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Additive Manufacturing Process Planning

Chi Zhou

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Paperback / softback
06 June 2014
RRP: $123.50
$99.00
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Current market trends have resulted in the need for more efficient and robust manufacturing paradigm. Additive manufacturing (AM) can fabricate parts directly from digital models. Thus it can significantly shorten product development cycle while satisfying customized design requirements. However, compared with traditional manufacturing process, AM process also have disadvantages. Many researchers have extensively studied some critical processes and proposed novel solutions to improve the process. However, all these process planning methods are still mainly based on trial and error. This book, therefore, investigated the main principles and key techniques of AM process, formulated predicative mathematics models, proposed various optimization approaches and conducted simulation and physical experiments for verification. The proposed method can fundamentally and efficiently improve the AM process constrained by the current technique conditions. This research work should be useful to professionals in advanced manufacturing especially additive manufacturing fields, or anyone else who are interested in process modeling, optimization and simulation.

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RRP: $123.50
$99.00
Ships in 3-5 business days
Hurry up! Current stock:

Additive Manufacturing Process Planning

RRP: $123.50
$99.00

Description

Current market trends have resulted in the need for more efficient and robust manufacturing paradigm. Additive manufacturing (AM) can fabricate parts directly from digital models. Thus it can significantly shorten product development cycle while satisfying customized design requirements. However, compared with traditional manufacturing process, AM process also have disadvantages. Many researchers have extensively studied some critical processes and proposed novel solutions to improve the process. However, all these process planning methods are still mainly based on trial and error. This book, therefore, investigated the main principles and key techniques of AM process, formulated predicative mathematics models, proposed various optimization approaches and conducted simulation and physical experiments for verification. The proposed method can fundamentally and efficiently improve the AM process constrained by the current technique conditions. This research work should be useful to professionals in advanced manufacturing especially additive manufacturing fields, or anyone else who are interested in process modeling, optimization and simulation.

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