The Experts below are selected from a list of 318 Experts worldwide ranked by ideXlab platform
Khaled Abou-el-hossein - One of the best experts on this subject based on the ideXlab platform.
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PREDICTION OF TORQUE IN MILLING BY RESPONSE SURFACE METHOD AND NEURAL NETWORK
International Journal of Modelling and Simulation, 2015Co-Authors: Kumaran Kadirgama, Khaled Abou-el-hosseinAbstract:The present paper discusses the development of the first-order model for predicting the cutting torque in the milling operation of ASSAB 618 stainless steel using coated carbide cutting tools. The first-order equation was developed using response surface method (RSM). The input cutting parameters were the cutting speed, feed rate, radial Depth and Axial Depth of cut. The study found that the predictive model was able to predict torque values close to those readings recorded experimentally with a 95% confident interval. The results obtained from the predictive model were also compared by using multilayer perceptron with back-propagation learning rule artificial neural network. The first-order equation revealed that the feed rate was the most dominant factor which was followed by Axial Depth, radial Depth and cutting speed. The cutting torque value predicted by using Neural Network was in good agreement with that obtained by RSM. This observation indicates the potential use of RSM in predicting cutting parameters thus eliminating the need for exhaustive cutting experiments to obtain the optimum cutting conditions in terms of torque.
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Tool wear analysis in end milling of advanced ceramics with TiAlN and TiN coated carbide inserts
Advanced Materials Research, 2012Co-Authors: Moola Mohan Reddy, Alexander Gorin, D Sujan, Khaled Abou-el-hossein, Abdul MalequeAbstract:Advanced ceramic materials are difficult to machine by conventional methods due to the brittle nature and high hardness. The appropriate selection of cutting tool and cutting conditions may help to improve machinability by endmilling. Performance of TiAlN and TiN coated carbide tool insert in end milling of machinable glass ceramic has been investigated. Several dry cutting tests were performed to select the optimum cutting parameters for the endmilling in order to obtain better tool life. In this work, a study was carried out on the influence of cutting speed, feed rate and Axial Depth of cut on tool wear.The technique of design of experiments (DOE) was used for the planning and analysis of the experiments. Tool wear prediction model was developed using Response surface methodology.The results indicate that tool wear increased with increasing the cutting speed and Axial Depth of cut. Effect of feed rate is not much significant on selected range of cutting condition
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Influence of Cutting Parameters on Machinable Glass Ceramic Processed by End Milling
Advanced Materials Research, 2011Co-Authors: Moola Mohan Reddy, Khaled Abou-el-hossein, Alexander GorinAbstract:This experimental research work attempted to use End milling on Machinable Glass Ceramic (MGC) using micro grain solid carbide end mill under dry conditions. The predictive Surface Roughness model has been developed in terms of Spindle speed, Feed rate and Axial Depth of cut by Response Surface Methodology (RSM). The influence of each milling parameter analyzed and results showed that Axial Depth of cut was the most dominant variable. The adequacy of the model has been verified by ANOVA.
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Prediction Modelling Of Power And Torque In End-Milling
WIT Transactions on the Built Environment, 2010Co-Authors: Kumaran Kadirgama, M. M. Noor, Mohd Shahrir Mohd Sani, M. M. Rahman, Mohd Ruzaimi Mat Rejab, Rosli Abu Bakar, Khaled Abou-el-hosseinAbstract:This paper presents the development of mathematical models for torque and power in milling 618 stainless steel using coated carbides cutting tool. Response surface method was use to predict the effect of power and torque in the end-milling. From the model, the relationship between the manufacturing process factors including the cutting speed, feed rate, Axial Depth and radial Depth with the responses such as torque and power can be developed. Beside the relationship, the effect of the factors can be investigated from the equation developed. It can seen that the torque increases with decreases of cutting speed while increase of the feed rate, Axial Depth and radial Depth. The acquired results also shown that the power increases with the increases of cutting speed, feed rate, Axial Depth and radial Depth .It can be found that the second order is more accurate based on the variance analysis and the predicted value is closely match with the experimental result. Third- and fourth- order model generated for both response to investigate the 3- and 4-way interaction between the factors. The third and fourth order model shows that 3- and 4-way interaction found less significant for the variables.
