Comparison of performance of different tool electrodes during electrical discharge machining

186-199In this work, performance of tool electrode prepared through selective laser sintering (SLS) process has been studied along with traditional copper and brass electrodes for electrical discharge machining (EDM) of AISI 1040 stainless steel. Performance measures like material removal rate (MRR), tool wear rate (TWR), radial over cut (ROC) and average surface roughness (Ra) of the machined surface have been considered. Multi-response optimization like technique for order preference through similarity to ideal solution (TOPSIS) method has been used to find out the best parametric setting of the EDM process for maximization of MRR and minimization of TWR, ROC and Ra. Scanning electron microscopic (SEM) images of the machined surface reveals that less surface crack density (SCD) has been formed on the machined surface by the use of AlSiMg RP tool electrode followed by brass and copper tool electrodes. Although MRR decreases with the use of AlSiMg tool electrode, good surface finish with less surface crack density on the machined surfaces has been observed as compared to other two tool electrodes. SEM and EDX analysis of the machined surfaces by different tool electrodes reveals presence of tool materials on the machined surfaces with increased carbon content. Therefore, it has been recommended that AlSiMg tool electrode can be conveniently adopted for finishing and semi-finishing operations

Analysis and characterization of weld quality during butt welding through friction stir welding

298-310In the present study, butt weld produced by friction stir welding of aluminium 1060 alloy has been analyzed. Destructive test, non-destructive test, and SEM image analysis methods have been implemented to investigate the microstructural evolution and mechanical properties of welded joints. The effects of tool rotation speed, welding speed, tool pin profile and tool offset have been investigated to optimize welding conditions for required weld properties. Face-centered central composite design of response surface methodology has been adapted to analyze the effect of parameters with an optimal number of experiments. It has been observed that weld produced with threaded pin tool has higher ultimate tensile stress and ultimate flexural stress. Radiography test has shown that cracks are not present in the produced weldment. From the study of the fracture surface of the tensile test specimen, it has been found that ductility of weld is highest at the top area and decreases towards the bottom area of weld. Dimple formation has been found at the top area of the fracture surface but has been absent in the bottom area of weld. Vickers hardness of weld zone and the heat affected zone has found to be less than the base material

Assessment of machinability of inconel 718: A comparative study of CVD & PVD coated tools

281-297This paper highlights the parametric appraisal in turning of inconel 718 using fuzzy inference system coupled with imperialistic competitive algorithm (ICA) approach. The machining variables such as spindle speed, feed rate and depth of cut have been taken into consideration to analyse their effect on evaluation characteristics viz. material removal rate (MRR), flank wear and surface roughness. Fuzzy inference system (FIS) has been used to integrate aforementioned evaluation characteristics into a single response known as multi performance characteristic index (MPCI) to address the issue of impreciseness and uncertainties involved in decision making. Mathematical models have also been proposed for MPCI using non-linear regression analysis which acts as an objective function in ICA. ICA is new meta-heuristic based on social political theory which is used to obtain global optimal parametric combination in machining of Inconel 718. The results indicate that single layer (single coating: AlTiN) physical vapour deposition (PVD) coated tool is more efficient as compared to multi-layered (four coatings: TiN, TiCN, Al2O3 and TiN) chemical vapour deposition (CVD) coated tool

Application of a Fuzzy Inference System for the Optimization of Material Removal Rate and Multiple Surface Roughness Characteristics in the Machining of GFRP Polyester Composites

This paper presents a multi-objective extended optimization methodology applied in the machining of a randomly oriented GFRP rod. Design of Experiment (DOE) has been selected based on a L9 orthogonal array design with varying process control parameters like: spindle speed, feed rate and depth of cut. Multiple surface roughness parameters of the machined FRP product along with the Material Removal Rate (MRR) of the machining process have been optimized simultaneously. The Fuzzy Inference System (FIS) has been proposed for providing feasible means for the meaningful aggregation of multiple objective functions into an equivalent single performance index (MPCI). This Multi-Performance Characteristic Index (MPCI) has been optimized using the Taguchi method. The approach adapted here is capable of overcoming limitations/ assumptions of existing optimization methodologies available in the literature

