人工智能对航空业的影响:全行业审查

IF 3.7 3区 管理学 Q2 BUSINESS
Amina Zaoui , Dieudonné Tchuente , Samuel Fosso Wamba , Bernard Kamsu-Foguem
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引用次数: 0

摘要

令人奇怪的是,关于人工智能(AI)及其对航空业影响的科学文献却寥寥无几。然而,航空企业却发表了许多关于人工智能技术应用的通讯和报告。本文采用三步顺序法对航空业的人工智能进行了全行业审查:(i) 审查人工智能及其概念,以定义和开发概念图;(ii) 从使用人工智能技术的航空企业(如空中客车公司、波音公司、法国航空公司、赛峰集团、易捷航空公司、达索航空公司、Altair 公司)中选择 100 个使用案例;(iii) 使用概念图中定义的主题对使用案例进行分析。主要结果表明,航空领域的实体对整合人工智能技术的兴趣日益浓厚。此外,使用案例的结果表明,最常见的技术是大数据分析、自主智能系统、预测分析、机器学习和机器人技术。另一项发现与促使企业将人工智能技术融入其工业和运营流程的若干好处有关。最常见的好处包括客户满意度、节省时间、安全和安保、降低成本、更好地决策、解决复杂问题以及确保优化和效率。使用这些人工智能技术似乎还对公司的业绩产生了积极影响。这些影响涉及所有运营部门,包括市场营销(这些技术有助于满足客户需求)、工业和运营领域(提供优质产品)以及生产力和经济效益优化(提高效率)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Impact of artificial intelligence on aeronautics: An industry-wide review

Curiously, there are few contributions in the scientific literature on the subject of artificial intelligence (AI) and its impact on aeronautics. However, many communications and reports have been published by aeronautic companies about their applications of AI technologies. This article makes an industry-wide review of AI in aeronautics using a three-step sequential approach: (i) a review of AI and its concepts to define and develop a conceptual map; (ii) a selection of 100 use cases from aeronautics companies that use AI technologies (e.g., Airbus, Boeing, Air France, Safran, EasyJet, Dassault Aviation, Altair); and (iii) an analysis of the use cases using the topics defined in the conceptual map. The main results describe a rising interest in the integration of AI technologies by entities in the aeronautic sector. Moreover, the results from the use cases show that the most recurrent technologies are big data analytics, autonomous intelligent systems, predictive analytics, machine learning, and robotics. Another finding is related to the several benefits that motivate companies to integrate AI technologies into their industrial and operational processes. The most frequent benefits include customer satisfaction, saving time, safety and security, cost reduction, better decision making, solving complex problems, and ensuring optimisation and efficiency. It also appears that the performance of companies is positively impacted by using these AI technologies. Such impacts span all operational departments including marketing, where these technologies help satisfy customer needs; the industrial and operational area, which is provided with quality products; and where productivity and economic performance are optimised for more efficiency.

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来源期刊
CiteScore
8.00
自引率
6.20%
发文量
29
审稿时长
>12 weeks
期刊介绍: The Journal of Engineering and Technology Management (JET-M) is an international scholarly refereed research journal which aims to promote the theory and practice of technology, innovation, and engineering management. The journal links engineering, science, and management disciplines. It addresses the issues involved in the planning, development, and implementation of technological capabilities to shape and accomplish the strategic and operational objectives of an organization. It covers not only R&D management, but also the entire spectrum of managerial concerns in technology-based organizations. This includes issues relating to new product development, human resource management, innovation process management, project management, technological fusion, marketing, technological forecasting and strategic planning. The journal provides an interface between technology and other corporate functions, such as R&D, marketing, manufacturing and administration. Its ultimate goal is to make a profound contribution to theory development, research and practice by serving as a leading forum for the publication of scholarly research on all aspects of technology, innovation, and engineering management.
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