A1 Journal article (refereed), original research (Journal article, original research)

A Dynamic Route-Planning System Based on Industry 4.0 Technology


Open Access publication


Publication Details

Authors: Nguyen Duc Duy, Tran Huu Thong, Nananukul Narameth

Publisher: MDPI

Publication year: 2020

Language: English

Related journal or series: Algorithms

Volume number: 13

Issue number: 12

eISSN: 1999-4893

JUFO level of this publication: 1

Digital Object Identifier (DOI): http://dx.doi.org/10.3390/a13120308

Open Access: Open Access publication


Abstract

Due to the availability of Industry 4.0 technology, the application of big data analytics to automated systems is possible. The distribution of products between warehouses or within a warehouse is an area that can benefit from automation based on Industry 4.0 technology. In this paper, the focus was on developing a dynamic route-planning system for automated guided vehicles within a warehouse. A dynamic routing problem with real-time obstacles was considered in this research. A key problem in this research area is the lack of a real-time route-planning algorithm that is suitable for the implementation on automated guided vehicles with limited computing resources. An optimization model, as well as machine learning methodologies for determining an operational route for the problem, is proposed. An internal layout of the warehouse of a large consumer product distributor was used to test the performance of the methodologies. A simulation environment based on Gazebo was developed and used for testing the implementation of the route-planning system. Computational results show that the proposed machine learning methodologies were able to generate routes with testing accuracy of up to 98% for a practical internal layout of a warehouse with 18 storage racks and 67 path segments. Managerial insights into how the machine learning configuration affects the prediction accuracy are also provided.


Last updated on 2021-03-12 at 08:48