of burnished surfaces, which was conducted for various structures after hard turning, and with variable burnishing parameters. The results obtained for the decrease of roughness are presented as the relation between the parameters Rat/Rab, which is approximately 2, while for Rpkt/Rpkb, it is around 3.7, respectively. Sat/Sab is around 2, while Spkt/Spkb is around 3.5 (where an index denotes the t-surface after turning, and the index b-surface after burnishing). The structure of the surface after burnishing and turning is described with roughness parameters, as well as with the photographs of the specimen surface, and the bearing area curve.

Hard Turning of AISI D2 Steel by Polycrystalline Cubic Boron Nitride (PCBN)

2015 ◽  
Vol 766-767 ◽  
pp. 649-654
Author(s):  
A. Srithar ◽  
K. Palanikumar ◽  
B. Durgaprasad
Keyword(s):  
Boron Nitride ◽  
Hard Turning ◽  
Cubic Boron Nitride ◽  
Machining Process ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Aisi D2 Steel ◽  
Polycrystalline Cubic Boron Nitride ◽  
Aisi D2 ◽  
D2 Steel

The machining of hard turning is performed on hardened steel in the range of 45 to 68 Rockwell hardness using a variety of tool materials such as Polycrystalline cubic boron nitride (PCBN) , Polycrystalline diamond (PCD) and Cubic boron nitride (CBN). It is an alternative to conventional grinding process is a flexible and effective machining process for hardened metals and hence broadly used in various applications such as dies, moulds, tools, gears, cams, shafts, axles, bearings and forgings. Although the process is performed within small depth of cut and feed rates, estimates to reduce machining time as high as 60 % in hard turning. This paper discusses the importance of hard turning of AISI D2 steel. In this study, Experimental investigations are carried out on conventional lathe using prefixed the cutting conditions. The responses studied in the investigation are cutting forces (Fa, Ft and Fz). The cutting parameters considered for the investigation are cutting speed, feed and depth of cut. The influence of machining parameters on response is studied and presented in detail.

Designing and implementation of a novel online adaptive control with optimization technique in hard turning

2020 ◽  
pp. 095965182095219
Author(s):  
Vahid Pourmostaghimi ◽  
Mohammad Zadshakoyan
Keyword(s):  
Adaptive Control ◽  
Tool Wear ◽  
Hard Turning ◽  
Cutting Tool ◽  
Optimization Technique ◽  
Cutting Parameters ◽  
Numerical Control ◽  
Machining Process ◽  
Machining Parameters ◽  
Optimization Methodology

Determination of optimum cutting parameters is one of the most essential tasks in process planning of metal parts. However, to achieve the optimal machining performance, the cutting parameters have to be regulated in real time. Therefore, utilizing an intelligent-based control system, which can adjust the machining parameters in accordance with optimal criteria, is inevitable. This article presents an intelligent adaptive control with optimization methodology to optimize material removal rate and machining cost subjected to surface quality constraint in finish turning of hardened AISI D2 considering the real condition of the cutting tool. Wavelet packet transform of cutting tool vibration signals is applied to estimate tool wear. Artificial intelligence techniques (artificial neural networks, genetic programming and particle swarm optimization) are used for modeling of surface roughness and tool wear and optimization of machining process during hard turning. Confirmatory experiments indicated that the efficiency of the proposed adaptive control with optimization methodology is 25.6% higher compared to the traditional computer numerical control turning systems.

DEVELOPMENT OF SURFACE ROUGHNESS PREDICTION MODEL FOR HARD TURNING ON AISI D2 STEEL USING CUBIC BORON NITRIDE INSERT

2017 ◽  
Vol 80 (1) ◽  
Author(s):  
Amrifan Saladin Mohruni ◽  
Muhammad Yanis ◽  
Edwin Kurniawan
Keyword(s):  
Surface Roughness ◽  
Boron Nitride ◽  
Feed Rate ◽  
Hard Turning ◽  
Cubic Boron Nitride ◽  
Cutting Speed ◽  
Machining Parameters ◽  
Aisi D2 Steel ◽  
Aisi D2 ◽  
D2 Steel

Hard turning is an alternative to traditional grinding in the manufacturing industry for hardened ferrous alloy material above 45 HRC. Hard turning has advantages such as lower equipment cost, shorter setup time, fewer process steps, greater part geometry flexibility and elimination of cutting fluid. In this study, the effect of cutting speed and feed rate on surface roughness in hard turning was experimentally investigated. AISI D2 steel workpiece (62 HRC) was machined with Cubic Boron Nitride (CBN) insert under dry machining. A 2k-factorial design with 4 centre points as an initial design of experiment (DOE) and a central composite design (CCD) as augmented design were used in developing the empirical mathematical models. They were employed for analysing the significant machining parameters. The results show that the surface roughness value decreased (smoother) with increasing cutting speed. In contrary, surface roughness value increased significantly when the feed rate increased. Optimum cutting speed and feed rate condition in this experiment was 105 m/min and 0.10 mm/rev respectively with surface roughness value was 0.267 µm. Further investigation revealed that the second order model is a valid surface roughness model, while the linear model cannot be used as a predicted model due to its lack of fit significance.

