Multiple Regression Analysis and Non-Dominated Sorting Genetic Algorithm II Optimization of Machining Carbon-Fiber-Reinforced Polyethylene Terephthalate Glycol Parts Fabricated via Additive Manufacturing Under Dry and Lubricated Conditions
The present research deals with the processing of the additively manufactured Carbon-Fiber-Reinforced Polymer (CFRP) under dry and lubricated cutting conditions, focusing on the generated surface roughness. The cutting speed, feed, and depth of cut were selected as the continuous variables. A compar...
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MDPI AG
2025-02-01
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| author | Anastasios Tzotzis Nikolaos Efkolidis Kai Cheng Panagiotis Kyratsis |
| author_facet | Anastasios Tzotzis Nikolaos Efkolidis Kai Cheng Panagiotis Kyratsis |
| author_sort | Anastasios Tzotzis |
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| description | The present research deals with the processing of the additively manufactured Carbon-Fiber-Reinforced Polymer (CFRP) under dry and lubricated cutting conditions, focusing on the generated surface roughness. The cutting speed, feed, and depth of cut were selected as the continuous variables. A comparison between the generated surface roughness of the dry and the lubricated cuts revealed that the presence of coolant contributed towards reducing surface roughness by more than 20% in most cases. Next, a regression analysis was performed with the obtained measurements, yielding a robust prediction model, with the determination coefficient <i>R</i><sup>2</sup> being equal to 94.65%. It was determined that feed and the corresponding interactions contributed more than 45% to the model’s <i>R</i><sup>2</sup>, followed by the depth of cut and the machining condition. In addition, the cutting speed was the variable with the least effect on the response. The Non-Dominated Sorting Genetic Algorithm 2 (NSGA-II) was employed to identify the front of optimal solutions that consider both minimizing surface roughness and maximizing Material Removal Rate (MRR). Finally, a set of extra experiments proved the validity of the model by exhibiting relative error values, between the measured and predicted roughness, below 10%. |
| format | Article |
| id | doaj-art-a87d2394e1c8433db4f56a24e125c3bd |
| institution | DOAJ |
| issn | 2075-4442 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Lubricants |
| spelling | doaj-art-a87d2394e1c8433db4f56a24e125c3bd2025-08-20T03:12:02ZengMDPI AGLubricants2075-44422025-02-011326310.3390/lubricants13020063Multiple Regression Analysis and Non-Dominated Sorting Genetic Algorithm II Optimization of Machining Carbon-Fiber-Reinforced Polyethylene Terephthalate Glycol Parts Fabricated via Additive Manufacturing Under Dry and Lubricated ConditionsAnastasios Tzotzis0Nikolaos Efkolidis1Kai Cheng2Panagiotis Kyratsis3Department of Product and Systems Design Engineering, University of Western Macedonia, 50100 Kila Kozani, GreeceDepartment of Product and Systems Design Engineering, University of Western Macedonia, 50100 Kila Kozani, GreeceDepartment of Mechanical and Aerospace Engineering, Brunel University London, Uxbridge UB8 3PH, UKDepartment of Product and Systems Design Engineering, University of Western Macedonia, 50100 Kila Kozani, GreeceThe present research deals with the processing of the additively manufactured Carbon-Fiber-Reinforced Polymer (CFRP) under dry and lubricated cutting conditions, focusing on the generated surface roughness. The cutting speed, feed, and depth of cut were selected as the continuous variables. A comparison between the generated surface roughness of the dry and the lubricated cuts revealed that the presence of coolant contributed towards reducing surface roughness by more than 20% in most cases. Next, a regression analysis was performed with the obtained measurements, yielding a robust prediction model, with the determination coefficient <i>R</i><sup>2</sup> being equal to 94.65%. It was determined that feed and the corresponding interactions contributed more than 45% to the model’s <i>R</i><sup>2</sup>, followed by the depth of cut and the machining condition. In addition, the cutting speed was the variable with the least effect on the response. The Non-Dominated Sorting Genetic Algorithm 2 (NSGA-II) was employed to identify the front of optimal solutions that consider both minimizing surface roughness and maximizing Material Removal Rate (MRR). Finally, a set of extra experiments proved the validity of the model by exhibiting relative error values, between the measured and predicted roughness, below 10%.https://www.mdpi.com/2075-4442/13/2/63additive manufacturingCFRPflooded coolingmachiningNSGA-IIPET-G |
| spellingShingle | Anastasios Tzotzis Nikolaos Efkolidis Kai Cheng Panagiotis Kyratsis Multiple Regression Analysis and Non-Dominated Sorting Genetic Algorithm II Optimization of Machining Carbon-Fiber-Reinforced Polyethylene Terephthalate Glycol Parts Fabricated via Additive Manufacturing Under Dry and Lubricated Conditions Lubricants additive manufacturing CFRP flooded cooling machining NSGA-II PET-G |
| title | Multiple Regression Analysis and Non-Dominated Sorting Genetic Algorithm II Optimization of Machining Carbon-Fiber-Reinforced Polyethylene Terephthalate Glycol Parts Fabricated via Additive Manufacturing Under Dry and Lubricated Conditions |
| title_full | Multiple Regression Analysis and Non-Dominated Sorting Genetic Algorithm II Optimization of Machining Carbon-Fiber-Reinforced Polyethylene Terephthalate Glycol Parts Fabricated via Additive Manufacturing Under Dry and Lubricated Conditions |
| title_fullStr | Multiple Regression Analysis and Non-Dominated Sorting Genetic Algorithm II Optimization of Machining Carbon-Fiber-Reinforced Polyethylene Terephthalate Glycol Parts Fabricated via Additive Manufacturing Under Dry and Lubricated Conditions |
| title_full_unstemmed | Multiple Regression Analysis and Non-Dominated Sorting Genetic Algorithm II Optimization of Machining Carbon-Fiber-Reinforced Polyethylene Terephthalate Glycol Parts Fabricated via Additive Manufacturing Under Dry and Lubricated Conditions |
| title_short | Multiple Regression Analysis and Non-Dominated Sorting Genetic Algorithm II Optimization of Machining Carbon-Fiber-Reinforced Polyethylene Terephthalate Glycol Parts Fabricated via Additive Manufacturing Under Dry and Lubricated Conditions |
| title_sort | multiple regression analysis and non dominated sorting genetic algorithm ii optimization of machining carbon fiber reinforced polyethylene terephthalate glycol parts fabricated via additive manufacturing under dry and lubricated conditions |
| topic | additive manufacturing CFRP flooded cooling machining NSGA-II PET-G |
| url | https://www.mdpi.com/2075-4442/13/2/63 |
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