Imani farhad (10 resultados)

Condición: New.

Paperback. Condición: Brand New. 400 pages. 9.00x6.00x0.94 inches. In Stock.

Condición: As New. Unread book in perfect condition.

Paperback. Condición: new. Paperback. Machine Learning for Powder-based Metal Additive Manufacturing outlines machine learning (ML) methods for additive manufacturing (AM) of metals that will improve product quality, optimize manufacturing processes, and reduce costs. The book combines ML and AM methods to develop intelligent models that train AM techniques in pre-processing, process optimization, and post-processing for optimized microstructure, tensile and fatigue properties, and biocompatibility for various applications. The book covers ML for design in AM, ML for materials development and intelligent monitoring in metal AM, both geometrical deviation and physics informed machine learning modeling, as well as data-driven cost estimation by ML.In addition, optimization for slicing and orientation, ML to create models of materials for AM processes, ML prediction for better mechanical and microstructure prediction, and feature extraction by sensing data are all covered, and each chapter includes a case study. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Condición: New. Covers machine learning (ML) methods for additive manufacturing (AM) of metals that will improve product quality, optimize manufacturing processes, and reduce costsCombines ML and AM methods to develop intelligent models that train AM techn.

Condición: New. 2024. 1st Edition. paperback. . . . . .

Paperback. Condición: Brand New. 400 pages. 9.00x6.00x0.94 inches. In Stock.

Condición: New. 2024. 1st Edition. paperback. . . . . . Books ship from the US and Ireland.

Paperback. Condición: new. Paperback. Machine Learning for Powder-based Metal Additive Manufacturing outlines machine learning (ML) methods for additive manufacturing (AM) of metals that will improve product quality, optimize manufacturing processes, and reduce costs. The book combines ML and AM methods to develop intelligent models that train AM techniques in pre-processing, process optimization, and post-processing for optimized microstructure, tensile and fatigue properties, and biocompatibility for various applications. The book covers ML for design in AM, ML for materials development and intelligent monitoring in metal AM, both geometrical deviation and physics informed machine learning modeling, as well as data-driven cost estimation by ML.In addition, optimization for slicing and orientation, ML to create models of materials for AM processes, ML prediction for better mechanical and microstructure prediction, and feature extraction by sensing data are all covered, and each chapter includes a case study. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

Condición: new. Questo è un articolo print on demand.