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Optimised tool life by partial swarm optimisation
International Journal of Material Forming, 2010Co-Authors: Kumaran Kadirgama, M. M. Noor, Mustafizur Rahman, Mohd Shahrir Mohd Sani, Khaled Abou-el-hosseinAbstract:The aim of the this paper is to develop the tool life prediction model for P20 tool steel with aid of statistical method and find the optimisation values with partial swarm optimisation (PSO), using coated carbide cutting tool. By using Response Surface Method (RSM), first and second order models were developed with 95% confidence level. The tool life model was developed in terms of cutting speed, feed rate, Axial Depth and radial Depth, using RSM. It was found that the feedrate, cutting speed, Axial Depth and radial Depth played a major role. Tool life increases with a reduction in cutting speed and feedrate. For end-milling of P20 tool steel, the optimum conditions obtained from PSO are: cutting speed of 100 m/s, federate of 0.1 mm/tooth, Axial Depth of 1.9596 mm and radial Depth of 2 mm. Using these parameters, a tool life of 40.52 min was obtained.
Kumaran Kadirgama - One of the best experts on this subject based on the ideXlab platform.
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PREDICTION OF TORQUE IN MILLING BY RESPONSE SURFACE METHOD AND NEURAL NETWORK
International Journal of Modelling and Simulation, 2015Co-Authors: Kumaran Kadirgama, Khaled Abou-el-hosseinAbstract:The present paper discusses the development of the first-order model for predicting the cutting torque in the milling operation of ASSAB 618 stainless steel using coated carbide cutting tools. The first-order equation was developed using response surface method (RSM). The input cutting parameters were the cutting speed, feed rate, radial Depth and Axial Depth of cut. The study found that the predictive model was able to predict torque values close to those readings recorded experimentally with a 95% confident interval. The results obtained from the predictive model were also compared by using multilayer perceptron with back-propagation learning rule artificial neural network. The first-order equation revealed that the feed rate was the most dominant factor which was followed by Axial Depth, radial Depth and cutting speed. The cutting torque value predicted by using Neural Network was in good agreement with that obtained by RSM. This observation indicates the potential use of RSM in predicting cutting parameters thus eliminating the need for exhaustive cutting experiments to obtain the optimum cutting conditions in terms of torque.
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Response Surface Design Model to Predict Surface Roughness when Machining Hastelloy C-2000 using Uncoated Carbide Insert
IOP Conference Series: Materials Science and Engineering, 2012Co-Authors: N. H. Razak, Mustafizur Rahman, Kumaran KadirgamaAbstract:This paper presents to develop of the response surface design model to predict the surface roughness for end-milling operation of Hastelloy C-2000 using uncoated carbide insert. Mathematical model is developed to study the effect of three input cutting parameters includes the feed rate, Axial Depth of cut and cutting speed. Design of experiments (DOE) was implemented with the aid of the statistical software package. Analysis of variance (ANOVA) has been performed to verify the fit and adequacy of the developed mathematical model. The result shows that the feed rate gave the more effect on the both prediction values of Ra compared to the cutting speed and Axial Depth of cut. SEM and EDX analyses were performed in different cutting conditions. It can be concluded that the feed rate and cutting force give the higher impact to influence the machining characteristics of surface roughness. Thus, the optimizing the cutting conditions are essential in order to improve the surface roughness in machining of Hastlelloy C-2000.
