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Presently Machining condition monitoring is becoming more important in the manufacturing industry to improve machine reliability and reducing the conceivable production losses. Therefore, it is essential to make a system that can adapt new data as available without affecting the performance of previously learned data. This research has considered new data monitoring or prediction techniques for abrasive jet machining process using Artificial Intelligence approaches. The Research work has been conducted in three section. Jet Pressure, impact angle, nozzle diameter are considered as an input parameter whereas material removal rate and sphericity constant (Sc) is the response parameters. After conducting the experiments Fuzzy logic is developed for this machining system. In second section result obtained by the Taguchi OA method is used for the implementation of a neural network to predict the response behavior. Finally, erosion model of CFD is used to simulate the shape profile of crater at different impact angle and correlate with the experimentally cutting profile. The last chapter initially emphasizes the fabrication of 3D cutting profile by using CNC programming.
| Autorius: | Kamal Singh, Vikas Sharma, Manish Dadhich, |
| Leidėjas: | LAP LAMBERT Academic Publishing |
| Išleidimo metai: | 2018 |
| Knygos puslapių skaičius: | 132 |
| ISBN-10: | 6137340139 |
| ISBN-13: | 9786137340134 |
| Formatas: | 220 x 150 x 8 mm. Knyga minkštu viršeliu |
| Kalba: | Anglų |
Parašykite atsiliepimą apie „Artificial Intelligence in Abrasive Jet Machining and CFD Simulation: Applications of AI in Machining Process“