Investigation on electroless copper metallization on FDM built ABS parts

In this work, metallization of copper on acrylonitrile-butadiene-styrene (ABS) substrate has been fabricated by fused deposition modelling (FDM) using electroless process avoiding chemicals detrimental to environment. Four acidic baths containing five weight percentages of HF, H2SO4, HNO3 and H3PO4 varying copper sulphate (CuSO4) at 10, 15 and 20 weight percentage in each bath has been used for metallization. The metallization process in each bath has continued for seventy two hours. Copper coating obtained on the substrate by the use of different baths has been evaluated for electrical resistance, thickness of copper coated layer, percentage of copper present on the coated surface and adhesion performance. Scanning electron microscopy (SEM) and energy dispersion X-ray spectroscopy (EDX) results have indicated that all the baths are quite capable of deposition of copper on ABS substrates. However, HF bath has exhibited superior coating performance as compared to other baths. The thickness of copper coated layer and percentage of copper present in the coated layer has been found to be highest by the use of HF bath with fifteen weight percentage of CuSO4

Prediction of welding responses using AI approach : adaptive neuro-fuzzy inference system and genetic programming

Laser welding of thin sheets has widespread application in various fields such as battery manufacturing, automobiles, aviation, electronics circuits and medical sciences. Hence, it is very essential to develop a predictive model using artificial intelligence in order to achieve high-quality weldments in an economical manner. In the present study, two advanced artificial intelligence techniques, namely adaptive neuro-fuzzy inference system (ANFIS) and multi-gene genetic programming (MGGP), were implemented to predict the welding responses such as heat-affected zone, surface roughness and welding strength during joining of thin sheets using Nd:YAG laser. The study attempts to develop an appropriate predictive model for the welding process. In the proposed methodology, 70% of the experimental data constitutes the training set whereas remaining 30% data is used as testing set. The results of this study indicated that the root-mean-square error (RMSE) of tested data set ranges between 7 and 16% for MGGP model, while RMSE for testing data set lies 18–35% for ANFIS model. The study indicates that the MGGP predicts the welding responses in a superior manner in laser welding process and can be applied for accurate prediction of performance measures

Investigation on electroless copper metallization on FDM built ABS parts

174-181In this work, metallization of copper on acrylonitrile-butadiene-styrene (ABS) substrate has been fabricated by fused deposition modelling (FDM) using electroless process avoiding chemicals detrimental to environment. Four acidic baths containing five weight percentages of HF, H2SO4, HNO3 and H3PO4 varying copper sulphate (CuSO4) at 10, 15 and 20 weight percentage in each bath has been used for metallization. The metallization process in each bath has continued for seventy two hours. Copper coating obtained on the substrate by the use of different baths has been evaluated for electrical resistance, thickness of copper coated layer, percentage of copper present on the coated surface and adhesion performance. Scanning electron microscopy (SEM) and energy dispersion X-ray spectroscopy (EDX) results have indicated that all the baths are quite capable of deposition of copper on ABS substrates. However, HF bath has exhibited superior coating performance as compared to other baths. The thickness of copper coated layer and percentage of copper present in the coated layer has been found to be highest by the use of HF bath with fifteen weight percentage of CuSO4