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Prediction Modelling Of Power And Torque In End-Milling
WIT Transactions on the Built Environment, 2010Co-Authors: Kumaran Kadirgama, M. M. Noor, Mohd Shahrir Mohd Sani, M. M. Rahman, Mohd Ruzaimi Mat Rejab, Rosli Abu Bakar, Khaled Abou-el-hosseinAbstract:This paper presents the development of mathematical models for torque and power in milling 618 stainless steel using coated carbides cutting tool. Response surface method was use to predict the effect of power and torque in the end-milling. From the model, the relationship between the manufacturing process factors including the cutting speed, feed rate, Axial Depth and radial Depth with the responses such as torque and power can be developed. Beside the relationship, the effect of the factors can be investigated from the equation developed. It can seen that the torque increases with decreases of cutting speed while increase of the feed rate, Axial Depth and radial Depth. The acquired results also shown that the power increases with the increases of cutting speed, feed rate, Axial Depth and radial Depth .It can be found that the second order is more accurate based on the variance analysis and the predicted value is closely match with the experimental result. Third- and fourth- order model generated for both response to investigate the 3- and 4-way interaction between the factors. The third and fourth order model shows that 3- and 4-way interaction found less significant for the variables.
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Optimised tool life by partial swarm optimisation
International Journal of Material Forming, 2010Co-Authors: Kumaran Kadirgama, M. M. Noor, Mustafizur Rahman, Mohd Shahrir Mohd Sani, Khaled Abou-el-hosseinAbstract:The aim of the this paper is to develop the tool life prediction model for P20 tool steel with aid of statistical method and find the optimisation values with partial swarm optimisation (PSO), using coated carbide cutting tool. By using Response Surface Method (RSM), first and second order models were developed with 95% confidence level. The tool life model was developed in terms of cutting speed, feed rate, Axial Depth and radial Depth, using RSM. It was found that the feedrate, cutting speed, Axial Depth and radial Depth played a major role. Tool life increases with a reduction in cutting speed and feedrate. For end-milling of P20 tool steel, the optimum conditions obtained from PSO are: cutting speed of 100 m/s, federate of 0.1 mm/tooth, Axial Depth of 1.9596 mm and radial Depth of 2 mm. Using these parameters, a tool life of 40.52 min was obtained.
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Fourth order torque prediction model in end milling
Journal of Applied Sciences, 2009Co-Authors: Kumaran Kadirgama, M. M. Noor, M. M. Rahman, Rosli Abu Bakar, Khaled Abou-el-hosseinAbstract:This study presents the development of mathematical models for torque in end-milling of AISI 618. Response Surface Method (RSM) was used to predict the effect of torque in the end-milling. The relationship between the manufacturing process factors including the cutting speed, feed rate, Axial Depth and radial Depth with the torque can be developed. The effect of the factors can be investigated from the equation developed for first order to fourth order model. The acquired results show that the torque increases with decreases of the cutting speed and increases the feed rate, Axial Depth and radial Depth. It found that the second order is more accurate based on the analysis of variance (ANOVA) and the predicted torque results is closely match with the experimental results. Third- and fourth-order model generated for the response to investigate the 3 and 4-way interaction between the factors. It's found less significant for the variables.
Zhan Qiang Liu - One of the best experts on this subject based on the ideXlab platform.
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Development of constrained layer damping toolholder to improve chatter stability in end milling
International Journal of Mechanical Sciences, 2016Co-Authors: Yong Liu, Zhan Qiang Liu, Qinghua Song, Bing WangAbstract:The chatter occurs during milling operation when the Axial Depth of cut is too large and/or the spindle speed approaches one of natural frequencies of the machining system. The critical Axial Depth of cut and stable spindle speed ranges for chatter occurrence are influenced by dynamic stiffness and natural frequency of the milling toolholder. In this work, a novel constrained layer damping toolholder was developed to increase chatter stability of end milling operation. Firstly, optimum design geometrical parameters were analytically solved with respect to optimum damping and constraining layer materials. Then the developed damping toolholder was manufactured. Lastly, modal tests and cutting experiments were carried out to verify the effectiveness of chatter suppression with the developed damping toolholder. The frequency response, cutting forces and machined surface quality were measured and compared. It is found that the dynamic stiffness and critical Axial Depth of cut for the developed damping toolholder are 600% higher than those of the conventional mono-solid toolholder with steel alloys. The natural frequency of the developed damping toolholder has increased by 19%, which can allow wider spindle speed ranges for stable end milling operations.
