Innovative Applications of Machine Learning in Aerospace Design and Manufacturing

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Author(s): G. Boopathy (Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai, India), Balaji Ganesan (Hindustan Institute of Technology and Science, India), P. Sivaprakasam (Addis Ababa Science and Technology University, Ethiopia)and T. Kumaran (Acharya Institute of Technology, India)
Copyright: 2026
Pages: 42
Source title: Innovative Machine Learning Applications in the Aerospace Industry
Source Author(s)/Editor(s): Venkata Tulasiramu Ponnada (Collins Aerospace, USA)
DOI: 10.4018/979-8-3693-7525-9.ch001

Keywords: Aerospace Engineering / Engineering Science Reference / Knowledge Management and Library Science / Machine Learning

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Abstract

This chapter explores how machine learning (ML) is revolutionizing aerospace design and manufacturing, highlighting how it may improve operational efficiency, safety, and engineering precision. It describes how ML technologies enable smarter design, manufacturing optimization, and superior quality assurance in aerospace applications by discussing both historical and modern developments in the field. ML greatly enhances aerodynamic design, improves structural analysis, and speeds up computational fluid dynamics (CFD) simulations by using predictive algorithms and analyzing large datasets. It also explores the legal framework governing machine learning in the aerospace industry by tackling issues including data management, integration difficulties, and ethical concerns. This chapter provides a thorough review of current machine learning applications, new developments, and possible advancements in aerospace technology.

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