The Experts below are selected from a list of 31218 Experts worldwide ranked by ideXlab platform
Peng Zhuang - One of the best experts on this subject based on the ideXlab platform.
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hybrid modeling with finite element and statistical methods for residual stress prediction in peripheral milling of titanium alloy ti 6al 4v
International Journal of Mechanical Sciences, 2016Co-Authors: Dong Yang, Zhanqiang Liu, Xiaoping Ren, Peng ZhuangAbstract:Residual stresses and their optimization in terms of machining and service performance represent both a serious barrier to better materials processing, usage, and an opportunity in terms of surface engineering and life extension. It is therefore that there is a considerable amount of researches on developing predictive models for machining-induced residual stress such as analytical model, computational/numerical model. However, these developed models for residual stress prediction are operational complexity, time-consuming and Low prediction efficiency. For the purpose of avoiding the large number of time-consuming experimental work, a hybrid technique combining the finite element method and the statistical model is developed in this paper. On the basis of the simulation residual stress, the exponentially damped cosine function is fitted using a particle swarm optimization method. It was found that values of fitting accuracy R2 are ranging from 81.7 to 99.2% in peripheral milling of titanium alloy Ti-6Al-4V. Sensitivity to cutting speed and Feed Rate of four key features of the residual stress profile including surface residual stress (σr,Sur), compressive stress peak value (σC,ax) and location (hr0), response depth (hry) are investigated. The four key features showed the similar sensitivity to cutting speed and Feed Rate. Performance of σr,Sur changed from compressive to tensile, while σC,ax decreased, hr0 and hry increased with the increase of cutting speed and Feed Rate. However, the trend was not significant at Low Feed Rate. Using the proposed procedure, the optimum cutting conditions could be obtained to control the residual stress of milling titanium alloy Ti-6Al-4V and also other metals.
G L Samuel - One of the best experts on this subject based on the ideXlab platform.
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some studies on hard turning of aisi 4340 steel using multilayer coated carbide tool
Measurement, 2012Co-Authors: R Suresh, S Basavarajappa, G L SamuelAbstract:Abstract Hard turning with multilayer coated carbide tool has several benefits over grinding process such as, reduction of processing costs, increased productivities and improved material properties. The objective was to establish a correlation between cutting parameters such as cutting speed, Feed Rate and depth of cut with machining force, power, specific cutting force, tool wear and surface roughness on work piece. In the present study, performance of multilayer hard coatings (TiC/TiCN/Al 2 O 3 ) on cemented carbide substRate using chemical vapor deposition (CVD) for machining of hardened AISI 4340 steel was evaluated. An attempt has been made to analyze the effects of process parameters on machinability aspects using Taguchi technique. Response surface plots are geneRated for the study of interaction effects of cutting conditions on machinability factors. The correlations were established by multiple linear regression models. The linear regression models were validated using confirmation tests. The analysis of the result revealed that, the optimal combination of Low Feed Rate and Low depth of cut with high cutting speed is beneficial for reducing machining force. Higher values of Feed Rates are necessary to minimize the specific cutting force. The machining power and cutting tool wear increases almost linearly with increase in cutting speed and Feed Rate. The combination of Low Feed Rate and high cutting speed is necessary for minimizing the surface roughness. Abrasion was the principle wear mechanism observed at all the cutting conditions.
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machinability investigations on hardened aisi 4340 steel using coated carbide insert
International Journal of Refractory Metals & Hard Materials, 2012Co-Authors: R Suresh, V N Gaitonde, S Basavarajappa, G L SamuelAbstract:Abstract The hard turning process with advanced cutting tool materials has several advantages over grinding such as short cycle time, process flexibility, compatible surface roughness, higher material removal Rate and less environment problems without the use of cutting fluid. However, the main concerns of hard turning are the cost of expensive tool materials and the effect of the process on machinability characteristics. The poor selection of the process parameters may cause excessive tool wear and increased work surface roughness. Hence, there is a need to study the machinability aspects in high-hardened components. In this work, an attempt has been made to analyze the influence of cutting speed, Feed Rate, depth of cut and machining time on machinability characteristics such as machining force, surface roughness and tool wear using response surface methodology (RSM) based second order mathematical models during turning of AISI 4340 high strength Low alloy steel using coated carbide inserts. The experiments were planned as per full factorial design (FFD). From the parametric analysis, it is revealed that, the combination of Low Feed Rate, Low depth of cut and Low machining time with high cutting speed is beneficial for minimizing the machining force and surface roughness. On the other hand, the interaction plots suggest that employing Lower cutting speed with Lower Feed Rate can reduce tool wear. Chip morphology study indicates the formation of various types of chips operating under several cutting conditions.