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Modeling and simulation of three-dimensional stability lobes of milling thin-walled plate
Proceedings of the IEEE International Conference on Automation and Logistics ICAL 2008, 2008Co-Authors: Ai Jun Tang, Zhan Qiang LiuAbstract:Chatter phenomenon often occurs during peripheral milling of thin-walled plate, which affect the quality of the finished part, the tool life and the spindle life. Therefore, it is necessary to avoid chatter with a suitable choice of cutting condition. Several stability models only emphasize the Axial Depth for chatter free machining. In this paper, it is shown that the radial Depth is the same important for stability. This paper studies the three-dimensional stability of milling the thin-walled plate, and develops a three-dimensional lobes diagram of the spindle speed, the Axial Depth and the radial Depth. Through the three-dimensional lobes, it is possible to choose the appropriate cutting parameters according to the dynamic behavior of the chatter system.
Kadirgama K - One of the best experts on this subject based on the ideXlab platform.
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Experimental and Numerical Study of Cutting Force in End-Milling Operation Using Statistical Method
2020Co-Authors: Kadirgama K, Noor M M, Rahman M M, Bakar R. A.Abstract:The present paper explores the experimental and finite element study to predict the cutting force produced in end-milling operation for modified AISI P20 tool steel using statistical approach. The first order cutting force equations were developed utilizing the response surface methodology (RSM) to study the effect of input cutting parameters including the cutting speed, feed rate, radial Depth and Axial Depth of cut. The explicit code was used to estimate the cutting and thrust forces. It can be seen that the longitudinal component of cutting force predicted by RMS and finite element analysis (FEA) are excellent agreement with the experimental results at 95% of confident interval. It can be observed that the range of the error for both methods within 10% except few and the more error occurred for higher cutting speed. At a level of confidence of 95%, the lack-of-fit F –value of 3.50 is not significant with relative to the pure error and zero order term and the model could fit and adequate. The acquired results show that the Axial Depth of cut, radial Depth of cut and feed rate are strongly related with the cutting force. It can be seen that the increases of cutting force with increases of Axial Depth of cut, radial Depth of cut and feed rate, however, the decreases of cutting speed. The cutting force obtained the highest value about 426 N at cutting speed 100m/min.
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Tool Life Analysis By Partial Swarm Optimisation
2020Co-Authors: Noor M M, Kadirgama K, Rahman M M, Sani M. S. M., Rejab M. R. M.Abstract:Tool life is one of the main factors to be considered in CNC milling machine. Prediction model and optimum values are very important for the machinist to save number of cutting tools and reduce machining time. The aim of the this paper is to develop the tool life prediction model for P20 tool steel with aid of statistical method and to determine the optimisation values using partial swarm optimisation (PSO) for coated carbide cutting tool under different cutting conditions. By using response surface method, first and second order models were developed with 95% confidence level. The tool life model was developed in terms of cutting speed, feed rate, Axial Depth and radial Depth. In general, the results obtained from the mathematical model are in good agreement with that obtained from the experiment data’s. It was found that the feed rate, cutting speed, Axial Depth and radial Depth played a major role to determine the tool life. On the other hand, the tool life increases with the reduction of cutting speed and feed rate. For end-milling of P20 tool steel, the optimum cutting speed, feed rate, Axial Depth and radial Depth obtained from PSO are of 100 m/s, 0.1 mm/rev, 1.9596 mm and 2 mm respectively. The optimized tool life of 40.52 min was obtained using the above mentioned parameters.
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Modelling Of Tool Life When Milling Nickel Base Alloys With Two Different Coated Carbide Insert.
