Deepak Rajendra Unune

Current status and applications of hybrid micro-machining processes: A review:

The hybrid micro-machining process employs simultaneous or ensuing action of two or more machining processes or takes aid of some energy assistance in material removal to enhance advantages and minimize potential disadvantages found in individual material removal techniques. There are various examples, such as abrasive electro-discharge grinding, electrochemical discharge machining, laser-assisted turning, and jet-assisted machining. This article presents a novel classification of and reviews the past and present research and applications of the hybrid micro-machining process, highlighting its effects on response variables such as material removal rate, tool wear, and surface roughness. Although hybrid micro-machining has been an active research area in non-conventional and critical machining since few years, insufficient knowledge about capabilities in sizes, materials, machinery, and manipulating devices is still a major constraint in the development of these processes. In the near future, there is ample scope for the hybrid micro-machining process in exploring issues in material removal at micro-scale, effect of residual stresses, and environment.

Experimental Investigations of Abrasive Mixed Electro Discharge Diamond Grinding of Nimonic 80A

This paper presents a novel hybrid machining process (HMP) called abrasive mixed electro discharge diamond grinding (AMEDDG) in which abrasive powder is mixed in dielectric fluid to perform electro discharge diamond grinding (EDDG) action on a workpiece. In-house-fabricated AMEDDG setup was used to experimentally evaluate the performance of the process during the machining of Nimonic 80A. The effects of wheel speed, powder concentration, current, and pulse-on-time (POT) were investigated on the material removal rate (MRR). The surface morphological properties of the machined workpiece were investigated based on some quality surface indicators. The experimental results show that MRR of the workpiece was influenced by wheel speed, current, and powder concentration, and optimum MRR can be achieved at a wheel speed of 1400 RPM, a powder concentration of 4 g/L, a current of 10 A, and a POT of 26 µs.

Artificial neural network–based and response surface methodology–based predictive models for material removal rate and surface roughness during electro-discharge diamond grinding of Inconel 718:

Hybrid machining processes growing popularity in the processing of difficult-to-cut materials due to their distinct merits over individual machining processes attributed by an amalgamation of two or more machining mechanisms simultaneously. This research study deals with the response surface methodology and artificial neural network with backpropagation algorithm–based mathematical modeling of electro-discharge diamond grinding of Inconel 718 superalloy. The matrix experiments were designed based on central composite design. The wheel speed, current, pulse-on-time, and duty factor were chosen as control factors, while material removal rate and average surface roughness (Ra) were chosen as performance parameters. The analysis of variance test shows that the wheel speed is the major factor influencing both the material removal rate and the Ra and contributes 89.03% and 79.10% on material removal rate and Ra, respectively, followed by current which contributes 4.43% and 8.38% on material removal rate and Ra, respectively. The modeling and predictive abilities of developed artificial neural network model (4-24-2) were related to the response surface methodology model using root mean square error and absolute standard deviation. The predicted values of material removal rate and Ra by response surface methodology and artificial neural network are in close agreement with the actual experimental results.

Investigating effects of resistance wire heating on AISI 1023 weldment characteristics during ASAW

ABSTRACT In this article, effects of advanced submerged arc welding process parameters on weld bead geometry have been investigated. A novel water-cooled torch has been developed which allow a use of higher preheat current values for a continuous advanced submerged arc welding (ASAW) operation. Weld beads have been deposited on AISI 1023 steel plates by varying open circuit voltage, wire feed rate, welding speed, nozzle to plate distance, and preheat current as per central composite design. The relationships between welding parameters and weldment characteristics namely bead width, penetration, reinforcement, and dilution have been developed using multiple linear regression. The effects of individual process parameters and their interactions on response parameters were examined. Finally, single and multiobjective optimization of process parameters were performed using desirability approach and Jaya algorithm. The results reveal that a smaller bead width and lower dilution can be achieved with the developed torch by allowing the use of higher preheat current values.

Design and Fabrication of a Strain Gauge Type 3-axis Milling Tool Dynamometer: Fabrication and Testing

1 Design and Fabrication of a Strain Gauge Type 3-axis Milling Tool Dynamometer: Fabrication and Testing; Bhargav Prajwal Pathri, Malaviaya National Institute of Technology, Jaipur, India Arpit Kumar Garg, National Institute of Technical Teacher’s Training and Research, Chandigarh, India Deepak Rajendra Unune, Malaviya National Institute of Technology, Jaipur, India Harlal Singh Mali, Malaviya National Institute of Technology Jaipur, India Sukhdeep S. Dhami, National Institute of Technical Teacher’s Training and Research, Chandigarh, India Ravindra Nagar, Malaviya National Institute of Technology Jaipur, India

A study of multiobjective parametric optimisation of electric discharge diamond cut-off grinding of Inconel 718

Hybrid machining techniques are becoming more and more popular for machining of difficult-to-cut materials. This paper presents an approach for the optimisation of electric discharge diamond cut-off grinding of Inconel 718 with multiple performance characteristics based on the Taguchi orthogonal array with grey relational analysis. In this study, the machining parameters namely, wheel speed, current, pulse-on-time, and duty factor are optimised for performance characteristics, i.e., material removal rate and surface roughness. The optimal machining parameters are determined by the Grey relational grade as the performance index. The research result identifies significant machining parameters and their effects on process performance. The confirmation experiments have been conducted to verify the optimal process conditions. Experimental results show that the performance of process improved effectively through this approach.

Machinability of Nickel-Based Superalloys: An Overview

Nickel-based superalloys have gained more importance, nowadays, owing to extensive applications in aerospace, marine, nuclear reactor, and chemical industries. Various properties, such as superior mechanical and chemical properties at elevated temperature, toughness, and exceptional resistance to corrosion and thermal shocks, are mainly accountable for their widespread application. However, machinability of nickel-based superalloys is a critical aspect that influences functional performance including fatigue life of the component. This article presents the composition and properties of various nickel-based superalloys and briefly discusses the tool failure mechanism, challenges, and cutting tool materials in their conventional machining. In addition, the recent trends of use of hybrid machining processes for enhanced machinability of these superalloys have been discussed.

Experimental investigation on low-frequency vibration-assisted µ-ED milling of Inconel 718

ABSTRACT The microelectric discharge (µ-ED) milling is a competent process for the fabrication of complex 3-D shapes, but longer machining time limits the wide applications of the process. Therefore, in this work, a novel approach of low-frequency workpiece vibration-assisted µ-ED milling has used intending to improve the process performance. The experimental investigation has been performed using Taguchi L-16 orthogonal array to examine the effects of low-frequency workpiece vibration assistance in the µ-ED milling while fabricating microchannels on Inconel 718. The gap voltage, capacitance, and vibration frequency were selected as input parameters while material removal rate (MRR) and frontal electrode wear (FEW) were chosen as response variables. It has been observed that the MRR increases and FEW decreases with an increase in vibrational frequency up to an optimal value and then decreases for further increase in vibration frequency. The results disclose a positive influence of the low-frequency workpiece vibration of both MRR and FEW during µ-ED milling of Inconel 718. Finally, the effects of vibration and discharge energy on surface quality of fabricated microchannels were analyzed using field emission scanning electron microscopic images.