Safian Sharif - One of the best experts on this subject based on the ideXlab platform.
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effect of machining parameters on tool wear and hole quality of aisi 316l stainless steel in conventional drilling
Procedia Manufacturing, 2015Co-Authors: Ahmad Zubair Sultan, Safian Sharif, Denni KurniawanAbstract:Abstract This paper focuses on the effect of drilling parameters on tool wear and hole quality in terms of diameter error, roundness, cylindricity, and surface roughness. In this work, the drilling was conducted using uncoated carbide tool with diameter of 4 ± 0.01 mm with point angle of 135° and helix angle of 30°. The drilling was done at different levels of spindle speed (18 and 30 mmin-1) and Feed Rate (0.03, 0.045 and 0.06 mmrev-1). Austenitic stainless steel AISI 316L was the workpiece material. Comparatives analysis was done on hole diameter, roundness, cylindricity, and surface roughness of the drilled holes by experimentation. From the result, the hole quality characteristics are mostly influenced by cutting speed and Feed Rate. An exception was for circularity error where a two tail t-test for circularity error indicates that cutting speed and Feed Rate give no significant influence on circularity error. As the cutting speed increases, the surface roughness decreases (1.09 μm). Contrary, when the Feed Rate increases, the surface roughness value increases as well. For cylindricity error, Lower cutting speed and Lower Feed Rate will give better result. In terms of diameter error, Feed Rate influences more than cutting speed. Minimum diameter error was achieved when Low cutting speed and Low Feed Rate were employed.
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mathematical modeling of cutting force in milling of medium density fibreboard using response surface method
Advanced Materials Research, 2012Co-Authors: Norazmein Abdul Raman, Safian Sharif, S IzmanAbstract:This paper reports on the development of predicted mathematical model for cutting force (Fc) during side milling of medium density fiberboard (MDF) using uncoated carbide insert. Box-Behnken design (BBD) of experiment, coupled with response surface method (RSM) were employed to establish the cutting force model. Evaluation on the effects and interactions of the machining variables on the cutting force were carried out. The machining variables involved include spindle speed, Feed Rate, routing width and were denoted by A, B and C respectively. Statistical analysis conducted on the experimental results indicated that the mathematical model for cutting force was adequate within the limits of factors being investigated. After eliminating the insignificant factors or model terms in the reduced model, it was found that factors A, B, C, B2 (second order of B), C2 (second order of C), were the most significant factors affecting the cutting force. BC (interaction of B and C) and AC (interaction of A and C) are the subsequent significant factors. Three-dimensional plots displaying the interactions between these significant factors were presented. The reduced model was then verified experimentally and statistically using ANOVA. It was evident that Box-Behnken design proved to be an efficient tool in identifying and constructing maps of interactions between the significant factors. Experimental results showed that Lower cutting force can be obtained by employing higher cutting speed, Low Feed Rate and Lower routing width when side milling MDF using uncoated carbide insert.