2020Co-Authors: Kadirgama KAbstract:This paper discusses the development of the first-order model for predicting the tool life in end-milling operation of Hastelloy C-22HS nickel base superalloy when employing two differently coated carbide cutting tools. The first-order equations of tool life are developed using response surface methodology (RSM). The cutting variables used in this study are the cutting speed, feed rate, and Axial Depth of cut. The analysis of the obtained models is supported using a statistical software package. From this study, it is found that the models are able to predict values of tool life close to those readings recorded experimentally with a 95%-confidence interval. The tool life first order equations show that feed rate is the most dominant factor, followed by Axial Depth of cut, and then cutting speed. In addition, the study indicates that inserts coated with a single TiAlN layer outperform the other type of inserts,which are with multiple-layered coating.
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Prediction Modeling of Torque in End-milling
2020Co-Authors: Kadirgama K, Noor M M, Rahman M M, Sani M. S. M., Rejab M. R. M., Bakar R. A., N. M. N. M. ZukiAbstract:This paper presents the development of mathematical models for torque in end-milling of AISI618 using coated carbides cutting tool. Response surface method was use to predict the effect of torque in the end-milling. From the model, the relationship between the manufacturing process factors including the cutting speed, feed rate, Axial Depth and radial Depth with the torque can be developed. The effect of the factors can be investigated from the equation developed for first order to fourth order model. The acquired results show that the torque increases with decreases of the cutting speed and increases the feed rate, Axial Depth and radial Depth. It found that the second order is more accurate based on the analysis of variance (A&OVA) and the predicted torque results is closely match with the experimental results. Third-and fourth-order model generated for response to investigate the 3- and 4-way interaction between the factors. The third and fourth order model show that 3- and 4-way interaction found less significant for the variables.
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finite element analysis and statistical method to determine temperature distribution on cutting tool in end milling
European journal of scientific research, 2009Co-Authors: Kadirgama K, Noor M M, Rahman M M, Wan Harun W SAbstract:The aim of this study is to determine the temperature distribution on cutting tool when machining HASTELLOY C-22HS with carbide coated cutting tool. Response Surface Method (RSM) used to minimize the number of experiments and to develop first order temperature model. Finite element analysis (FEA) was used to verification of the temperature distribution on cutting tool. From FEA results show clearly that the relationship between the variables (cutting speed, feed rate and Axial Depth) with responses (temperature). From the first order model shows that cutting speed, feed rate and Axial Depth plays important role in producing cutting temperature. The feed rate has the most dominant parameter on the temperature, followed by the Axial Depth and cutting speed. The results from FEA were compared with the experimental values. The predicted values are quite close to the experimental results, even though its accuracy is slightly inferior as
M. M. Noor - One of the best experts on this subject based on the ideXlab platform.
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Prediction Modelling Of Power And Torque In End-Milling
WIT Transactions on the Built Environment, 2010Co-Authors: Kumaran Kadirgama, M. M. Noor, Mohd Shahrir Mohd Sani, M. M. Rahman, Mohd Ruzaimi Mat Rejab, Rosli Abu Bakar, Khaled Abou-el-hosseinAbstract:This paper presents the development of mathematical models for torque and power in milling 618 stainless steel using coated carbides cutting tool. Response surface method was use to predict the effect of power and torque in the end-milling. From the model, the relationship between the manufacturing process factors including the cutting speed, feed rate, Axial Depth and radial Depth with the responses such as torque and power can be developed. Beside the relationship, the effect of the factors can be investigated from the equation developed. It can seen that the torque increases with decreases of cutting speed while increase of the feed rate, Axial Depth and radial Depth. The acquired results also shown that the power increases with the increases of cutting speed, feed rate, Axial Depth and radial Depth .It can be found that the second order is more accurate based on the variance analysis and the predicted value is closely match with the experimental result. Third- and fourth- order model generated for both response to investigate the 3- and 4-way interaction between the factors. The third and fourth order model shows that 3- and 4-way interaction found less significant for the variables.
