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Hamlaoui N.,Annaba University | Azzouz S.,Annaba University | Chaoui K.,Annaba University | Azari Z.,Laboratoire Of Biomecanique | Yallese M.-A.,May 8th 1945 University
International Journal of Advanced Manufacturing Technology | Year: 2017

Manufacturing of high-density polyethylene (HDPE) pipes is usually achieved by extrusion processes. However, various joining or fitted parts and mechanical testing samples are prepared by material removal methods. This study focuses on the machinability of the HDPE tough resin used for piping and fittings to make standard test specimens. The experimental plan has been conducted using a Taguchi (L27) orthogonal array. Input machining parameters are cutting speed (Vc), feed rate (f), and depth of cut (ap) while output effects are represented by conventional surface roughness criteria (Ra, Rt, and Rz) and the measured cutting temperature (t°). As a result, a second-order model was established between input and output parameters via the response surface methodology (RSM). The development of predictive models is essential for machining of extruded HDPE since few experimental trends and data are available in literature as compared to metals. Optimum cutting conditions are determined using the desirability function approach. It is revealed that the feed rate (f) is the main contributing factor when minimizing surface roughness of HDPE material. The analysis of variance (ANOVA) results showed that the contributions for surface roughness criteria (Ra, Rt, and Rz) are 96.11, 86.92, and 92.22% respectively. On the other hand, cutting temperature is mainly influenced by cutting speed (Vc), depth of cut (ap), and the three interactions (Vc × f), (Vc × ap), and (f × ap). Finally, optimized cutting temperature is discussed for the three main cases, which are lower, targeted, and upper values, i.e., t° minimum, t° targeted = 30 °C, and t° maximum allowable = 32 °C. © 2017 Springer-Verlag London


Keblouti O.,Annaba University | Boulanouar L.,Annaba University | Azizi M.W.,Annaba University | Yallese M.A.,May 8th 1945 University
Structural Engineering and Mechanics | Year: 2017

In the present paper, the effects of cutting parameters and coating material on the performances of cutting tools in turning of AISI 52100 steel are discussed experimentally. A comparative study was carried out between uncoated and coated (with TiCN-TiN coating layer) cermet tools. The substrate composition and the geometry of the inserts compared were the same. A mathematical model was developed based on the Response Surface Methodology (RSM). ANOVA method was used to quantify the effect of cutting parameters on the machining surface quality and the cutting forces. The results show that feed rate has the most effect on surface quality. However, cutting depth has the significant effect on the cutting force components. The effect of coating layers on the surface quality was also studied. A lower surface roughness was observed when using PVD (TiCN-TiN) coated insert. A second order regression model was developed and a good accuracy was obtained with correlation coefficients in the range of 95% to 97%. Copyright © 2017 Techno-Press, Ltd.


Babouri M.K.,May 8th 1945 University | Babouri M.K.,University of Science and Technology Houari Boumediene | Ouelaa N.,May 8th 1945 University | Djebala A.,May 8th 1945 University
International Journal of Advanced Manufacturing Technology | Year: 2016

This paper deals with the experimental study of the tool life transition and the wear monitoring during the turning operation of AISI D3 steel workpiece using coated carbide tool inserts (TiCN/Al2O3/TiN). A hybrid method, based on the combination of wavelet multi-resolution analysis (WMRA) and Empirical Mode Decomposition (EMD), is proposed to analyze vibratory signals acquired during the machining process. Using the mean power and the energy as main scalar indicators, the proposed method has been optimized and evaluated in several configurations including the cutting speed, the feed rate, and the depth of cut. The results show that the proposed hybrid method (WMRA/EMD) gives better evaluation of the tool state and the wear monitoring compared to the application of WMRA or EMD alone. © 2015, Springer-Verlag London.