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prediction of surface roughness in the end milling machining using artificial neural network
Expert Systems With Applications, 2010Co-Authors: Azlan Mohd Zain, Habibollah Haron, Safian SharifAbstract:This paper presents the ANN model for predicting the surface roughness performance measure in the machining process by considering the Artificial Neural Network (ANN) as the essential technique for measuring surface roughness. A revision of several previous studies associated with the modelling issue is carried out to assess how capable ANN is as a technique to model the problem. Based on the studies conducted by previous researchers, the abilities and limitations of the ANN technique for predicting surface roughness are highlighted. Utilization of ANN-based modelling is also discussed to show the required basic elements for predicting surface roughness in the milling process. In order to investigate how capable the ANN technique is at estimating the prediction value for surface roughness, a real machining experiment is referred to in this study. In the experiment, 24 samples of data concerned with the milling operation are collected based on eight samples of data of a two-level DOE 2^k full factorial analysis, four samples of centre data, and 12 samples of axial data. All data samples are tested in real machining by using uncoated, TiAIN coated and SN"T"R coated cutting tools of titanium alloy (Ti-6A1-4V). The Matlab ANN toolbox is used for the modelling purpose with some justifications. Feedforward backpropagation is selected as the algorithm with traingdx, learngdx, MSE, logsig as the training, learning, performance and transfer functions, respectively. With three nodes in the input layer and one node in the output layer, eight networks are developed by using different numbers of nodes in the hidden layer which are 3-1-1, 3-3-1, 3-6-1, 3-7-1, 3-1-1-1, 3-3-3-1, 3-6-6-1 and 3-7-7-1 structures. It was found that the 3-1-1 network structure of the SN"T"R coated cutting tool gave the best ANN model in predicting the surface roughness value. This study concludes that the model for surface roughness in the milling process could be improved by modifying the number of layers and nodes in the hidden layers of the ANN network structure, particularly for predicting the value of the surface roughness performance measure. As a result of the prediction, the recommended combination of cutting conditions to obtain the best surface roughness value is a high speed with a Low Feed Rate and radial rake angle.
Dong Yang - One of the best experts on this subject based on the ideXlab platform.
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hybrid modeling with finite element and statistical methods for residual stress prediction in peripheral milling of titanium alloy ti 6al 4v
International Journal of Mechanical Sciences, 2016Co-Authors: Dong Yang, Zhanqiang Liu, Xiaoping Ren, Peng ZhuangAbstract:Residual stresses and their optimization in terms of machining and service performance represent both a serious barrier to better materials processing, usage, and an opportunity in terms of surface engineering and life extension. It is therefore that there is a considerable amount of researches on developing predictive models for machining-induced residual stress such as analytical model, computational/numerical model. However, these developed models for residual stress prediction are operational complexity, time-consuming and Low prediction efficiency. For the purpose of avoiding the large number of time-consuming experimental work, a hybrid technique combining the finite element method and the statistical model is developed in this paper. On the basis of the simulation residual stress, the exponentially damped cosine function is fitted using a particle swarm optimization method. It was found that values of fitting accuracy R2 are ranging from 81.7 to 99.2% in peripheral milling of titanium alloy Ti-6Al-4V. Sensitivity to cutting speed and Feed Rate of four key features of the residual stress profile including surface residual stress (σr,Sur), compressive stress peak value (σC,ax) and location (hr0), response depth (hry) are investigated. The four key features showed the similar sensitivity to cutting speed and Feed Rate. Performance of σr,Sur changed from compressive to tensile, while σC,ax decreased, hr0 and hry increased with the increase of cutting speed and Feed Rate. However, the trend was not significant at Low Feed Rate. Using the proposed procedure, the optimum cutting conditions could be obtained to control the residual stress of milling titanium alloy Ti-6Al-4V and also other metals.
H H Hassan - One of the best experts on this subject based on the ideXlab platform.
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application of taguchi method in the optimization of end milling parameters
Journal of Materials Processing Technology, 2004Co-Authors: Jaharah A Ghani, I A Choudhury, H H HassanAbstract:Abstract This paper outlines the Taguchi optimization methodology, which is applied to optimize cutting parameters in end milling when machining hardened steel AISI H13 with TiN coated P10 carbide insert tool under semi-finishing and finishing conditions of high speed cutting. The milling parameters evaluated are cutting speed, Feed Rate and depth of cut. An orthogonal array, signal-to-noise (S/N) ratio and Pareto analysis of variance (ANOVA) are employed to analyze the effect of these milling parameters. The analysis of the result shows that the optimal combination for Low resultant cutting force and good surface finish are high cutting speed, Low Feed Rate and Low depth of cut. Using Taguchi method for design of experiment (DOE), other significant effects such as the interaction among milling parameters are also investigated. The study shows that the Taguchi method is suitable to solve the stated problem with minimum number of trials as compared with a full factorial design.
