Prosun Mandal
@iiests.ac.in
Indian Institute of Engineering Science and Technology, Shibpur
RESEARCH INTERESTS
Manufacturing Engineering
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Prosun Mandal, Srinjoy Chatterjee, and Shankar Chakraborty
Emerald
Purpose In many of today’s manufacturing industries, such as automobile, aerospace, defence, die and mould making, medical and electrical discharge machining (EDM) has emerged as an effective material removal process. In this process, a series of discontinuous electric discharges is used for removing material from the workpiece in the form of craters generating a replica of the tool into the workpiece in a dielectric environment. Appropriate selection of the tool electrode material and combination of input parameters is an important requirement for performance enhancement of an EDM process. This paper aims to optimize an EDM process using single-valued neutrosophic grey relational analysis using Cu-multi-walled carbon nanotube (Cu-MWCNT) composite tool electrode. Design/methodology/approach This paper proposes the application of grey relational analysis (GRA) in a single-valued neutrosophic fuzzy environment to identify the optimal parametric intermix of an EDM process while considering Cu-MWCNT composite as the tool electrode material. Based on Taguchi’s L9 orthogonal array, nine experiments are conducted at varying combinations of four EDM parameters, i.e. pulse-on time, duty factor, discharge current and gap voltage, with subsequent measurement of two responses, i.e. material removal rate (MRR) and tool wear rate (TWR). The electrodeposition process is used to fabricate the Cu-MWCNT composite tool. Findings It is noticed that both the responses would be simultaneously optimized at higher levels of pulse-on time (38 µs) and duty factor (8), moderate level of discharge current (5 A) and lower level of gap voltage (30 V). During bi-objective optimization (maximization of MRR and minimization of TWR) of the said EDM process, the achieved values of MRR and TWR are 243.74 mm3/min and 0.001034 g/min, respectively. Originality/value Keeping in mind the type of response under consideration, their measured values for each of the EDM experiments are expressed in terms of linguistic variables which are subsequently converted into single-valued neutrosophic numbers. Integration of GRA with single-valued neutrosophic sets would help in optimizing the said EDM process with the Cu-MWCNT composite tool while simultaneously considering truth-membership, indeterminacy membership and falsity-membership degrees in a human-centric uncertain decision-making environment.
PROSUN MANDAL and SUBHAS CHANDRA MONDAL
World Scientific Pub Co Pte Ltd
In this paper, the copper (Cu)-based multi-wall carbon nanotube (MWCNT) composite tools were fabricated using electro-co-deposition method. The composite tools were prepared from different MWCNT concentrated (0.5, 0.75 and 1[Formula: see text]g/L) electrolytic solution and these tools were utilized in electro discharge machining (EDM). The experiments were performed with varying discharge currents. The results indicated that the incorporation of MWCNTs into the copper matrix greatly influenced the machining performances. A lower rate of tool wear and higher material removal rate (MRR) were observed for the copper-based MWCNT composite tools at different discharge currents. The highest tool wear rate (TWR) was reduced by 45.68% and the MRR was improved by 63% for the Cu-MWCNT (0.5[Formula: see text]g/L) composite tool compared to copper coated tool. At higher discharge current, smoother machined surfaces were generated using copper-based MWCNT composite tools compared to the copper tools. The SEM image exhibits that the micro-crack-free machined surfaces were produced by using copper-based MWCNT composite tools. The migration of tool material to the machined surface was also reduced for copper-based MWCNT composite tools.
Prosun Mandal and Subhas Chandra Mondal
Elsevier BV
Abstract In this study, the electro discharge machining (EDM) operation was performed with varying four major independent controlling parameters, i.e., pulse on time (Ton), duty cycle (Tau), discharge current (I), and gap voltage (GV) with Cu-MWCNT composite coated 6061Al electrode. The machining performance, such as EWR and MRR, were evaluated for each of the experiments. The Taguchi L9 orthogonal array was adopted for conducting experiments, and polynomial regression model was utilized to develop a relationship between input and machining responses. The MOPSO is a very useful technique to achieve optimal solutions from the multi decision criteria. This technique was utilized to find non-dominated solutions and formed the Pareto frontier. The TOPSIS was applied to find the most desirable solution from the Pareto optimal set. Based on the TOPSIS analysis, the optimal solution was found to be Ton = 14 µs, Tau = 6%, I = 3 A, and GV = 50 V. The confirmation test satisfied the predicted results.
