Multi-regression prediction model for surface roughness and tool wear in turning novel aluminum alloy (LM6)/fly ash composite using response surface and central composite design methodology
Turning experiments were conducted on a novel aluminum alloy (LM6)/fly ash composite based on the response surface and face centered central composite design methodology. The effects of cutting parameters on surface roughness and tool wear were investigated. Multiple regression models were developed...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Growing Science
2017-01-01
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| Series: | International Journal of Industrial Engineering Computations |
| Subjects: | |
| Online Access: | http://www.growingscience.com/ijiec/Vol8/IJIEC_2016_25.pdf |
| _version_ | 1818683315787399168 |
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| author | Smita Rani Panda Ajit Kumar Senapati Purna Chandra Mishra |
| author_facet | Smita Rani Panda Ajit Kumar Senapati Purna Chandra Mishra |
| author_sort | Smita Rani Panda |
| collection | DOAJ |
| description | Turning experiments were conducted on a novel aluminum alloy (LM6)/fly ash composite based on the response surface and face centered central composite design methodology. The effects of cutting parameters on surface roughness and tool wear were investigated. Multiple regression models were developed for the responses and the adequacies of the developed models were tested at 95% confidence interval using the analysis of variance (ANOVA) technique. Carbide inserts (Model: CNMG 120408-M5) were used for turning the specimens in a CNC turning machine (model: LT-16). The test for significance of the regression models, the test for significance on individual model coefficients and the lack-of-fit tests were performed using the statistical Design-Expert7.0v software environments. R2 indicated the model significance and the value was more than 97%, revealed that the relation between cutting responses and input parameters held good for more than 97% and the model was adequate. |
| first_indexed | 2024-12-17T10:32:47Z |
| format | Article |
| id | doaj.art-bac47fefca624da4ad6cf6cd45bc2ce5 |
| institution | Directory Open Access Journal |
| issn | 1923-2926 1923-2934 |
| language | English |
| last_indexed | 2024-12-17T10:32:47Z |
| publishDate | 2017-01-01 |
| publisher | Growing Science |
| record_format | Article |
| series | International Journal of Industrial Engineering Computations |
| spelling | doaj.art-bac47fefca624da4ad6cf6cd45bc2ce52022-12-21T21:52:29ZengGrowing ScienceInternational Journal of Industrial Engineering Computations1923-29261923-29342017-01-018111810.5267/j.ijiec.2016.8.001Multi-regression prediction model for surface roughness and tool wear in turning novel aluminum alloy (LM6)/fly ash composite using response surface and central composite design methodologySmita Rani PandaAjit Kumar Senapati Purna Chandra MishraTurning experiments were conducted on a novel aluminum alloy (LM6)/fly ash composite based on the response surface and face centered central composite design methodology. The effects of cutting parameters on surface roughness and tool wear were investigated. Multiple regression models were developed for the responses and the adequacies of the developed models were tested at 95% confidence interval using the analysis of variance (ANOVA) technique. Carbide inserts (Model: CNMG 120408-M5) were used for turning the specimens in a CNC turning machine (model: LT-16). The test for significance of the regression models, the test for significance on individual model coefficients and the lack-of-fit tests were performed using the statistical Design-Expert7.0v software environments. R2 indicated the model significance and the value was more than 97%, revealed that the relation between cutting responses and input parameters held good for more than 97% and the model was adequate.http://www.growingscience.com/ijiec/Vol8/IJIEC_2016_25.pdfAluminum alloy matrixFly ashTurningResponse surface methodCentral composite design |
| spellingShingle | Smita Rani Panda Ajit Kumar Senapati Purna Chandra Mishra Multi-regression prediction model for surface roughness and tool wear in turning novel aluminum alloy (LM6)/fly ash composite using response surface and central composite design methodology International Journal of Industrial Engineering Computations Aluminum alloy matrix Fly ash Turning Response surface method Central composite design |
| title | Multi-regression prediction model for surface roughness and tool wear in turning novel aluminum alloy (LM6)/fly ash composite using response surface and central composite design methodology |
| title_full | Multi-regression prediction model for surface roughness and tool wear in turning novel aluminum alloy (LM6)/fly ash composite using response surface and central composite design methodology |
| title_fullStr | Multi-regression prediction model for surface roughness and tool wear in turning novel aluminum alloy (LM6)/fly ash composite using response surface and central composite design methodology |
| title_full_unstemmed | Multi-regression prediction model for surface roughness and tool wear in turning novel aluminum alloy (LM6)/fly ash composite using response surface and central composite design methodology |
| title_short | Multi-regression prediction model for surface roughness and tool wear in turning novel aluminum alloy (LM6)/fly ash composite using response surface and central composite design methodology |
| title_sort | multi regression prediction model for surface roughness and tool wear in turning novel aluminum alloy lm6 fly ash composite using response surface and central composite design methodology |
| topic | Aluminum alloy matrix Fly ash Turning Response surface method Central composite design |
| url | http://www.growingscience.com/ijiec/Vol8/IJIEC_2016_25.pdf |
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