Investigation of Machinability Characteristics of EDMed Inconel 825 Alloy under Multidimensional Parametric Modeling by Using Holistic Grey-PCA Statistical Models

The current social and industrial communities exceedingly demanded the materials that dealt with rich mechanical properties, i.e., the rich strength, hardness, reliability, high resistance against corrosion and oxidation, and high toughness and refractoriness. Recently, the researchers ascertained t...

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Main Authors: Nitin Kumar Sahu, Mukesh Kumar Singh, Bupe Getrude Mutono-Mwanza, Atul Kumar Sahu
Format: Article
Language:English
Published: Wiley 2022-01-01
Series:Advances in Materials Science and Engineering
Online Access:http://dx.doi.org/10.1155/2022/3147586
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author Nitin Kumar Sahu
Mukesh Kumar Singh
Bupe Getrude Mutono-Mwanza
Atul Kumar Sahu
author_facet Nitin Kumar Sahu
Mukesh Kumar Singh
Bupe Getrude Mutono-Mwanza
Atul Kumar Sahu
author_sort Nitin Kumar Sahu
collection DOAJ
description The current social and industrial communities exceedingly demanded the materials that dealt with rich mechanical properties, i.e., the rich strength, hardness, reliability, high resistance against corrosion and oxidation, and high toughness and refractoriness. Recently, the researchers ascertained the comprehensive applications of these difficult to machine materials in the domain of automotive, aeronautical, nuclear industries etc. It is claimed that it is quite hard and expensive for machining these superadvanced materials by traditional machining operations. In the present study, worldwide promising nickel-based superalloy Inconel 825 material is used due to its outstanding mechanical and thermal properties at eminent temperatures and also having broad application in imperative engineering fields. The authors probed that machining cost and smart machinability index have become the gigantic concern in EDM operation; however, these can be minimized by adapting a conduit of evaluation of the optimum setting among multiple input parameters. It was a challenging task, which is respected by authors as the research gaps to be sorted out. To fulfill research gaps, the authors encountered imperative significant EDM input parameters, i.e., spark gap (Sg), gap voltage (Vg), pulse on time (Ton), pulse off time (Toff), Peak Current (Ip), Servo feed (Sf), Depth of Cut (Dc) and difficulty index (Di) corresponding to output responses, i.e., power consumption (Pc), machining time (Mt), and material removal rate (MRR) for framing the machinability index/model for conducting experiments and collecting objectives/responses/outputs. Next, the authors conducted experiments using the Taguchi L27 orthogonal array model in the nonvibratory domain for recording output responses. Later, to potentially access the results, the authors integrated the computational Taguchi methodology with dual models which is called as Taguchi-grey relational analysis (T-GRA) and Taguchi-principal component analysis (T-PCA). The optimum setting condition among considered inputs is discussed in the conclusion section. Later, confirmatory test gratified the evaluated optimum settings which is yielding an improvement of 0.16262 and 0.34398 score in executing T-GRA and T-PCA, respectively. In continuation, the current research evidenced that pulse off time is the chief significant process parameter having p values 0.005 and 0.001 for T-GRA and T-PCA, respectively. It is also seen that the depth of cut is also another important significant process parameter having p values 0.061 and 0.073 for T-GRA and T-PCA, respectively. Moreover, the current research work also investigated the effect of variation of momentous input process parameters over the surface topography and their utility in improving surface integrity and eliminating the micropores and cracks.
