Modeling of Tool Wear in Turning EN 31 Alloy Steel using Coated Carbide Inserts

The experimental investigations of the tool wear in turning of EN 31 alloy steel at different cutting parameters are reported in this paper. Mathematical model has been developed for flank wear using response surface methodology. This mathematical model correlates independent cutting parameters viz. cutting speed, feed rate and depth of cut with dependent parameters of flank wear. This model is capable of estimating the tool wear at different cutting conditions. The central composite design has been used to plan the experiments. Coated carbide inserts have been used for turning EN 31 alloy steel. Results revealed that cutting speed is the most significant factor effecting flank wear, followed by depth of cut and feed rate. Flank wear increases with increase in all the three cutting parameters. DOI: 10.4018/ijmmme.2012070103 International Journal of Manufacturing, Materials, and Mechanical Engineering, 2(3), 34-51, July-September 2012 35 Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. manufacturing industry. Due to stringent dimensional and surface requirements these materials need machining which can be accomplished by the use of turning or milling operations. Due to these concerns, there is a need to develop better understanding of the effects of process conditions on the wear behavior of cutting tools. Several researchers in the past have carried out experimental studies in machining different materials with different tools to formulate empirical relationship between tool wear, surface roughness and process parameters. Noordin, Venkatesh, Sharif, Elting, and Abdullah (2004) applied response surface methodology to evaluate the performance of coated carbide tools in turning AISI 1045 steel. Results showed that the feed is the most significant factor that influences the surface roughness and the tangential force. Aslan, Camuscu, and Birgoren (2007) conducted an experimental study to optimize process parameters when machining hardened steel with alumina based ceramic cutting tools. Taguchi techniques were employed to achieve the purpose. Effects of three parameters viz. cutting speed, feed rate and depth of cut on flank wear and surface roughness were investigated. Ezugwu, Fadare, Bonney, Da Silva, and Sales (2005) developed an artificial neural network (ANN) model for the analysis and prediction of the relationship between cutting and process parameters during high-speed turning of nickel-based Inconel 718 alloy. Aggarwal, Singh, Kumar, and Singh (2008) studied the effect of turning process parameters viz. cutting speed, depth of cut, feed rate and nose radius on the tool life, cutting force, surface roughness and power consumption in turning of AISI P-20 steel using liquid nitrogen as coolant. Coelho, Ng, and Elbestawi (2007) studied the effect of different coatings on the tool wear, cutting force and surface finish in turning hardened AISI 4340 using PCBN coated and uncoated inserts. Sharma, Chandrashekar, and Dogra (2006) optimized cutting parameters for turning of grey cast iron with uncoated carbide inserts. Response Surface Methodology was used to formulate the empirical model describing the relationship between tool wear, surface roughness and process parameters. Singh and Rao (2007) formulated a surface roughness prediction model for hard turning process. An experimental investigation was conducted to determine the effects of cutting conditions and tool geometry on the surface roughness in the finish hard turning of the bearing steel. Mixed ceramic inserts made up of aluminum and titanium carbonitride having different nose radius and different effective rake angles, were used as the cutting tools. The study showed that feed is the dominant factor determining surface finish followed by nose radius and cutting velocity. Mathematical models were developed by using the response surface methodology. Chou and Song (2004) investigated the effects of tool nose radius on finish turning of hardened AISI 52100 steels. Surface finish, tool wear, cutting forces, and, particularly, white layer (phase transformation structures) were evaluated at different machining conditions. Results showed that large tool nose radii only give finer surface finish, but comparable tool wear compared to small nose radius tools. Ozel, Karpat, Figueira, and Davim (2007) investigated surface finishing and tool flank wear in finish turning of AISI D2 steels (60 HRC) using ceramic wiper (multi-radii) design inserts. Multiple linear regression models and neural network models were developed for predicting surface roughness and tool flank wear. Devillez, Schneider, Dominiak, Dudzinski, and Larrouquere (2007) compared the performance of different coated and uncoated carbide tools in dry turning of Inconel 718. The tool wear mechanisms of tool were analyzed by using white light interferometer and scanning electron microscopy coupled to an energy-dispersive X-ray spectroscopy EDS-system. Kansal, Singh, and Kumar (2005) conducted a study to optimize process parameters in powder mixed electric discharge machining. Response surface methodology was used to plan and analyze the experiments. Suresh, Rao, and Deshmukh (2002) developed a second order mathematical model for the prediction of surface roughness in turning mild steel with TiN coated carbide cutting tools. Sahin and Motorcu (2005) devel16 more pages are available in the full version of this document, which may be purchased using the "Add to Cart" button on the product's webpage: www.igi-global.com/article/modeling-tool-wear-turningalloy/68868?camid=4v1 This title is available in InfoSci-Journals, InfoSci-Journal Disciplines Engineering, Natural, and Physical Science. Recommend this product to your librarian: www.igi-global.com/e-resources/libraryrecommendation/?id=2