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Reddy V.V.,Jayamukhi Institute of Technological science | Kumar A.,National Institute of Technology Warangal | Valli P.M.,GITAM Institute of Technology | Reddy C.S.,Jawaharlal Nehru Technological University Anantapur
Journal of the Brazilian Society of Mechanical Sciences and Engineering | Year: 2015

In the present work, an investigation has been made into the electrical discharge machining process (EDM) when both graphite powder and surfactant-mixed dielectric fluid were used during EDM of precipitation hardening stainless steel PH17-4. The addition of graphite powder in the dielectric fluid results in uniform distribution of discharge, which improves surface finish. However, agglomeration of graphite particles is found in the dielectric due to the electrostatic forces among the graphite powder particles. The addition of surfactant in the dielectric increases dielectric conductivity and in turn reduces relay time of discharge. This increases actual discharge time, which results in more material removal. At the same time, uniform distribution of graphite powder particles in the dielectric fluid is achieved. This leads to increase in discharge frequency, which results in increase in material removal rate and surface finish. Taguchi parameter design approach was used to get an optimal parametric setting of EDM process parameters namely: peak current, surfactant concentration and graphite powder concentration that yields to optimal process performance characteristics such as material removal rate, surface roughness, white layer thickness and surface crack density. Individual effect of process parameters on performance characteristics was also studied. To identify the significance of parameters on measured response, the analysis of variance has been carried out. Further, mathematical models were developed by performing nonlinear regression analysis to predict process performance characteristics. Confirmation tests were conducted at their respective optimal parametric settings to verify the predicted optimal values of performance characteristics. © 2014, The Brazilian Society of Mechanical Sciences and Engineering. Source


Kumar G.M.,Bhavans Vivekananda College | Ramachandram S.,Osmania University | Gyani J.,Jayamukhi Institute of Technological science
Souvenir of the 2015 IEEE International Advance Computing Conference, IACC 2015 | Year: 2015

Grid Computing pools the resources from various heterogeneous computers to solve a particular problem which requires huge computation. In a grid, a number of known and unknown entities from same or different domain participate in communication where in every entity need to undergo a strong authentication and authorization scheme. There is risk while making the communication among untrusted entities since there is a chance of misusing resources. So, in-order to avoid this problem a strong trust establishment phenomenon is required. This paper demonstrates a randomized algorithm for developing a trust model which makes the user and service provider to maintain consistency among their ratings from each other every time, so that they reach the eligible criteria for communication. © 2015 IEEE. Source


Bhukya R.,Kakatiya Institute of Technology and Science | Gyani J.,Jayamukhi Institute of Technological science
Proceedings of the 2015 International Conference on Applied and Theoretical Computing and Communication Technology, iCATccT 2015 | Year: 2015

The Hadoop distributed file system offers efficient Mapreduce frame work using which the big datasets can be processed with efficient time complexity. Capability to load on low-cost commodity hardware and greater extent of fault tolerance leading many business organizations to store data in Hadoop distributed file system. Considering the real-time importance of distributed file system in recent literature conventional data mining algorithms getting extended to scale in MapReduce architecture. In line to this trend we propose a fuzzy associative classification algorithm based on MapReduce framework to extract intuitive classification rules from data stored in distributed file systems. The experimental investigation shows that the proposed algorithm on MapReduce frame work can scale to effectively extract intuitive classification rules from training data stored in distributed file systems. © 2015 IEEE. Source


Reddy V.V.,Jayamukhi Institute of Technological science | Valli P.M.,Gandhi Institute of Technology and Management | Kumar A.,National Institute of Technology Warangal | Reddy C.S.,Jawaharlal Nehru Technological University Anantapur
Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture | Year: 2015

Electrical discharge machining is commonly used in manufacturing industry to make dies of complex cavities. This work investigates electric discharge machining of PH17-4 stainless steel when both graphite powder-mixed and surfactant-mixed dielectric fluid were used during electrical discharge machining. Taguchi method is used for conducting experiments with L9 orthogonal array by choosing electrical discharge machining process parameters, namely, peak current, surfactant concentration and graphite powder concentration. The process performance characteristics of electrical discharge machining such as material removal rate, surface roughness and tool wear rate are chosen for this study. The purpose of this work is to find significance of process parameters on performance characteristics and also get an optimal combination of these parameters using Taguchi-data envelopment analysis-based ranking multi-response optimization method. © IMechE 2014. Source


Reddy V.V.,Jayamukhi Institute of Technological science | Valli P.M.,AITS | Kumar A.,National Institute of Technology Warangal | Reddy C.S.,Jawaharlal Nehru Technological University Anantapur
Journal of Advanced Manufacturing Systems | Year: 2015

In the present work, an investigation has been made into the electrical discharge machining process during machining of precipitation hardening stainless steel PH17-4. Taguchi method is used to formulate the experimental layout, to analyze the effect of each process parameter on machining characteristics and to predict the optimal choice for each electrical discharge machining process parameters namely, peak current, pulse on time and pulse off time that give up optimal process performance characteristics such as material removal rate, surface roughness, tool wear rate and surface hardness. To identify the significance of parameters on measured response, the analysis of variance has been done. It is found that parameters peak current and pulse on time have the significant affect on material removal rate, surface roughness, tool wear rate and surface hardness. However, parameter pulse off time has significant affect on material removal rate. Confirmation tests are conducted at their respective optimum parametric settings to verify the predicted optimal values of performance characteristics. © 2015 World Scientific Publishing Company. Source

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