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A Systematic Literature Review on the Application of Automation in Logistics

Author

Listed:
  • Bárbara Ferreira

    (Higher Institute of Management and Administration of Santarém (ISLA), 2000-241 Santarém, Portugal)

  • João Reis

    (Industrial Engineering and Management, Faculty of Engineering, Lusófona University and RCM2+, 1749-024 Lisbon, Portugal)

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.

Suggested Citation

  • Bárbara Ferreira & João Reis, 2023. "A Systematic Literature Review on the Application of Automation in Logistics," Logistics, MDPI, vol. 7(4), pages 1-17, November.
    • Handle: RePEc:gam:jlogis:v:7:y:2023:i:4:p:80-:d:1273697
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    References listed on IDEAS

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    1. Anna Pernestål & Albin Engholm & Marie Bemler & Gyözö Gidofalvi, 2020. "How Will Digitalization Change Road Freight Transport? Scenarios Tested in Sweden," Sustainability, MDPI, vol. 13(1), pages 1-18, December.
    2. Jasim Alnahas, 2023. "Application of Process Mining in Logistic Processes of Manufacturing Organizations: A Systematic Review," Sustainability, MDPI, vol. 15(15), pages 1-12, July.
    Full references (including those not matched with items on IDEAS)

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