Titlebook: Recent Advances in Materials and Modern Manufacturing; Select Proceedings o I. A. Palani,P. Sathiya,D. Palanisamy Conference proceedings 20

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Design and Analysis of a Panel Using FEA,d vertical translations of the panels are assisted by the two linear gantries. And, the two actuated swivel drive systems and two gripper jaws execute a 180° panel rotation and help safeguard the panels throughout the entire procedure.

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Experimental Investigation and Optimization of Cryogenically Treated Titanium Grade-2 Alloy in Elec in higher material removal rate, low electrode wear rate and low surface roughness, grey relational analysis was used in the present work. From the analysis it was observed that machining using non-cryogenically treated work material with graphite electrode gives promising result on peak current of

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Application of Multiple Regression Analysis for Wire Electrical Discharge Machining of Stainless St to devise the experimental trials in view of the process variables such as pulse on time (Ton), pulse off time (Toff) and peak current at three different levels. Material removal rate is the performance measure considered in this investigation. Multiple regression analysis has been evolved for asso

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Modeling the Barriers in Applying Lean and Agile Manufacturing Practice: A Case of Indian Automobilethods for measuring lean efficiency as the five critical barriers to lean and agile manufacturing practice. This paper would aid the organization judge and analyze the barriers and avert new barriers for higher implementation of strategic thinking.

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Strength Properties of Mortar Using Industrial Waste,he obtained outcomes of this study designate that replacing cement with GP, sand with SD replacing and 5% of AH affect the mechanical properties of mortar. The apparent compressive strength and density is considerably decreased other hand abrasion resistance and water absorption percentage is slight

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Prediction of Gear Pitting Severity by Using Naive Bayes Machine Learning Algorithm, the algorithm is evaluated based on the accuracy score and confusion matrix. This algorithm has proved that the severity of defect can be classified based on the gear noise level. The noise measurement was done by using a free-field microphone. The model prepared is showing good accuracy.