Prosun Mandal and Subhas Chandra Mondal
Informa UK Limited
Prosun Mandal
IGI Global
This chapter aims to optimize centreless grinding conditions using the Taguchi method for minimizing surface roughness. The grinding operation has been performed according to the L9 orthogonal array in a centreless grinding process. The centreless grinding experiments are carried out on the crane-hook pin of C40 steel. The analysis of variance (ANOVA) and computation of signal to noise (S/N) ratio are adopted to determine the influence of grinding parameters (depth of cut [µm], regulating wheel speed [rpm], and coolant valve opening) on surface roughness. The depth of cut (µm) is found to be the most significant among the grinding parameters on the surface roughness. The signal to noise (S/N) ratio was calculated based on smaller the best criteria. The lower level of depth of cut, medium level of regulating wheel speed, and higher-level coolant valve opening is found to be optimal grinding condition according to the mean response and signal to noise (S/N) ratio.
Prosun Mandal and Subhas Chandra Mondal
Informa UK Limited
ABSTRACT In this paper, copper based single-wall carbon nanotube (SWCNT) composite was deposited on 6061Al using electrodeposition process. Anodisation method was applied for surface preparation of 6061Al before deposition in order to get strong adherent coating. Ammonium bi-fluoride (NH4F·HF) was added to anodised solution for the formation of highly porous structure in 6061Al surface. A stable, well dispersed and colloidal solution was achieved by addition of cationic dispersing agent (CTAB) in the SWCNT mixed copper sulphate electrolytic bath. The microstructure and composition of Cu–SWCNT composite coated surface were inspected by SEM-EDS. The electrical, thermal conductivity and micro-hardness of the Cu–SWCNT composite coated, Cu coated and uncoated 6061Al were investigated. The results show that the electrical, thermal conductivity and micro-hardness were improved by 79, 78 and 39%, respectively, for Cu–SWCNT composited coated 6061Al compared to uncoated 6061Al.
Prosun Mandal and Subhas Chandra Mondal
Informa UK Limited
ABSTRACT The surface properties of machine components are enhanced by surface modification. The workpiece surface can be modified using electro discharge machining (EDM) process. In this paper, mild steel work surface was modified by EDM operation using copper–multiwalled carbon nanotube (Cu-MWCNT) composite-coated 6061Al electrode. Five different electrodes (uncoated, Cu coated, Cu-MWCNT (0.5, 0.75, and 1 gL−1) composite-coated 6061Al electrode) were used for machining of mild steel work in order to compare the EDMed surface. The microstructure, elemental composition analysis, microhardness, and surface roughness of EDMed surface were investigated. The microstructural and elemental compositional analyses indicated that the MWCNTs were included into the mild steel workpiece during EDM operation. The microhardness (HV) of machined surface was enhanced by 163% compared to the base mild steel. The micro-crack formation on machined surface was significantly decreased by using Cu-MWCNT composite-coated 6061Al electrode.
Prosun Mandal and Subhas Chandra Mondal
Springer Science and Business Media LLC
Electric discharge machining (EDM), a popular non-traditional machining process, is applied for machining very hard conductive materials with desired shape, size, and dimensional accuracy. Generally, copper is used as EDM tool due to its excellent electrical and thermal conductivities. The scarcity and higher cost of copper is called for its replacement with aluminum and its alloys in the field of electrical, electronic, and mechanical industries. In this paper, a copper-single wall carbon nanotube (Cu-SWCNT) nanocomposite was deposited on 6061 aluminum and used as EDM electrode. Prior to deposition, the 6061aluminium surface was anodized to achieve a strong adhesive bond between coating and the substrate. A cationic dispersing agent (cetyl tri-methyl ammonium bromide) was mixed with electrolytic bath for getting a stable, colloidal, and uniform dispersed SWCNT copper sulfate solution. The surface of electrode and workpiece was characterized with SEM-EDX. The EDM operation was performed on AISI 304 SS workpiece using Cu-SWCNT nanocomposite–coated 6061Al electrode and compared the performances with uncoated and copper-coated 6061 aluminums. The experimental result showed that the MRR was increased by 3.13% and 14.52% and electrode wear rate was decreased by 21.04% and 29.6% for copper-coated and Cu-SWCNT composite–coated 6061Al electrodes, respectively, compared to uncoated or base 6061Al electrode.
