Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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VIT University

The nontraditional hole-making process Friction Drilling (FD) receives major attention nowadays because of its operational efficiency in terms of unpolluted, chipless hole making and in fact, the holes are drilled in single step. It is a cumbersome and challenging task to predict surface finish of the work material in the final stages of operation. This difficulty arises because of nonlinear interactions between the process parameters and nonuniform nature of the heat caused by friction which occurred between the conical drill bit rotating at high speed and the workpiece. Since this process is having ambiguities and uncertainties, a model based on fuzzy logic has been developed for the prediction of surface roughness of drilled holes in the FD process. Operating parameters such as rotational speed of the spindle, feed rate, and workpiece temperature are the three membership functions chosen to propose this fuzzy model. These functions are assigned for each input of the model. This fuzzy logic model is verified by two firsthand set of parameter values. The results opine that the established fuzzy model is well in agreement with the investigational data with the maximum deviation of 3.81%. Furthermore, three-dimensional surface plots are developed using this fuzzy model to reveal the influence of individual process parameters on the surface ambiguities. The outcomes of the study attest that the three-dimensional surface plots are much useful for selecting input parameter combinations to achieve the required surface roughness.

Department of Design and Automation

School of Mechanical Engineering

Vellore Campus

Advances in Intelligent Systems and Computing Soft Computing for Problem Solving

Fuzzy Logic-Based Model for Predicting Surface Roughness of Friction Drilled Holes

The present investigation deals with monitoring the bush and collar formation during the friction drilling (FD) process of Be-Cu alloy. During the FD process, the alloys are often prone to structural damages as well as irregular bush formation. Hence, monitoring the quality of the hole during the process becomes inevitable. The quality of the drilled hole was monitored using different machine learning (ML) techniques. The vibration signals were captured using an accelerometer sensor. The change in amplitude of the measurement data concerning each process parameter and the measured bush surface roughness values were used to validate the effectiveness of the proposed method. The results inferred that the rigidity of the hole could be differentiated between the formation of a proper and improper bush. The study opines that the decision tree method is faster and more accurate compared to the other two methods for identifying the quality of the drilled hole. Copyright © 2020 Inderscience Enterprises Ltd.

International Journal of Materials Engineering Innovation

Monitoring of hole quality in friction drilling using different machine learning techniques

VIT Unitversity

School of Computer Science and Engineering

Emerging Research in Data Engineering Systems and Computer Communications Advances in Intelligent Systems and Computing

Cost Effective Model for Using Different Cloud Services