Optimization of Cutting Parameters for Milling Process of (4032) Al-Alloy using Taguchi-Based Grey Relational Analysis
The objective of this work is to study the influence of end milling cutting process parameters, tool material and geometry on multi-response outputs for 4032 Al-alloy. This can be done by proposing an approach that combines Taguchi method with grey relational analysis. Three cutting parameters have...
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| Format: | Article |
| Language: | English |
| Published: |
Al-Khwarizmi College of Engineering – University of Baghdad
2021-09-01
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| Series: | Al-Khawarizmi Engineering Journal |
| Online Access: | https://alkej.uobaghdad.edu.iq/index.php/alkej/article/view/740 |
| _version_ | 1818879390479548416 |
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| author | Sami Abbas Hammood |
| author_facet | Sami Abbas Hammood |
| author_sort | Sami Abbas Hammood |
| collection | DOAJ |
| description | The objective of this work is to study the influence of end milling cutting process parameters, tool material and geometry on multi-response outputs for 4032 Al-alloy. This can be done by proposing an approach that combines Taguchi method with grey relational analysis. Three cutting parameters have been selected (spindle speed, feed rate and cut depth) with three levels for each parameter. Three tools with different materials and geometry have been also used to design the experimental tests and runs based on matrix L9. The end milling process with several output characteristics is solved using a grey relational analysis. The results of analysis of variance (ANOVA) showed that the major influencing parameters on multi-objective response were spindle speed and cutting tool with contribution percentage (52.75%, 24%), respectively. In addition, the optimum combination of end milling process parameters was then validated by performing confirmation tests to determine the improvement in multi-response outputs. The confirmation tests obtained a minimum (surface roughness and micro-hardness) and maximum metal removal rate with grey relational grade of 0.784 and improvement percentage of 2.3%. |
| first_indexed | 2024-12-19T14:29:19Z |
| format | Article |
| id | doaj.art-63e91097712b4d2382bbb12d5bda9fb5 |
| institution | Directory Open Access Journal |
| issn | 1818-1171 2312-0789 |
| language | English |
| last_indexed | 2024-12-19T14:29:19Z |
| publishDate | 2021-09-01 |
| publisher | Al-Khwarizmi College of Engineering – University of Baghdad |
| record_format | Article |
| series | Al-Khawarizmi Engineering Journal |
| spelling | doaj.art-63e91097712b4d2382bbb12d5bda9fb52022-12-21T20:17:30ZengAl-Khwarizmi College of Engineering – University of BaghdadAl-Khawarizmi Engineering Journal1818-11712312-07892021-09-0117310.22153/kej.2021.06.001Optimization of Cutting Parameters for Milling Process of (4032) Al-Alloy using Taguchi-Based Grey Relational AnalysisSami Abbas Hammood0Department of Production Engineering and Metallurgy/ University of Technology/ Baghdad/ IraqThe objective of this work is to study the influence of end milling cutting process parameters, tool material and geometry on multi-response outputs for 4032 Al-alloy. This can be done by proposing an approach that combines Taguchi method with grey relational analysis. Three cutting parameters have been selected (spindle speed, feed rate and cut depth) with three levels for each parameter. Three tools with different materials and geometry have been also used to design the experimental tests and runs based on matrix L9. The end milling process with several output characteristics is solved using a grey relational analysis. The results of analysis of variance (ANOVA) showed that the major influencing parameters on multi-objective response were spindle speed and cutting tool with contribution percentage (52.75%, 24%), respectively. In addition, the optimum combination of end milling process parameters was then validated by performing confirmation tests to determine the improvement in multi-response outputs. The confirmation tests obtained a minimum (surface roughness and micro-hardness) and maximum metal removal rate with grey relational grade of 0.784 and improvement percentage of 2.3%.https://alkej.uobaghdad.edu.iq/index.php/alkej/article/view/740 |
| spellingShingle | Sami Abbas Hammood Optimization of Cutting Parameters for Milling Process of (4032) Al-Alloy using Taguchi-Based Grey Relational Analysis Al-Khawarizmi Engineering Journal |
| title | Optimization of Cutting Parameters for Milling Process of (4032) Al-Alloy using Taguchi-Based Grey Relational Analysis |
| title_full | Optimization of Cutting Parameters for Milling Process of (4032) Al-Alloy using Taguchi-Based Grey Relational Analysis |
| title_fullStr | Optimization of Cutting Parameters for Milling Process of (4032) Al-Alloy using Taguchi-Based Grey Relational Analysis |
| title_full_unstemmed | Optimization of Cutting Parameters for Milling Process of (4032) Al-Alloy using Taguchi-Based Grey Relational Analysis |
| title_short | Optimization of Cutting Parameters for Milling Process of (4032) Al-Alloy using Taguchi-Based Grey Relational Analysis |
| title_sort | optimization of cutting parameters for milling process of 4032 al alloy using taguchi based grey relational analysis |
| url | https://alkej.uobaghdad.edu.iq/index.php/alkej/article/view/740 |
| work_keys_str_mv | AT samiabbashammood optimizationofcuttingparametersformillingprocessof4032alalloyusingtaguchibasedgreyrelationalanalysis |