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
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