On data-driven nonlinear uncertainty modeling: Methods and application for control-oriented surface condition prediction in hard turning

2020 ◽  
Vol 87 (11) ◽  
pp. 732-741
Author(s):  
Felix Wittich ◽  
Lars Kistner ◽  
Andreas Kroll ◽  
Christopher Schott ◽  
Thomas Niendorf
Keyword(s):  
Hard Turning ◽  
Surface Condition ◽  
Gaussian Process Regression ◽  
Uncertainty Modeling ◽  
Data Driven ◽  
Machining Parameters ◽  
Robust Model ◽  
Bounded Error ◽  
Data Driven Modeling ◽  
Takagi Sugeno

AbstractIn this article, two data-driven modeling approaches are investigated, which allow an explicit modeling of uncertainty. For this purpose, parametric Takagi-Sugeno multi-models with bounded-error parameter estimation and nonparametric Gaussian process regression are applied and compared. These models can for instance be used for robust model-based control design. As an application, the prediction of residual stresses during hard turning depending on the machining parameters and the initial hardness is considered.

Analysis and Fabrication of a Mechanical Quick-Stop for Research on Chip Formation in Hard Turning Process

2019 ◽  
Vol 889 ◽  
pp. 87-94
Author(s):  
Nguyen Thi Quoc Dung
Keyword(s):  
Chip Formation ◽  
Hard Turning ◽  
Manufacturing Industry ◽  
Metal Cutting ◽  
Cutting Speed ◽  
Cutting Process ◽  
Machining Process ◽  
Machining Parameters ◽  
Machining Processes ◽  
On Chip

Metal cutting is one of the most important machining processes in manufacturing industry. Thorough understanding of metal cutting process facilitates the optimization in selection of cutting tools and machining parameters. There are several methods used for studying phenomena in metal cutting process. Using a quick-top device is an efficient technique for investigation cutting process in which cutting action is stopped so suddenly that the “froze” specimen called the chip root honestly depicts what happened during cutting action. Design strategies of a quick-stop are accelerating cutting tool away from the workpiece or decelerating the workpiece remaining in engagement with the tool. Operation of a quick-stop device can be either mechanically or by explosive. Quick-stop devices can be utilized for various types of machining processes such as: turning, milling, drilling. This paper described the analysis, fabrication, and testing of a quick-stop device which is used for researching on chip formation in hard turning. This device has simple and safe operation which utilizes spring forces to retract the tool from workpiece during cutting. The results of performance at cutting speed of 283 m/min show that the separation distance is quite small, less than 0.2mm so that the deformations on the root chip are close to that while actual machining process. This indicates that the device has satisfied the requirements of an equipment for studying on chip formation.

Experimental Investigation of Hard Turning Mechanisms by PCBN Tooling Embedded Micro Thin Film Thermocouples

2013 ◽  
Vol 135 (4) ◽  
Author(s):  
Linwen Li ◽  
Bin Li ◽  
Xiaochun Li ◽  
Kornel F. Ehmann
Keyword(s):  
Thin Film ◽  
Hard Turning ◽  
Cubic Boron Nitride ◽  
Cutting Tools ◽  
Cutting Temperature ◽  
Chip Morphology ◽  
Machining Process ◽  
Cutting Insert ◽  
Thin Film Thermocouples ◽  
Cutting Zone

Temperature-distribution measurements in cutting tools during the machining process are extremely difficult and remain an unresolved problem. In this paper, cutting temperature distributions were measured by thin film thermocouples (TFTCs) embedded into polycrystalline cubic boron nitride (PCBN) cutting inserts in the immediate vicinity of the tool-chip interface. The embedded TFTC array provides temperature measurements with a degree of spatial resolution (100 μm) and dynamic response (150 ns) that is not possible with currently employed methods due to the micro-scale junction size of the TFTCs. Using these measurements during hard turning, steady-state, dynamic, as well as chip morphology and formation process analyses were performed based on the cutting temperature and cutting force variations in the cutting zone. It has been shown that the temperature changes in the cutting zone depend on the shearing band location in the chip and the thermal transfer rate from the heat generation zone to the cutting tool. Furthermore, it became evident that the material flow stress and the shearing bands greatly affect not only the chip formation morphology but also the cutting temperature field distributions in the cutting zone of the cutting insert.

