Tapan Kr. Barman

Effect of Operating Temperature on Tribological Behavior of As-Plated Ni-B Coating Deposited by Electroless Method

ABSTRACT The present work investigates the tribological behavior of electroless Ni-B coating in its as-plated condition at elevated operating temperatures. Ni-B coating is deposited using an electroless method on AISI 1040 steel specimens. Coating characterization is done using scanning electron microscopy, energy-dispersive X-ray analysis, and X-ray diffraction techniques. Vickers microhardness and surface roughness are measured. Friction and wear tests are carried out on a pin-on-disc tribological test setup at room and elevated temperatures of 100, 300, and 500°C. The tribological behavior deteriorates at 100°C compared to room temperature. Electroless Ni-B coating shows excellent wear resistance at 300°C, which again degrades at 500°C due to severe oxidation and softening of the deposits. The worn surface of the coatings is analyzed using optical microscopy and scanning electron microscopy. Within the temperature range considered, the wear mechanism changes from adhesion to a combination of adhesion and abrasion as the temperature rises from ambient condition to 100°C, following which the wear mechanism is predominantly abrasive. The formation of a tribochemical oxide film also affects the tribological behavior of the coatings at high temperature.

Investigation of Friction and Wear Properties of Electroless Ni–P–Cu Coating Under Dry Condition

This study presents the deposition and tribological characterization of electroless Ni–P–Cu coatings deposited on AISI 1040 steel specimens. After deposition, coatings are heat treated at 500∘C for...

Tribology of Electroless Ni-P Coating Under Lubricated Condition: An RSM and GA Approach

Friction and wear behavior of electroless Ni-P coating under lubricated condition is studied on a block – on – roller type tribo – tester by varying applied normal load, sliding speed of the roller and sliding time. Electroless Ni-P coating is deposited on AISI 1040 steel substrates. Surface morphology, phase transformation, composition and analysis of wear mechanism are done using scanning electron microscope, X-ray diffraction techniques and energy dispersive X-ray analysis respectively. Based on Taguchi experimental data, a multiple regression model is fitted to relate the coefficient of friction and wear depth with the tribo – testing parameters. Three dimensional surface and contour plots are generated to analyze the trends in variation of the response variables with the interaction of the process parameters (load, speed and time). Significant improvement in wear depth and COF of electroless Ni-P coating is observed under lubrication. Optimization of wear depth and coefficient of friction is conducted using genetic algorithm. KEywoRdS Friction, Genetic Algorithm, Lubrication, Ni-P Coating, Regression, Taguchi, Wear

Optimisation of EDM process parameters using grey-Taguchi technique

This paper presents an experimental study of material removal rate (MRR) and roughness characteristics in electrical discharge machining (EDM) of EN 31 tool steel. Experiments are carried out by utilising the combination of four process parameters viz. pulse on time, pulse off time, discharge current and voltage based on L27 Taguchi orthogonal array. Multi-response optimisation of EDM process parameters is done with respect to MRR and five different surface roughness characteristics based on Taguchi method coupled with grey relational analysis. Analysis of variance (ANOVA) is performed and it is observed that current is the significant process parameter that affects the responses. Optimal setting has been verified through confirmation test and the result shows a good agreement with the predicted value. This indicates utility of the grey-Taguchi technique as a multi-objective optimiser in the field of EDM. Also, the surface morphology is studied with the help of scanning electron microscopy.

Effect of Heat Treatment on Tribological Behavior of Electroless Ni-B-Mo Coatings at Different Operating Temperatures

The present work aims to characterize the tribological behavior of electroless Ni-B-Mo coatings in their as-plated and heat treated conditions deposited on AISI 1040 steel. Heat treatment temperatures considered are 350 °C, 400 °C and 450 °C. Friction and wear tests are carried out at room (25 °C) and elevated temperatures of 100 °C, 300 °C and 500 °C. The as-deposited Ni-B-Mo coatings show a high wear rate compared to the heat treated ones at room as well as elevated temperatures. The wear rate of the heat treated coatings at high temperatures does not show a significant variation which is indicative of their high thermal stability. A similar result is also observed for the coefficient of friction of the heat treated Ni-B-Mo coatings. Analysis of worn specimens at 500 °C indicates the formation of protective tribo-oxide layers and occurrence of microstructural changes due to the in-situ heat treatment effect resulting from the high operating temperatures. The wear debris also significantly affects the tribological mechanisms of the coatings at high operating temperatures.

Response Surface Modeling of Fractal Dimension in WEDM

This chapter presents the application of fractal dimension in describing surface roughness in wire electrical discharge machining (WEDM) . Conventional surface roughness parameters (center line average roughness, root mean square roughness, etc.) strongly depend on the resolution of the measuring instrument. But fractal dimension is scale invariant. As a case study, experiments are conducted on EN31 steel specimens in WEDM varying four process parameters, viz., current, voltage, pulse on time, and pulse off time. The effects of process parameters on fractal dimension are evaluated and a second order relationship between process parameters and fractal dimension is developed using response surface methodology (RSM). Also, the parameters having significant influences on fractal dimension are identified.

ANN modelling of fractal dimension in machining

Abstract: This chapter deals with fractal dimension modelling in machining operations. The study considers the fractal dimension to describe surface roughness. Four different machining operations, including CNC end milling, CNC turning, cylindrical grinding and EDM are carried out on mild steel (AISI 1040) work-pieces. The surface roughness data are used to develop models for predicting fractal dimension using artificial neural network (ANN). From the results of all machining operations, it is seen that developed models can predict fractal dimension very accurately.