A Systematic Literature Review on the Application of Automation in Logistics

IF 3.6 Q2 MANAGEMENT
Bárbara Ferreira, João Reis
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引用次数: 0

Abstract

Background: in recent years, automation has emerged as a hot topic, showcasing its capacity to perform tasks independently, without constant supervision. While automation has witnessed substantial growth in various sectors like engineering and medicine, the logistics industry has yet to witness an equivalent surge in research and implementation. Therefore, it becomes imperative to explore the application of automation in logistics. Methods: this article aims to provide a systematic analysis of the scientific literature concerning artificial intelligence (AI) and automation in logistics, laying the groundwork for robust and relevant advancements in the field. Results: the foundation of automation lies in cutting-edge technologies such as AI, machine learning, and deep learning, enabling self-problem resolution and autonomous task execution, reducing the reliance on human labor. Consequently, the implementation of smart logistics through automation has the potential to enhance competitiveness and minimize the margin of error. The impact of AI and robot-driven logistics on automation in logistics is profound. Through collaborative efforts in human–robot integration (HRI), there emerges an opportunity to develop social service robots that coexist harmoniously with humans. This integration can lead to a revolutionary transformation in logistics operations. By exploring the scientific literature on AI and automation in logistics, this article seeks to unravel critical insights into the practical application of automation, thus bridging the existing research gap in the logistics industry. Conclusions: the findings underscore the impact of artificial intelligence and robot-driven logistics on improving operational efficiency, reducing errors, and enhancing competitiveness. The research also provided valuable insights into the applications of various automation techniques, including machine learning and deep learning, in the logistics domain. Hence, the study’s insights can guide practitioners and decision makers in implementing effective automation strategies, thereby improving overall performance and adaptability in the dynamic logistics landscape. Understanding these foundations can pave the way for a future where automation and human expertise work hand in hand to drive logistics toward unparalleled efficiency and success.
自动化在物流中的应用系统文献综述
背景:近年来,自动化已经成为一个热门话题,展示了它在没有持续监督的情况下独立执行任务的能力。虽然自动化在工程和医学等各个领域都取得了长足的发展,但物流行业的研究和实施尚未出现相应的激增。因此,探索自动化在物流中的应用已势在必行。方法:本文旨在对物流中人工智能(AI)和自动化的科学文献进行系统分析,为该领域的强大和相关进展奠定基础。结果:自动化的基础在于人工智能、机器学习、深度学习等尖端技术,能够自我解决问题,自主执行任务,减少对人力的依赖。因此,通过自动化实施智能物流有可能提高竞争力并最大限度地减少误差。人工智能和机器人驱动的物流对物流自动化的影响是深远的。通过人-机器人集成(HRI)的协同努力,出现了开发与人类和谐共处的社会服务机器人的机会。这种整合可以导致物流业务的革命性转变。通过探索人工智能和物流自动化的科学文献,本文试图揭示自动化实际应用的关键见解,从而弥合物流行业现有的研究差距。结论:研究结果强调了人工智能和机器人驱动的物流对提高运营效率、减少错误和增强竞争力的影响。该研究还为各种自动化技术在物流领域的应用提供了有价值的见解,包括机器学习和深度学习。因此,该研究的见解可以指导从业者和决策者实施有效的自动化策略,从而提高动态物流领域的整体绩效和适应性。了解这些基础可以为自动化和人类专业知识携手合作的未来铺平道路,推动物流走向无与伦比的效率和成功。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Logistics-Basel
Logistics-Basel Multiple-
CiteScore
6.60
自引率
0.00%
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0
审稿时长
11 weeks
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