Gourhari Ghosh, Prosun Mandal, and Subhas Chandra Mondal
Springer Science and Business Media LLC
This paper emphasizes on the development of a combined study of surface roughness for modeling and optimization of cutting parameters for keyway milling operation of C40 steel under wet condition. Spindle speed, feed, and depth of cut are considered as input parameters and surface roughness (Ra) is selected as output parameter. Surface roughness model is developed by both artificial neural networks (ANN) and response surface methodology (RSM). ANOVA analysis is performed to determine the effect of process parameters on the response. Back-propagation algorithm based on Levenberg-Marquardt (LM) and gradient descent (GDX) methods is used separately to train the neural network and results obtained from the two methods are compared. It is found that network trained by the LM algorithm gives better result. ANN model (trained by the LM algorithm) is coupled with genetic algorithm (GA) and RS model is further interfaced with the GA and particle swarm optimization (PSO) to optimize the cutting conditions that lead to minimum surface roughness. It is found that RSM coupled with PSO gives better result and the result is validated by confirmation test. Good agreement is observed between the predicted Ra value and experimental Ra value for RSM-PSO technique.
P. Mandal and S. C. Mondal
Springer Singapore
Electric Discharge Machining (EDM) is one of the most popular nontraditional machining processes applied for machining very hard conductive materials with desired shape, size and dimensional accuracy. In this paper, copper-coated 6061 aluminium alloy is applied as EDM electrode instead of copper. Electrodeposition, simple and economical process, was used for preparation of copper coating on 6061 Aluminium alloy. The method of anodization was applied in order to get a strong adhesive copper coating on aluminium alloy substrate. Ammonium bi-fluoride (NH4F·HF), a fluorine-containing inorganic substance was added to the anodizing solution to increase the porosity of aluminium alloy surface. The copper-coated surface was characterized with SEM/EDS and XRD. Lower electrode wear, surface roughness and higher MRR were found for copper-coated 6061 Aluminium alloy EDM electrode compare to uncoated 6061 Aluminium alloy electrode.
Prosun Mandal and Subhas Chandra Mondal
Elsevier BV
Abstract In this paper, electrodeposition process was used for deposition of copper based multi-walled carbon nanotubes (MWCNTs) nanocomposite coating on 6061 aluminium in order to enhance the electrical and thermal properties. The method of anodization of aluminium alloy was applied prior to plating to get highly adherent Cu-MWCNT composite coating. Ammonium bi-fluoride (NH4F·HF), a fluorine-containing inorganic substances was added to the anodized solution to increase the porosity of the anodized aluminium alloy surface. Cetyl Tri-methyl Ammonium Bromide (CTAB) cationic surfactant was added in electrolytic bath to get stable, colloidal and uniform dispersed MWCNT copper sulphate solution. The characterization and compositional analysis of the developed Cu-MWCNT composite coating was investigated by scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS) and x-ray diffraction (XRD). The electrical and thermal conductivity were measured for the pure copper coated and Cu-MWCNT nanocomposite coated samples, respectively. It was found that incorporation of MWCNTs in the copper coatings enhanced the electrical conductivity by 59.63%, 103.67% and 128.44%, respectively for Cu-MWCNT (0.5 gL−1, 0.75 gL−1 and 1 gL−1, respectively) nanocomposite coated specimens compared to pure copper coated specimen. The thermal conductivity of Cu-MWCNTs (0.5 gL−1) composite coated sample was improved by 95.62% compared to uncoated 6061 aluminium specimen.
Prosun Mandal and Subhas Chandra Mondal
Informa UK Limited
ABSTRACT Stainless steel is a material with high toughness, high ductility and easy formability but it suffers from low electrical and thermal conductivity. In this paper, an attempt has been made for deposition of copper-based multi-walled carbon nanotubes (MWCNTs) composite coatings on the surface of stainless steel plate by the direct current electrodeposition method to enhance the electrical and thermal properties. Cetyl tri-methyl ammonium bromide, a cationic dispersing agent, is applied in the electrolytic bath to prevent aggregation of carbon nanotubes. The microstructure and compositional analysis of the developed Cu-MWCNT coating were investigated by scanning electron microscopy and energy-dispersive X-ray spectroscopy. The electrical conductivity of Cu-MWCNT composite-coated stainless-steel specimen is found to be 183% greater than the uncoated stainless-steel specimen and 58% high compared with the copper-coated stainless steel specimen. Thermal conductivity of Cu-MWCNT composite-coated stainless-steel specimen also improved compared with copper-coated and uncoated stainless-steel.