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spelling doaj-art-39a5cd097c5f4e66ad545321a3a1547c2025-02-03T05:50:02ZengWileyAdvances in Materials Science and Engineering1687-84422022-01-01202210.1155/2022/3147586Investigation of Machinability Characteristics of EDMed Inconel 825 Alloy under Multidimensional Parametric Modeling by Using Holistic Grey-PCA Statistical ModelsNitin Kumar Sahu0Mukesh Kumar Singh1Bupe Getrude Mutono-Mwanza2Atul Kumar Sahu3Department of Industrial and Production EngineeringDepartment of Industrial and Production EngineeringGraduate School of BusinessDepartment of Industrial and Production EngineeringThe current social and industrial communities exceedingly demanded the materials that dealt with rich mechanical properties, i.e., the rich strength, hardness, reliability, high resistance against corrosion and oxidation, and high toughness and refractoriness. Recently, the researchers ascertained the comprehensive applications of these difficult to machine materials in the domain of automotive, aeronautical, nuclear industries etc. It is claimed that it is quite hard and expensive for machining these superadvanced materials by traditional machining operations. In the present study, worldwide promising nickel-based superalloy Inconel 825 material is used due to its outstanding mechanical and thermal properties at eminent temperatures and also having broad application in imperative engineering fields. The authors probed that machining cost and smart machinability index have become the gigantic concern in EDM operation; however, these can be minimized by adapting a conduit of evaluation of the optimum setting among multiple input parameters. It was a challenging task, which is respected by authors as the research gaps to be sorted out. To fulfill research gaps, the authors encountered imperative significant EDM input parameters, i.e., spark gap (Sg), gap voltage (Vg), pulse on time (Ton), pulse off time (Toff), Peak Current (Ip), Servo feed (Sf), Depth of Cut (Dc) and difficulty index (Di) corresponding to output responses, i.e., power consumption (Pc), machining time (Mt), and material removal rate (MRR) for framing the machinability index/model for conducting experiments and collecting objectives/responses/outputs. Next, the authors conducted experiments using the Taguchi L27 orthogonal array model in the nonvibratory domain for recording output responses. Later, to potentially access the results, the authors integrated the computational Taguchi methodology with dual models which is called as Taguchi-grey relational analysis (T-GRA) and Taguchi-principal component analysis (T-PCA). The optimum setting condition among considered inputs is discussed in the conclusion section. Later, confirmatory test gratified the evaluated optimum settings which is yielding an improvement of 0.16262 and 0.34398 score in executing T-GRA and T-PCA, respectively. In continuation, the current research evidenced that pulse off time is the chief significant process parameter having p values 0.005 and 0.001 for T-GRA and T-PCA, respectively. It is also seen that the depth of cut is also another important significant process parameter having p values 0.061 and 0.073 for T-GRA and T-PCA, respectively. Moreover, the current research work also investigated the effect of variation of momentous input process parameters over the surface topography and their utility in improving surface integrity and eliminating the micropores and cracks.http://dx.doi.org/10.1155/2022/3147586
spellingShingle Nitin Kumar Sahu
Mukesh Kumar Singh
Bupe Getrude Mutono-Mwanza
Atul Kumar Sahu
Investigation of Machinability Characteristics of EDMed Inconel 825 Alloy under Multidimensional Parametric Modeling by Using Holistic Grey-PCA Statistical Models
Advances in Materials Science and Engineering
title Investigation of Machinability Characteristics of EDMed Inconel 825 Alloy under Multidimensional Parametric Modeling by Using Holistic Grey-PCA Statistical Models
title_full Investigation of Machinability Characteristics of EDMed Inconel 825 Alloy under Multidimensional Parametric Modeling by Using Holistic Grey-PCA Statistical Models
title_fullStr Investigation of Machinability Characteristics of EDMed Inconel 825 Alloy under Multidimensional Parametric Modeling by Using Holistic Grey-PCA Statistical Models
title_full_unstemmed Investigation of Machinability Characteristics of EDMed Inconel 825 Alloy under Multidimensional Parametric Modeling by Using Holistic Grey-PCA Statistical Models
title_short Investigation of Machinability Characteristics of EDMed Inconel 825 Alloy under Multidimensional Parametric Modeling by Using Holistic Grey-PCA Statistical Models
title_sort investigation of machinability characteristics of edmed inconel 825 alloy under multidimensional parametric modeling by using holistic grey pca statistical models
url http://dx.doi.org/10.1155/2022/3147586
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