Kribes N.,Laboratory May 8th 1945 University | Hessainia Z.,May 8th 1945 University | Yallese M.A.,May 8th 1945 University
Lecture Notes in Mechanical Engineering | Year: 2015

In this study, the effects of cutting speed, feed rate and depth of cut on surface roughness in the hard turning were experimentally investigated. AISI 4140 steel was hardened to (56 HRC). The cutting tool used was an uncoated AL2O3/TiC mixed ceramics which is approximately composed of 70% of AL2O3 and 30% of TiC. Three factor (cutting speed, feed rate and depth of cut) and threelevel factorial experiment designs completed with a statistical analysis of variance (ANOVA) were performed. Mathematical model for surface roughness was developed using the response surface methodology (RSM) associated with response optimization technique and composite desirability was used to find optimum values of machining parameters with respect to objectives surface roughness. The results have revealed that the effect of feed is more pronounced than the effects of cutting speed and depth of cut, on the surface roughness. However, a higher cutting speed improves the surface finish. In addition, a good agreement between the predicted and measured surface roughness was observed. Therefore, the developed model can be effectively used to predict the surface roughness on the machining of AISI 4140 steel with in 95% confidence intervals ranges of conditions studied. © Springer International Publishing Switzerland 2015.


Tebassi H.,May 8th 1945 University | Yallese M.A.,May 8th 1945 University | Meddour I.,May 8th 1945 University
Engineering Solid Mechanics | Year: 2016

Serviceable engineering components not only rely on their bulk material properties but also on the design and the characteristics of their surface. These characteristics influence directly the surface quality of the machined products. In terms of surface roughness, the influence of the tool material can be also caused by its tribological properties, i.e. a contact behavior between cutting tool and workpiece. This study presents a formulation of the nominal’s coefficient and friction forces generated in machining between workpiece and cutting tool using cutting force profiles. The obtained equations led to the evaluation of coefficient, frictional forces and cutting inserts characterization in terms of better surface finish and lowest frictional forces. Indeed, results show that the contact between cutting tool and workpiece depends on the materials cutting tool nature, and that the cutting tool type can influences the surface roughness of the machined surface. © 2016 Growing Science Ltd. All rights reserved.


Aouici H.,May 8th 1945 University | Yallese M.A.,May 8th 1945 University | Chaoui K.,Annaba University | Mabrouki T.,University of Lyon | Rigal J.-F.,University of Lyon
Measurement: Journal of the International Measurement Confederation | Year: 2012

In this study, the effects of cutting speed, feed rate, workpiece hardness and depth of cut on surface roughness and cutting force components in the hard turning were experimentally investigated. AISI H11 steel was hardened to (40; 45 and 50) HRC, machined using cubic boron nitride (CBN 7020 from Sandvik Company) which is essentially made of 57% CBN and 35% TiCN. Four-factor (cutting speed, feed rate, hardness and depth of cut) and three-level fractional experiment designs completed with a statistical analysis of variance (ANOVA) were performed. Mathematical models for surface roughness and cutting force components were developed using the response surface methodology (RSM). Results show that the cutting force components are influenced principally by the depth of cut and workpiece hardness; on the other hand, both feed rate and workpiece hardness have statistical significance on surface roughness. Finally, the ranges for best cutting conditions are proposed for serial industrial production. © 2011 Elsevier Ltd. All rights reserved.


Zerti O.,May 8th 1945 University | Yallese M.A.,May 8th 1945 University | Khettabi R.,May 8th 1945 University | Chaoui K.,Annaba University | Mabrouki T.,Tunis el Manar University
International Journal of Advanced Manufacturing Technology | Year: 2016

The development in the manufacturing flied requires the continuous optimization using various methods. In order to minimize some technological output (such as surface roughness, tangential force, specific cutting force, and cutting power) characterizing material machinability, it is intended in the present paper to perform an optimizing approach of cutting parameters based on Taguchi method. Selected input cutting parameters are major cutting edge angle, cutting insert nose radius, cutting speed, feed rate, and depth of cut. The tests were performed on AISI D3 steel using mixed ceramic inserts under dry cutting conditions. A Taguchi L18 orthogonal array is used to design the optimization experiment. The analysis of variance (ANOVA) is exploited to evaluate the foremost effects on the output parameters. The results indicate that both feed rate and cutting insert nose radius are the mainly influencing factors on surface roughness while both tangential force and specific cutting force are affected principally by depth of cut followed by feed rate. The most significant parameter affecting cutting power is depth of cut followed by cutting speed and feed rate. Regression equations are formulated for estimating predicted values of technological parameters. Optimal cutting parameters are determined using the signal-to-noise (S/N) ratio which was calculated for the precited technological output according to the “the smaller-the-better” approach. Based on the confirmation experiments and laboratory results, it is concluded that the Taguchi method is successfully adapted to describe the optimization of cutting parameters (inputs) for improved technological ones (output). © 2016 Springer-Verlag London