Md. Samir Khan, Vishwajeet Kumar, Prosun Mandal, and Subhas Chandra Mondal
IOP Publishing
The current research work is based on combine effect of TIG & MIG welding to achieve desirable mechanical properties. The stainless steel 304L plates were selected for welding. Current, Voltage and gas flow rate were taken as input parameters to study the response (hardness and width of weld bead). The experiments were conducted with the help of a full factorial design. The increase in gas flow rate decreases the hardness of the weld bead as well as increases the bead width to some extent. Non-dominated Sorting Genetic Algorithm was used to optimize the responses. Sixteen non-dominated solutions were obtained. The welding current, voltage and gas flow rate should be maintained at approximately 200A, 24V and 15-17 l/min respectively for the best hardness and bead width value.
Sourav Ghosh, Prosun Mandal, and Subhas Chandra Mondal
IEEE
In this paper 201LN grade of 200 series Stainless Steel is selected for machining in WEDM process. The experiment is carried out using Taguchi L27 design matrix (3 levels and 5 factor (Pulse on time, Pulse off time, Current, Wire Feed and Wire Tension)). The Material Removal Rate (MRR) and Surface roughness (SR) values are consider as responses. Modelling has been carried out by RSM technique. The responses obtained were first analysed on the basis of single objective optimization technique Simulated Annealing (SA) and then multi-objective optimization is carried out by giving simultaneous weightages varying from 0% to 100% to both Surface roughness and MRR for generating a chart of optimal parameter settings for the entire range of weightage. Characteristics curves obtained for Optimized input parameters vs. Response weightage were studied for finding out the critical weightage points for which the optimized input parameters have undergone an abrupt change. Results reveal that for SA, the optimal setting for minimizing Surface Roughness corresponds to 105.01 microseconds Pulse on time, 57.38 microseconds Pulse off time, 142.62 Ampere current, 4.02mm/min Wire Feed and 5.81mm/min Wire Tension and that for maximizing MRR being 115 microseconds Pulse on time, 50.01 microseconds Pulse off time, 179.83 Ampere current, 7.71mm/min Wire Feed and 8.00mm/min Wire Tension. The obtained curves show that the critical weightage points for which the optimized input parameters have undergone an abrupt change correspond to 30–40% for Surface roughness and 60–70% for MRR.
Prosun Mandal and Subhas Chandra Mondal
Inderscience Publishers
S. C. Mondal, P. Mandal, and G. Ghosh
Springer Singapore
The aim of this work is to develop an integrated study of surface roughness for modeling and optimization of cutting parameters during end milling operation of C40 steel with HSS tools under wet condition. The experimentation is carried out using full factorial design (three factor depth of cut, feed and spindle speed and three level). Artificial neural network (ANN) based on Back-propagation (BP) learning algorithm is used to construct the surface roughness model and second-order response surface model for the surface roughness is developed using Response surface methodology. By analysis three different surface curves it can be concluded that the minimum surface roughness (2.1779 µm) will be achieved when spindle speed, feed and depth of cut are 486 rpm, 46 mm/min and 0.31 mm respectively. Optimum parameters are obtained using GA, is near about same as value of optimum parameters obtained using RSM so it is concluded that RSM method is verified by GA Optimization.
Subhas Chandra Mondal and Prosun Mandal
Springer India
There is growing need among the manufacturers to optimize performance of a centerless grinding operation to get high level of accuracy for micro-finishing of product. High quality surface finish is desired for manufacturing crane-hook-pin used in the bottom block of the crane subjected to bending and torsional load. This paper presents an application of particle swarm optimization techniques to identify optimal parameter settings to minimize surface roughness of C40 steel crane-hook-pin in centreless grinding operation. Experiments have been carried out and the effect of various process parameters (depth of cut, regulating wheel speed and coolant flow) has been studied in a full factorial design (three factors at three level) of 27 experiments for all possible combination of these factors. Particle Swarm Optimization (PSO) technique combining with response surface modelling (RSM) are used to find optimal parameter settings. The optimal parameter corresponds to 12 rpm regulating wheel speed, 1/3rd opening of coolant valve opening and 20 µm depth of cut.