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Jeevanantham, S.
- A Study on Characteristics of Parameters Influencing Internal Grinding Process with MRR
Abstract Views :221 |
PDF Views:0
Authors
S. Jeevanantham
1,
J. David Rathnaraj
2,
D. S. Robinson Smart
3,
S. Nallusamy
4,
N. Manikanda Prabu
5
Affiliations
1 Department of Mechanical Engineering, Karpagam University, Coimbatore - 641021, Tamil Nadu, IN
2 Department of Mechanical Engineering, Sri Ramakrishna Engineering College, Coimbatore - 641022, Tamil Nadu, IN
3 3School of Mechanical Sciences, Karunya University, Coimbatore - 641114, Tamil Nadu, IN
4 Department of Mechanical Engineering, Dr. M G R Educational and Research Institute, Chennai - 600095, Tamil Nadu, IN
5 Department of Mechanical Engineering, Nehru institute of Engineering and Technology, Coimbatore - 641105, Tamil Nadu, IN
1 Department of Mechanical Engineering, Karpagam University, Coimbatore - 641021, Tamil Nadu, IN
2 Department of Mechanical Engineering, Sri Ramakrishna Engineering College, Coimbatore - 641022, Tamil Nadu, IN
3 3School of Mechanical Sciences, Karunya University, Coimbatore - 641114, Tamil Nadu, IN
4 Department of Mechanical Engineering, Dr. M G R Educational and Research Institute, Chennai - 600095, Tamil Nadu, IN
5 Department of Mechanical Engineering, Nehru institute of Engineering and Technology, Coimbatore - 641105, Tamil Nadu, IN
Source
Indian Journal of Science and Technology, Vol 9, No 37 (2016), Pagination:Abstract
Objective: To generate the information about the process of internal grinding applied to envisage the grinding performance and accomplish the optimal operating procedure characteristics. In recent engineering and technology surface finish and precision are playing a major role in the manufacturing organizations. Method/Analysis: Different methods such as burnishing, honing, lapping and grinding are exercised for accomplishing good quality of surface finish. Grinding is the appropriate method for improving the surface finish and precision concurrently between all of those constraints. Recently lot of researches has been carried out on surface grinding process, but only few articles were elaborately described about the internal grinding procedure. In view of the fact the internal grinding processes was chosen as a main tool to characterize throughout this study. Findings: Similar to surface grinding various process parameters are used to get high surface finish and it could be achieved for the various components. This article relating the possibilities to get greater surface finish in internal grinding process and also it demonstrates the machining parameters involved in this process. Application/ Improvements: The machining parameters involved in these abrasive machining technologies were speed, feed, depth of cut and material removal rate and also these constraints were considered throughout the theoretical investigation.Keywords
Internal Grinding, MRR, Process Constraints, Surface Roughness, Surface Finish.- Intrusion Detection System Based on Artificial Intelligence
Abstract Views :840 |
PDF Views:6
Authors
Affiliations
1 School of Information Technology and Engineering, VIT University, Vellore, IN
2 VIT University, Vellore, IN
1 School of Information Technology and Engineering, VIT University, Vellore, IN
2 VIT University, Vellore, IN
Source
International Journal of Technology, Vol 7, No 1 (2017), Pagination: 20-24Abstract
The Internet plays a major role in today’s environment but many attacks are happening over the networks and it may cause serious issues. Intrusion detection system provides a way to prevent the network anomalies and threats. It plays a vital role in network security. The violation activity happenings over the networks can be prevented by intrusion detection system, it collects the detected activity using security information and event management (SIEM). Some IDS have the ability to respond to the detected intrusions. Systems with response capabilities are typically referred to as an intrusion prevention system. There are many techniques which are used to design IDSs for specific scenario and applications. Artificial intelligence techniques are mostly used for threats detection.Keywords
Intrusion Detection, Neural Networks, Knowledge Base.References
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