The Experts below are selected from a list of 28053 Experts worldwide ranked by ideXlab platform

J.s. Khamba - One of the best experts on this subject based on the ideXlab platform.

  • Modeling of Material Removal Rate in Ultrasonic Machining of Titanium: Buckingham-П Approach
    2012
    Co-Authors: Singh Rupinder, J.s. Khamba
    Abstract:

    In the present study, the outcome of Taguchi-based model has been used for developing a mathematical model using Buckingham’s theorem for ultrasonic machining of titanium and its alloys. Six input parameters, namely, tool Material, power rating, slurry type, slurry temperature, slurry concentration and slurry grit size were selected to give the output in the form of Material Removal Rate. The proposed study sheds light on the application of Buckingham approach to model the main effects of these variables on Material Removal Rate in ultrasonic machining of titanium and its alloys. The comparison with experimental results will also serve as further validation of the model.

  • Modeling the Material Removal Rate in ultrasonic machining of titanium using dimensional analysis
    The International Journal of Advanced Manufacturing Technology, 2010
    Co-Authors: Jatinder Kumar, J.s. Khamba
    Abstract:

    Titanium is known as the metal of the future because of its excellent combination of properties such as high strength-to-weight ratio, low thermal conductivity, and high corrosion resistance. Machining of titanium, however, is considered as cumbersome with the conventional manufacturing practices, and there is a critical need of developing and establishing cost-effective methods of machining. This investigation is focused on exploring the use of ultrasonic machining, a nontraditional machining process for commercial machining of pure titanium (American Society for Testing and Materials grade-I) and evaluation of Material Removal Rate under controlled experimental conditions. The optimal settings of parameters are determined through experiments planned, conducted, and analyzed using Taguchi method. An attempt has been made to construct a micro-model for prediction of Material Removal Rate in ultrasonic machining of titanium using dimensional analysis. The predictions from this model have been validated by conducting experiments. The microstructure of the machined surface under different experimental conditions has been studied using scanning electron microscopy. A relation was established between the mode of Material Removal and the energy input Rate corresponding to the different process conditions.

  • Taguchi technique for modeling Material Removal Rate in ultrasonic machining of titanium
    Materials Science and Engineering: A, 2007
    Co-Authors: Rupinder Singh, J.s. Khamba
    Abstract:

    Titanium and its alloys have many potential engineering applications for manufacturing industry. Now day's there is a critical need for cost-effective machining processes for this Material. Not much work hither to been reported for machining of titanium with ultrasonic machining process. In this paper, a Taguchi approach to model the Material Removal Rate during ultrasonic machining of titanium and its alloys has been proposed and applied. Relationships between Material Removal Rate and other controllable machining parameters (power rating; tool type; slurry concentration; slurry type; slurry temperature and slurry size) have been deduced by using Taguchi technique. The Taguchi design results suggested that Ultrasonic power rating significantly improves the Material Removal Rate with contribution of 28%, followed by type of tool with contribution of 24.6%. The third significant factor was type of slurry with contribution of 13.3%. The comparison with experimental results will also serve as future validation of the model.

Vahid M Khojastehnezhad - One of the best experts on this subject based on the ideXlab platform.

  • Electrical discharge machining of the AISI D6 tool steel: Prediction and modeling of the Material Removal Rate and tool wear ratio
    Precision Engineering, 2016
    Co-Authors: Reza Vatankhah Barenji, Hamed H Pourasl, Vahid M Khojastehnezhad
    Abstract:

    Abstract In this investigation, response surface method was used to predict and optimize the Material Removal Rate and tool wear ratio during electrical discharge machining of AISI D6 tool steel. Pulse on time, pulse current, and voltage were considered as input process parameters. Furthermore, the analysis of variance was employed for checking the developed model results. The results revealed that higher values of pulse on time resulted in higher values of Material Removal Rate and lower amounts of tool wear ratio. In addition, increasing the pulse current caused to higher amounts of both Material Removal Rate and tool wear ratio. Moreover, the higher the input voltage, the lower the both Material Removal Rate and tool wear ratio. The optimal condition to obtain a maximum of Material Removal Rate and a minimum of tool wear Rate was 40 μs, 14 A and 150 V, respectively for the pulse on time, pulse current and input voltage.