Multi-Objective Optimization of Submerged Arc Welding Process

Submerged arc welding (SAW) is an important metal fabrication technology specially applied to join metals of large thickness in a single pass. In order to obtain an efficient joint, several process parameters of SAW need to be studied and precisely selected to improve weld quality. Many methodologies were proposed in the past research to address this issue. However, a good number of past work seeks to optimize SAWprocess parameters with a single response only. In practical situations, not only is the influence of process parameters and their interactive effects on output responses are to be critically examined but also an attempt is to be made to optimize more than one response, simultaneously. To this end, the present study considers four process control parameters viz. voltage (OCV), wire feed rate, traverse speed and electrode stick-out. The selected weld quality characteristics related to features of bead geometry are depth of penetration, reinforcement and bead width. In the present reporting, an integrated approach capable of solving the simultaneous optimization of multi-quality responses in SAW was suggested. In the proposed approach, the responses were transformed into their individual desirability values by selecting appropriate desirability function. Assuming equal importance for all responses, these individual desirability values were aggregated to calculate the overall desirability values. Quadratic Response Surface Methodology (RSM) was applied to establish a mathematical model representing overall desirability as a function involving linear, quadratic and interaction effect of process control parameters. This model was optimized finally within the experimental domain using PSO (Particle Swarm Optimization) algorithm. A confirmatory test showed a satisfactory result. A detailed methodology of RSM, desirability function (DF) and a PSO-based optimization approach was illustrated in the paper

Multi-Objective Optimization of Submerged Arc Welding Process

Submerged arc welding (SAW) is an important metal fabrication technology specially applied to join metals of large thickness in a single pass. In order to obtain an efficient joint, several process parameters of SAW need to be studied and precisely selected to improve weld quality. Many methodologies were proposed in the past research to address this issue. However, a good number of past work seeks to optimize SAWprocess parameters with a single response only. In practical situations, not only is the influence of process parameters and their interactive effects on output responses are to be critically examined but also an attempt is to be made to optimize more than one response, simultaneously. To this end, the present study considers four process control parameters viz. voltage (OCV), wire feed rate, traverse speed and electrode stick-out. The selected weld quality characteristics related to features of bead geometry are depth of penetration, reinforcement and bead width. In the present reporting, an integrated approach capable of solving the simultaneous optimization of multi-quality responses in SAW was suggested. In the proposed approach, the responses were transformed into their individual desirability values by selecting appropriate desirability function. Assuming equal importance for all responses, these individual desirability values were aggregated to calculate the overall desirability values. Quadratic Response Surface Methodology (RSM) was applied to establish a mathematical model representing overall desirability as a function involving linear, quadratic and interaction effect of process control parameters. This model was optimized finally within the experimental domain using PSO (Particle Swarm Optimization) algorithm. A confirmatory test showed a satisfactory result. A detailed methodology of RSM, desirability function (DF) and a PSO-based optimization approach was illustrated in the paper

An integrated approach for scheduling flexible job-shop using teaching–learning-based optimization method

Abstract In this paper, teaching–learning-based optimization (TLBO) is proposed to solve flexible job shop scheduling problem (FJSP) based on the integrated approach with an objective to minimize makespan. An FJSP is an extension of basic job-shop scheduling problem. There are two sub problems in FJSP. They are routing problem and sequencing problem. If both the sub problems are solved simultaneously, then the FJSP comes under integrated approach. Otherwise, it becomes a hierarchical approach. Very less research has been done in the past on FJSP problem as it is an NP-hard (non-deterministic polynomial time hard) problem and very difficult to solve till date. Further, very less focus has been given to solve the FJSP using an integrated approach. So an attempt has been made to solve FJSP based on integrated approach using TLBO. Teaching–learning-based optimization is a meta-heuristic algorithm which does not have any algorithm-specific parameters that are to be tuned in comparison to other meta-heuristics. Therefore, it can be considered as an efficient algorithm. As best student of the class is considered as teacher, after few iterations all the students learn and reach the same knowledge level, due to which there is a loss in diversity in the population. So, like many meta-heuristics, TLBO also has a tendency to get trapped at the local optimum. To avoid this limitation, a new local search technique followed by a mutation strategy (from genetic algorithm) is incorporated to TLBO to improve the quality of the solution and to maintain diversity, respectively, in the population. Tests have been carried out on all Kacem’s instances and Brandimarte's data instances to calculate makespan. Results show that TLBO outperformed many other algorithms and can be a competitive method for solving the FJSP