Papers by Author: S.S. Mahapatra

Abstract: In this research work, an efficient optimization technique, grey relational analysis (GRA) has been used to for optimization of wire electrical discharge machining process of Titanium (grade 2) by considering multiple output parameters. This technique combines Taguchi’s orthogonal array with grey relational analysis for the design of the experiment. The central focus of this research is to achieve improved Kerf width, surface roughness and cutting speed. GRA method is implemented to decide the best input parameter that optimizes the output parameters. This study has been conducted by applying Taguchi’s L9 orthogonal array. Each experiment has been conducted in altered conditions of input variables. For the optimization of multiple criteria, GRA is suggested as a suitable technique for the optimization of complex interrelationships between multi-performance characteristics. By analysis of variance (ANOVA) it is found that the percentage of contribution of peak current on overall performance is maximum i.e.73.1%.

Abstract: Carbon Fiber Reinforced Polymer (CFRP) composite materials find varied engineering applications especially in automotive, aircraft and locomotive industries. Hence, it has become essential to study machining and machinability aspects of these composites. This paper reports an application of harmony research (HS) algorithm through a case experimental research in order to obtain optimal parametric combination in turning of CFRP (epoxy) composites. Taguchi’s L₉ orthogonal array has been used for experimentation. The performance indices such as surface roughness and cutting force have been chosen; and corresponding machining parameters that have been studied like spindle speed, feed rate and depth of cut. Optimal results have also been compared with genetic algorithm (GA); it has been revealed that harmony search method provided better result as compared to genetic algorithm.

Abstract: Fused deposition modelling (FDM) is one of the rapid prototyping (RP) processes that build part of any geometry by sequential deposition of material on a layer by layer basis. Unlike other RP systems which involve an array of lasers, powders, resins, this process uses heated thermoplastic filaments which are extruded from the tip of nozzle in a prescribed manner. Present work focuses on extensive study to understand the effect of five important parameters such as layer thickness, part build orientation, raster angle, raster width and air gap on the sliding wear of test specimen built through FDM. The study provides insight into complex dependency of wear on process parameters and proposes a statistically validated predictive equation. Microphotographs are used to explain the mechanism of wear. Finally, the predictive equation is used to find optimal parameter setting through bacteria foraging optimization algorithm (BFOA).

Abstract: Quality and productivity are two important aspects have become great concerns in todays competitive global market. Every manufacturing/ production unit mainly focuses on these areas in relation to the process as well as product developed. Achieving high quality necessarily requires higher degree of skill, sophisticated machine/ tools, advanced technology, precise control, immense attention-inspection and considerable time. Improvement of quality results reduction in productivity and vice versa. Thus, optimality must be maintained between quality as well as productivity. The case study highlights EDM of stainless steel in which best process environment (optimal) has been determined to satisfy productivity and quality requirements simultaneously. Material Removal Rate (MRR) during the process has been considered as productivity estimate with the aim to maximize it; whereas surface roughness i.e. (R_a value) of the machined surface has been chosen as surface quality estimate with the requirement to minimize it. These two contradicting requirements have been simultaneously satisfied by selecting an optimal process environment (optimal parameter setting). Desirability Function (DF) approach coupled with Taguchi method has been used to solve the problem.

Abstract: Reverse logistics (RL), which refers to the distribution activities involved in product returns, has recently received much attention because many companies are using it as a strategic tool to serve their customers and can generate good revenue. An efficient reverse distribution structure may lead to a significant return on investment as well as a significantly increased competitiveness in the market. Therefore, analysis of the interaction among the major barriers, which hinder or prevent the application of reverse logistics, is a crucial issue. Existing models have focused on diagnosing these barriers independently. As a result, the holistic view in understanding the barriers is not accounted for. This paper utilizes the Interpretive Structural Modeling (ISM) methodology to understand the mutual influences among the barriers so that those driving barriers, which can aggravate few more barriers and those independent barriers, which are most influenced by driving barriers, are identified.

Abstract: The present work attempts to overcome underlying assumptions in traditional Taguchi based optimization techniques highlighted in literature. Taguchi method alone fails to solve multi-response optimization problems. In order to overcome this limitation, exploration of grey relation theory, desirability function approach, utility theory etc. have been found amply applied in literature in combination with Taguchi method. But aforesaid approaches relies on the assumption that individual response features are uncorrelated i.e. independent of each other which are really impossible to happen in practice. The study takes into account this response correlation and proposes an integrated methodology in a case study on optimization of multiple bead geometry parameters of submerged arc weldment. Weighted Principal Component Analysis (WPCA) has been applied to eliminate response correlation and to convert correlated responses into equal or less number of uncorrelated quality indices called principal components. Based on individual principal components a Multi-response Performance Index (MPI) has been introduced to derive an equivalent single objective function which has been optimized (maximized) using Taguchi method. Experiments have been conducted based on Taguchi’s L25 Orthogonal Array design with combinations of process control parameters: voltage, wire feed, welding speed and electrode stick-out. Different bead geometry parameters: bead width, bead height, penetration depth and HAZ dimensions have been optimized. Optimal result has been verified by confirmatory test. The study highlights effectiveness of the proposed method for solving multi-objective optimization of submerged arc weld.