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.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
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.
Mr. Kamal Singh was born in Ajmer, India in 1993. He graduated in Mechanical Engineering and later did his Master’s in Production Engineering in 2017 from Rajasthan Technical University, Kota. He has published research papers in journals and has also contributed around four papers in International conferences.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 132 pp. Englisch. N° de réf. du vendeur 9786137340134
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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 132 pp. Englisch. N° de réf. du vendeur 9786137340134
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Taschenbuch. Etat : Neu. Artificial Intelligence in Abrasive Jet Machining and CFD Simulation | Applications of AI in Machining Process | Kamal Singh (u. a.) | Taschenbuch | 132 S. | Englisch | 2018 | LAP LAMBERT Academic Publishing | EAN 9786137340134 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. N° de réf. du vendeur 111697638
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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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. N° de réf. du vendeur 9786137340134
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