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Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/1194

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contributor.authorDatta, S-
contributor.authorMahapatra, S S-
contributor.authorBandyopadhyay, A-
date.accessioned2010-03-10T10:08:28Z-
date.available2010-03-10T10:08:28Z-
date.issued2010-
identifier.citationNational Seminar on Joining Processes: Challenges for Quality, Design and Development, organized by Mechanical and Production Engineering Department, held during March 5-6, 2010 at National Institute of Technology, Agartala, Tripura.en
identifier.urihttp://hdl.handle.net/2080/1194-
description.abstractThere are several bead geometry parameters which indicate quality of submerged arc weldment. These includes, bead height, penetration depth, bead width, percentage dilution etc. Achieving an optimal weld, with desired quality features, is really a challenging job. Because, these quality features are highly correlated and are expected to be influenced directly or indirectly by the direct effect of process parameters or their interactive effects (i.e. on process environment). However, the extents of significant influence of the process parameters are different for different responses. Therefore, SAW is a multi-factor, multi-objective metal fabrication process. It is desired that, an optimal weld should confirm lesser bead height and width, to reduce excess weld metal consumption; deeper penetration and higher parentage of dilution, in order to increase joint strength. Therefore, to solve such a multi-objective optimization problem, it is felt necessary to identify the optimal parametric combination, following which all objectives could be optimized simultaneously. In this context, it is essential to convert all the objective functions into an equivalent single objective function or overall representative function to meet desired multi-quality features of the weldment. The required multiquality features may or may not be conflicting in nature. The representative single objective function, thus calculated, would be optimized finally. In the present work, Design of Experiment (DOE) with Taguchi L16 Orthogonal Array (OA) has been explored to produce 16 weld specimens on mild steel plates by SAW. Collected data related to weld bead geometry have been utilized for optimization. Principal Component Analysis (PCA) has been applied to eliminate correlation among the responses and to evaluate independent or uncorrelated quality indices called principal components. Based on quality loss of individual principal components with respect to the ideal condition, an overall grey relational grade of the weldment has been calculated to serve as the single objective function for optimization. Finally, Taguchi method has been adopted for searching optimal process condition to yield desired quality of weld bead geometry. Result of the aforesaid optimization procedure has been verified through confirmatory test. The study illustrates the detailed methodology of PCA based grey-Taguchi method and its effectiveness for multi-response optimization in SAW.en
format.extent137201 bytes-
format.mimetypeapplication/pdf-
language.isoen-
subjectSAW,en
subjectPCA,en
subjectTaguchi method,en
subjectoverall grey relational gradeen
titleElimination of Multi-response Correlation while Applying Taguchi Philosophy in Optimization of Submerged Arc Welden
typeArticleen
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