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Optimised tool life by partial swarm optimisation
International Journal of Material Forming, 2010Co-Authors: Kumaran Kadirgama, M. M. Noor, Mustafizur Rahman, Mohd Shahrir Mohd Sani, Khaled Abou-el-hosseinAbstract:The aim of the this paper is to develop the tool life prediction model for P20 tool steel with aid of statistical method and find the optimisation values with partial swarm optimisation (PSO), using coated carbide cutting tool. By using Response Surface Method (RSM), first and second order models were developed with 95% confidence level. The tool life model was developed in terms of cutting speed, feed rate, Axial Depth and radial Depth, using RSM. It was found that the feedrate, cutting speed, Axial Depth and radial Depth played a major role. Tool life increases with a reduction in cutting speed and feedrate. For end-milling of P20 tool steel, the optimum conditions obtained from PSO are: cutting speed of 100 m/s, federate of 0.1 mm/tooth, Axial Depth of 1.9596 mm and radial Depth of 2 mm. Using these parameters, a tool life of 40.52 min was obtained.
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Fourth order torque prediction model in end milling
Journal of Applied Sciences, 2009Co-Authors: Kumaran Kadirgama, M. M. Noor, M. M. Rahman, Rosli Abu Bakar, Khaled Abou-el-hosseinAbstract:This study presents the development of mathematical models for torque in end-milling of AISI 618. Response Surface Method (RSM) was used to predict the effect of torque in the end-milling. The relationship between the manufacturing process factors including the cutting speed, feed rate, Axial Depth and radial Depth with the torque can be developed. The effect of the factors can be investigated from the equation developed for first order to fourth order model. The acquired results show that the torque increases with decreases of the cutting speed and increases the feed rate, Axial Depth and radial Depth. It found that the second order is more accurate based on the analysis of variance (ANOVA) and the predicted torque results is closely match with the experimental results. Third- and fourth-order model generated for the response to investigate the 3 and 4-way interaction between the factors. It's found less significant for the variables.
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surface roughness prediction model of 6061 t6 aluminium alloy machining using statistical method
European journal of scientific research, 2009Co-Authors: K. Kadirgama, M. M. Noor, M. M. Rahman, Mohd Ruzaimi Mat Rejab, Che Hassan Che Haron, Khaled AbouelhosseinAbstract:This paper explores on the optimization of the surface roughness of milling mould 6061-T6 aluminium alloys with carbide coated inserts. Optimization of the milling is very important to reduce the cost and time for machining mould. The purposes of this study are to develop the predicting model of surface roughness, to investigate the most dominant variables among the cutting speed, feed rate, Axial Depth and radial Depth and to optimize
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Prediction of tool life by statistic method in end-milling operation
2008Co-Authors: Kumaran Kadirgama, Khaled Abou-el-hossein, M. M. Noor, B. Mohammad, S.m. SapuanAbstract:The aim of the this study is to develop the tool life prediction model for P20 tool steel with aid of statistical method, using coated carbide cutting tool under various cutting conditions. This prediction model was then compared with the results obtained experimentally. By using Response Surface Method (RSM) of experiment, first and second order models were developed with 95% confidence level. The tool life was developed in terms of cutting speed, feed rate, Axial Depth and radial Depth, using RSM and design of experiment. In general, the results obtained from the mathematical model are in good agreement with that obtained from the experiment data’s. It was found that the feedrate, cutting speed, Axial Depth and radial Depth played a major role in determining the tool life. On the other hand, the tool life increases with a reduction in cutting speed and feedrate. For end-milling of P20 tool steel, the optimum conditions that is required to maximize the coated carbide tool life are as follow: cutting speed of 140 m/s, federate of 0.1 mm/rev, Axial Depth of 1.5 mm and radial Depth of 2 mm. Using these parameters, a tool life of 39.46 min was obtained.
