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Sustainable materials and manufacturing techniques in aviation

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Sustainable materials and manufacturing techniques in aviation/ edited by T. Hikmet Karakoc, Can Ozgur Colpan, Alper Dalkiran.
其他作者:	Karakoc, T. Hikmet.
出版者:	Cham :Springer Nature Switzerland : : 2024.,
面頁冊數:	vii, 126 p. :ill. (some col.), digital ;24 cm.
內容註:	Selection of Composite Materials for Aircraft -- Biocomposites as Aircraft Materials -- Life Cycle Assessment of the Use of Sustainable Materials in Aviation -- Energy Savings From New Materials and Processes in Aviation -- Green Manufacturing in Aviation -- Additive Manufacturing in Aviation -- Manufacturing Techniques in Electrified Aircraft -- Artificial Intelligence and Machine Learning in the Manufacturing of Aircraft.
Contained By:	Springer Nature eBook
標題:	Aircraft industry - Environmental aspects. -
電子資源:	https://doi.org/10.1007/978-3-031-62987-7
ISBN:	9783031629877

Sustainable materials and manufacturing techniques in aviation
Sustainable materials and manufacturing techniques in aviation[electronic resource] /edited by T. Hikmet Karakoc, Can Ozgur Colpan, Alper Dalkiran. - Cham :Springer Nature Switzerland :2024. - vii, 126 p. :ill. (some col.), digital ;24 cm. - Sustainable aviation,2730-7786. - Sustainable aviation..

Selection of Composite Materials for Aircraft -- Biocomposites as Aircraft Materials -- Life Cycle Assessment of the Use of Sustainable Materials in Aviation -- Energy Savings From New Materials and Processes in Aviation -- Green Manufacturing in Aviation -- Additive Manufacturing in Aviation -- Manufacturing Techniques in Electrified Aircraft -- Artificial Intelligence and Machine Learning in the Manufacturing of Aircraft.

This book offers comprehensive coverage of sustainable materials and manufacturing techniques in aviation that reduce fuel consumption, increase operational efficiency, and make more sustainable use of raw materials, energy, and water during manufacturing. Materials that enable the aircraft to be lightweight without compromising safety issues are covered. The sustainability aspects in selecting the materials and manufacturing techniques, as well as performance, cost, and environmental aspects are discussed. Artificial intelligence, machine learning, and digital twins in manufacturing are covered. Sustainable Materials and Manufacturing Techniques in Aviation will appeal to a broad readership in the aviation community, including students, engineers, scientists, and researchers, as a reference source for material science and modern production techniques. Offers guidance on the selection of sustainable materials for aircraft; Discusses additive manufacturing for aviation applications; Covers artificial intelligence and machine learning as well as digital twin in manufacturing.

ISBN: 9783031629877

Standard No.: 10.1007/978-3-031-62987-7doiSubjects--Topical Terms:

3594342
Aircraft industry
--Environmental aspects.

LC Class. No.: TL671.28

Dewey Class. No.: 623.746

Sustainable materials and manufacturing techniques in aviation
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520 $a This book offers comprehensive coverage of sustainable materials and manufacturing techniques in aviation that reduce fuel consumption, increase operational efficiency, and make more sustainable use of raw materials, energy, and water during manufacturing. Materials that enable the aircraft to be lightweight without compromising safety issues are covered. The sustainability aspects in selecting the materials and manufacturing techniques, as well as performance, cost, and environmental aspects are discussed. Artificial intelligence, machine learning, and digital twins in manufacturing are covered. Sustainable Materials and Manufacturing Techniques in Aviation will appeal to a broad readership in the aviation community, including students, engineers, scientists, and researchers, as a reference source for material science and modern production techniques. Offers guidance on the selection of sustainable materials for aircraft; Discusses additive manufacturing for aviation applications; Covers artificial intelligence and machine learning as well as digital twin in manufacturing.
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