Multi-response optimization of CuZn39Pb3 brass alloy turning by implementing Grey Wolf algorithm
Machinability of engineering materials is crucial for industrial manufacturing processes since it affects all the essential aspects involved, e.g. workload, resources, surface integrity and part quality. Two basic machinability parameters are the surface roughness, closely associated with the fu...
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| Format: | Article |
| Language: | English |
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Gruppo Italiano Frattura
2019-09-01
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| Series: | Fracture and Structural Integrity |
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| Online Access: | https://www.fracturae.com/index.php/fis/article/view/2626 |
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| author | Nikolaos Fountas Angelos Koutsomichalis John Kechagias Nikolaos Vaxevanidis |
| author_facet | Nikolaos Fountas Angelos Koutsomichalis John Kechagias Nikolaos Vaxevanidis |
| author_sort | Nikolaos Fountas |
| collection | DOAJ |
| description | Machinability of engineering materials is crucial for industrial manufacturing processes since it affects all the essential aspects involved, e.g. workload, resources, surface integrity and part quality. Two basic machinability parameters are the surface roughness, closely associated with the functional and tribological performance of components, and the cutting forces acting on the tool. Knowledge of the cutting forces is needed for estimation of power requirements and for the design of machine tool elements, tool-holders and fixtures, adequately rigid and free from vibration. This work investigates the influence of cutting conditions on machinability indicators such as the main cutting force Fc and surface roughness parameters Ra and Rt when longitudinally turning CuZn39Pb3 brass alloy. Full quadratic regression models were developed to correlate the machining conditions with the imparted machinability characteristics. Further on, an advanced artificial grey wolf optimization algorithm was implemented to optimize the aforementioned responses with great success in finding the final optimal values of the turning parameters. |
| format | Article |
| id | doaj-art-9d68b261d4f64bdbb58c4e7179d645b8 |
| institution | DOAJ |
| issn | 1971-8993 |
| language | English |
| publishDate | 2019-09-01 |
| publisher | Gruppo Italiano Frattura |
| record_format | Article |
| series | Fracture and Structural Integrity |
| spelling | doaj-art-9d68b261d4f64bdbb58c4e7179d645b82025-08-20T02:51:43ZengGruppo Italiano FratturaFracture and Structural Integrity1971-89932019-09-011350Multi-response optimization of CuZn39Pb3 brass alloy turning by implementing Grey Wolf algorithmNikolaos Fountas0Angelos Koutsomichalis1John Kechagias2Nikolaos Vaxevanidis3School of Pedagogical and Technological Education, Department of Mechanical Engineering Educators, Laboratory of Manufacturing Processes and Machine Tools, ASPETE Campus, GR 14121, N. Heraklion, GreeceHellenic Air-Force Academy, Faculty of Aerospace Studies, Dekelia Air Force Base, GR 19005, GreeceTechnological Educational Institute of Thessaly, Mechanical Engineering Department, TEI Campus, GR 41110, Larissa, GreeceSchool of Pedagogical and Technological Education, Department of Mechanical Engineering Educators, Laboratory of Manufacturing Processes and Machine Tools, ASPETE Campus, GR 14121, N. Heraklion, GreeceMachinability of engineering materials is crucial for industrial manufacturing processes since it affects all the essential aspects involved, e.g. workload, resources, surface integrity and part quality. Two basic machinability parameters are the surface roughness, closely associated with the functional and tribological performance of components, and the cutting forces acting on the tool. Knowledge of the cutting forces is needed for estimation of power requirements and for the design of machine tool elements, tool-holders and fixtures, adequately rigid and free from vibration. This work investigates the influence of cutting conditions on machinability indicators such as the main cutting force Fc and surface roughness parameters Ra and Rt when longitudinally turning CuZn39Pb3 brass alloy. Full quadratic regression models were developed to correlate the machining conditions with the imparted machinability characteristics. Further on, an advanced artificial grey wolf optimization algorithm was implemented to optimize the aforementioned responses with great success in finding the final optimal values of the turning parameters.https://www.fracturae.com/index.php/fis/article/view/2626TurningSurface roughnessCutting forcesMulti-parameter analysisOptimizationGrey Wolf algorithm |
| spellingShingle | Nikolaos Fountas Angelos Koutsomichalis John Kechagias Nikolaos Vaxevanidis Multi-response optimization of CuZn39Pb3 brass alloy turning by implementing Grey Wolf algorithm Fracture and Structural Integrity Turning Surface roughness Cutting forces Multi-parameter analysis Optimization Grey Wolf algorithm |
| title | Multi-response optimization of CuZn39Pb3 brass alloy turning by implementing Grey Wolf algorithm |
| title_full | Multi-response optimization of CuZn39Pb3 brass alloy turning by implementing Grey Wolf algorithm |
| title_fullStr | Multi-response optimization of CuZn39Pb3 brass alloy turning by implementing Grey Wolf algorithm |
| title_full_unstemmed | Multi-response optimization of CuZn39Pb3 brass alloy turning by implementing Grey Wolf algorithm |
| title_short | Multi-response optimization of CuZn39Pb3 brass alloy turning by implementing Grey Wolf algorithm |
| title_sort | multi response optimization of cuzn39pb3 brass alloy turning by implementing grey wolf algorithm |
| topic | Turning Surface roughness Cutting forces Multi-parameter analysis Optimization Grey Wolf algorithm |
| url | https://www.fracturae.com/index.php/fis/article/view/2626 |
| work_keys_str_mv | AT nikolaosfountas multiresponseoptimizationofcuzn39pb3brassalloyturningbyimplementinggreywolfalgorithm AT angeloskoutsomichalis multiresponseoptimizationofcuzn39pb3brassalloyturningbyimplementinggreywolfalgorithm AT johnkechagias multiresponseoptimizationofcuzn39pb3brassalloyturningbyimplementinggreywolfalgorithm AT nikolaosvaxevanidis multiresponseoptimizationofcuzn39pb3brassalloyturningbyimplementinggreywolfalgorithm |