Towards a Framework for AI Applications in Intralogistics

被引:0
作者
Venkatadri, Uday [1 ]
Murrenhoff, Anike [2 ]
机构
[1] Dalhousie Univ, Dept Ind Engn, Halifax, NS B3H 4R2, Canada
[2] Fraunhofer Inst Mat Flow & Logist IML, Dortmund, Germany
来源
IFAC PAPERSONLINE | 2024年 / 58卷 / 19期
基金
加拿大自然科学与工程研究理事会;
关键词
Intralogistics; Artificial Intelligence; Logistics; Machine Learning; Simulation; Digital Twinning; Warehouse; 5.0; Framework; DESIGN;
D O I
10.1016/j.ifacol.2024.09.084
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The field of intralogistics is ideal for applying artificial intelligence (AI). However, there is currently no comprehensive framework for AI-enabled intralogistics that considers decision making layers. This paper aims to fill that gap by providing context, reviewing recent publications, and identifying key elements for framework development. It explores how AI can be used in intralogistics system design, planning and operations, at both physical and virtual levels. Our focus is on engineering pragmatic systems within the intralogistics domain, with a framework comprising human interaction, intelligent agents, and devices. The paper also addresses training data for AI-enabled intralogistics. Copyright (C) 2024 The Authors. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)
引用
收藏
页码:37 / 42
页数:6
相关论文
共 36 条
  • [1] Future of industry 5.0 in society: human-centric solutions, challenges and prospective research areas
    Adel, Amr
    [J]. JOURNAL OF CLOUD COMPUTING-ADVANCES SYSTEMS AND APPLICATIONS, 2022, 11 (01):
  • [2] Basrur C., 2021, P 20 INT C AUT AG MU, P1755
  • [3] A MARKOVIAN DECISION PROCESS
    BELLMAN, R
    [J]. JOURNAL OF MATHEMATICS AND MECHANICS, 1957, 6 (05): : 679 - 684
  • [4] An efficient and general approach for the joint order batching and picker routing problem
    Briant, Olivier
    Cambazard, Hadrien
    Cattaruzza, Diego
    Catusse, Nicolas
    Ladier, Anne-Laure
    Ogier, Maxime
    [J]. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2020, 285 (02) : 497 - 512
  • [5] Smart Interactive Technologies in the Human-Centric Factory 5.0: A Survey
    Brunetti, Davide
    Gena, Cristina
    Vernero, Fabiana
    [J]. APPLIED SCIENCES-BASEL, 2022, 12 (16):
  • [6] Artificial intelligence in supply chain and operations management: a multiple case study research
    Cannas, Violetta Giada
    Ciano, Maria Pia
    Saltalamacchia, Mattia
    Secchi, Raffaele
    [J]. INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2024, 62 (09) : 3333 - 3360
  • [7] Davies ER, 2018, COMPUTER VISION PRIN
  • [8] Dong Hao, 2020, Deep Reinforcement Learning: Fundamentals, Research and Applications, DOI 10.1007/978-981-15-4095-0
  • [9] ETP4HPC, 2019, A blueprint for the new strategic research agenda for high performance computing
  • [10] Fottner J., 2021, Logistics Research, V14