Rupinder Singh - One of the best experts on this subject based on the ideXlab platform.

  • Taguchi technique for modeling Material Removal Rate in ultrasonic machining of titanium
    Materials Science and Engineering: A, 2007
    Co-Authors: Rupinder Singh, J.s. Khamba
    Abstract:

    Titanium and its alloys have many potential engineering applications for manufacturing industry. Now day's there is a critical need for cost-effective machining processes for this Material. Not much work hither to been reported for machining of titanium with ultrasonic machining process. In this paper, a Taguchi approach to model the Material Removal Rate during ultrasonic machining of titanium and its alloys has been proposed and applied. Relationships between Material Removal Rate and other controllable machining parameters (power rating; tool type; slurry concentration; slurry type; slurry temperature and slurry size) have been deduced by using Taguchi technique. The Taguchi design results suggested that Ultrasonic power rating significantly improves the Material Removal Rate with contribution of 28%, followed by type of tool with contribution of 24.6%. The third significant factor was type of slurry with contribution of 13.3%. The comparison with experimental results will also serve as future validation of the model.

Eberhard Bamberg - One of the best experts on this subject based on the ideXlab platform.

  • Material Removal Rate, Kerf, and Surface Roughness of Tungsten Carbide Machined with Wire Electrical Discharge Machining
    Journal of Materials Engineering and Performance, 2010
    Co-Authors: Aqueel Shah, Nadeem Ahmad Mufti, Dinesh Rakwal, Eberhard Bamberg
    Abstract:

    In this article, the effects of varying seven different machining parameters in addition to varying the Material thickness on the machining responses such as Material Removal Rate, kerf, and surface roughness of tungsten carbide samples machined by wire electrical discharge machining (WEDM) were investigated. The design of experiments was based on a Taguchi orthogonal design with 8 control factors with three levels each, requiring a set of 27 experiments that were repeated three times. ANOVA was carried out after obtaining the responses to determine the significant factors. The work piece thickness was expected to have a major effect on the Material Removal Rate but showed to be significant in the case of surface roughness only. Finally, optimization of the machining responses was carried out and models for the Material Removal Rate, kerf, and surface roughness were created. The models were validated through confirmation experiments that showed significant improvements in machining performance for all investigated machining outcomes.

Milton Coba-salcedo - One of the best experts on this subject based on the ideXlab platform.

  • Modelling of surface finish and Material Removal Rate in rough honing
    Precision Engineering, 2014
    Co-Authors: Irene Buj-corral, Joan Vivancos-calvet, Milton Coba-salcedo
    Abstract:

    Abstract In the present work influence of different parameters of the rough honing process on surface roughness and Material Removal Rate were studied. Specifically, second order mathematical models are presented for mean average roughness Ra (μm), maximum peak-to-valley roughness Rt (μm) and Material Removal Rate Qm (cm min −1 ), obtained by means of regression analysis. For doing this a central composite design was defined, with a full two-level five variables design of experiments, 5 centre points and 10 face-centred points. Steel cylinders were employed. Abrasive chosen was cubic boron nitride. Considered factors were grain size, density of abrasive, tangential speed of cylinders, linear speed of honing head and pressure of abrasive stones on internal surface of cylinders. From the models most influential factors on process quality as well as on productivity were determined. Within the range studied, roughness depends mainly on grain size, pressure and density of abrasive. Material Removal Rate depends on grain size and pressure, followed by tangential speed. Optimization by means of the desirability function technique allowed determining most appropriate conditions to minimize roughness (surface quality) and/or maximize Material Removal Rate (productivity).