Experimental Investigation and Analysis on Hard Turning of AISI D2 Steel Using Coated Carbide Insert

2014 ◽  
Vol 984-985 ◽  
pp. 154-158 ◽  
Author(s):  
A. Srithar ◽  
K. Palanikumar ◽  
B. Durgaprasad
Keyword(s):  
Feed Rate ◽  
Hard Turning ◽  
Cutting Conditions ◽  
Machining Process ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Study Results ◽  
Aisi D2 ◽  
Coated Carbide ◽  
Carbide Insert

Hard turning is one of the important operations for hardened steels and it has more benefits than grinding such as cycle time, process flexibility, and better surface finish at significantly better material removal rate and lesser environment issues. Although the machining process is performed with low feed rate and depths of cut, it results lesser machining time as compared with conventional turning. This paper discusses the machining performance tests on the AISI D2 hardened steel to 64 HRC were carried out using chemical vapor deposition ( cvd) coated carbide insert. Experiments are carried out on lathe using the cutting conditions prefixed. The responses studied in the investigation are cutting forces (fx, fy, and fz) and. The cutting parameters considered for the investigation are feed rate, depth of cut and cutting speed. The performance of machining parameters on response is studied and presented in detail. In chip morphology study results different formation and types of chips operating under various cutting conditions.

Performance Analysis on Eco-friendly Machining of Ti6Al4V using Powder Mixed with Different Dielectrics in WEDM

2020 ◽  
Vol 17 (3) ◽  
pp. 8128-8139
Author(s):  
S. Chakraborty ◽  
S. Mitra ◽  
D. Bose
Keyword(s):  
Metal Removal ◽  
Removal Rate ◽  
Machining Process ◽  
Process Efficiency ◽  
Machining Parameters ◽  
Dielectric Fluids ◽  
High Emission ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Wedm Process

The recent scenario of modern manufacturing is tremendously improved in the sense of precision machining and abstaining from environmental pollution and hazard issues. In the present work, Ti6Al4V is machined through wire EDM (WEDM) process with powder mixed dielectric and analyzed the influence of input parameters and inherent hazard issues. WEDM has different parameters such as peak current, pulse on time, pulse off time, gap voltage, wire speed, wire tension and so on, as well as dielectrics with powder mixed. These are playing an essential role in WEDM performances to improve the process efficiency by developing the surface texture, microhardness, and metal removal rate. Even though the parameter’s influencing, the study of environmental effect in the WEDM process is very essential during the machining process due to the high emission of toxic vapour by the high discharge energy. In the present study, three different dielectric fluids were used, including deionised water, kerosene, and surfactant added deionised water and analysed the data by taking one factor at a time (OFAT) approach. From this study, it is established that dielectric types and powder significantly improve performances with proper set of machining parameters and find out the risk factor associated with the PMWEDM process.

Surface Roughness and Cutting Force Components Evaluation in Hard Turning by Differently Shaped Cutting Tools

2016 ◽  
Vol 862 ◽  
pp. 26-32 ◽  
Author(s):  
Michaela Samardžiová
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Hard Turning ◽  
Cutting Tool ◽  
Single Point ◽  
Machining Process ◽  
Tool Geometry ◽  
Machined Surface ◽  
Cutting Force Components ◽  
Force Components

There is a difference in machining by the cutting tool with defined geometry and undefined geometry. That is one of the reasons of implementation of hard turning into the machining process. In current manufacturing processes is hard turning many times used as a fine finish operation. It has many advantages – machining by single point cutting tool, high productivity, flexibility, ability to produce parts with complex shapes at one clamping. Very important is to solve machined surface quality. There is a possibility to use wiper geometry in hard turning process to achieve 3 – 4 times lower surface roughness values. Cutting parameters influence cutting process as well as cutting tool geometry. It is necessary to take into consideration cutting force components as well. Issue of the use of wiper geometry has been still insufficiently researched.

Development of Machining Method for Micromold

2010 ◽  
Vol 154-155 ◽  
pp. 310-313
Author(s):  
Xue Feng Bi ◽  
Jin Sheng Wang ◽  
Jia Shun Shi ◽  
Ya Dong Gong
Keyword(s):  
Tool Path ◽  
Simulation Software ◽  
Machining Process ◽  
Machining Parameters ◽  
Machining Simulation ◽  
Post Process ◽  
Micro Parts ◽  
G Code ◽  
Micro Machine ◽  
3D Software

Micromold manufacturing technology is very important for the mass production of micro parts. In this paper, modeling of micromold is established in 3D software firstly. The 3D modeling is input into machining simulation software Master CAM to simulate machining process. The machining parameters and cutting tool path are optimized in machining simulation. Machining G code of micromold obtained from post-process program of Master CAM is input into HMI system of Micro Machine Tool (MMT), and hence the micromold will be machined precisely in MMT.

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