Elbah M.,May 8th 1945 University | Yallese M.A.,May 8th 1945 University | Aouici H.,May 8th 1945 University | Mabrouki T.,University of Lyon | Rigal J.-F.,University of Lyon
Measurement: Journal of the International Measurement Confederation | Year: 2013

This study considers the comparison between the surface roughness criteria (Ra, Rz and Rt) of the wiper inserts with conventional inserts during hard turning of AISI 4140 hardened steel (60 HRC).The planning of experiments was based on Taguchi's L27 orthogonal array. The response surface methodology (RSM) and analysis of variance (ANOVA) were used to check the validity of quadratic regression model and to determine the significant parameter affecting the surface roughness. The statistical analysis reveals that the feed rate and depth of cut have significant effects in reducing the surface roughness. The optimum machining conditions to produce the best possible surface roughness in the range of this experiment under these experimental conditions searched using desirability function approach for multiple response factors optimization. The results indicate that the surface quality obtained with the wiper ceramic insert significantly improved when compared with conventional ceramic insert is 2.5. Roughness measurements reveal a dependence on CC6050WH tool wear. However, although the wear rises up to the allowable flank wear of value 0.3 mm, roughness Ra did not exceeded 0.9 μm. © 2013 Published by Elsevier Ltd. All rights reserved.


Hessainia Z.,May 8th 1945 University | Belbah A.,May 8th 1945 University | Yallese M.A.,May 8th 1945 University | Mabrouki T.,University of Lyon | Rigal J.-F.,University of Lyon
Measurement: Journal of the International Measurement Confederation | Year: 2013

This research work concerns the elaboration of a surface roughness model in the case of hard turning by exploiting the response surface methodology (RSM). The main input parameters of this model are the cutting parameters such as cutting speed, feed rate, depth of cut and tool vibration in radial and in main cutting force directions. The machined material tested is the 42CrMo4 hardened steel by Al2O3/TiC mixed ceramic cutting tool under different conditions. The model is able to predict surface roughness of Ra and Rt using an experimental data when machining steels. The combined effects of cutting parameters and tool vibration on surface roughness were 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 cutting parameters and tool vibration with respect to announced objectives which are the prediction of surface roughness. The adequacy of the model was verified when plotting the residuals values. The results indicate that the feed rate is the dominant factor affecting the surface roughness, whereas vibrations on both pre-cited directions have a low effect on it. Moreover, a good agreement was observed between the predicted and the experimental surface roughness. Optimal cutting condition and tool vibrations leading to the minimum surface roughness were highlighted. © 2013 Elsevier Ltd. All rights reserved.


Bouzid L.,May 8th 1945 University | Boutabba S.,8 May 1945 University of Guelma | Yallese M.A.,May 8th 1945 University | Belhadi S.,May 8th 1945 University | Girardin F.,INSA Lyon
International Journal of Advanced Manufacturing Technology | Year: 2014

The objective of this article is to manufacture low-cost, high-quality products with maximum productivity in short time. In this work, four stages are considered: statistical investigation of the experimental results based on ANOVA, modelling based on regression analysis and mono- and multi-objective optimizations. In the first stage, turning experiments were carried out using an orthogonal array (L16) of Taguchi. Effects of cutting parameters on surface roughness and material removal rate were determined using ANOVA and interaction plots. In the second stage, regression analysis was utilized to formulate second-order models of all data gathered in the experimental works; these models could be used to predict responses in turning of X20Cr13 steel with a minor error. In the third stage, responses were used alone in an optimization study as an objective function. To minimize all responses, Taguchi’s signal-to-noise ratio was used. In the fourth stage, responses were optimized simultaneously using grey relational analysis. © 2014, Springer-Verlag London.

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