TY - JOUR
T1 - Industrial internet of things-driven storage location assignment and order picking in a resource synchronization and sharing-based robotic mobile fulfillment system
AU - Keung, K. L.
AU - Lee, C. K.M.
AU - Ji, P.
N1 - Funding Information:
This work was supported by the Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong (RK2F). Our gratitude is also extended to the Research Committee and the Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong and The Innovation and Technology Commission, The Government of the Hong Kong SAR, Hong Kong , for support of this project (PRP/002/19FX/K.ZM31)
Publisher Copyright:
© 2022 Elsevier Ltd
PY - 2022/4
Y1 - 2022/4
N2 - In this paper, we intend to address the value creation of utilizing the Industrial Internet of Things (IIoT)-driven resource synchronization and sharing-based robotic mobile fulfillment system (RMFS) to enhance the overall operational effectiveness and efficiencies during information transfer and synchronization of resources. With the advent of IIoT, a graph theory-based heuristic under the multi-deep RMFS is used for computing the shortest path. A-star, Dijkstra, and genetic heuristic algorithms are applied for comparison. A simulation with a consideration of the different types of collisions is conducted for different algorithms. By providing a new three-tier IIoT architecture which includes the suppliers, RMFS, and the disposal center, a model is developed with different storage location assignment rules and strategies under the particular parties to minimize the operation costs. IIoT enables resource synchronization and information sharing, and the path will be generated under different order scenarios with different algorithms. The results show that different storage assignment rules and strategies may lead to 30% cost differences compared to the company's current practice with random storage.
AB - In this paper, we intend to address the value creation of utilizing the Industrial Internet of Things (IIoT)-driven resource synchronization and sharing-based robotic mobile fulfillment system (RMFS) to enhance the overall operational effectiveness and efficiencies during information transfer and synchronization of resources. With the advent of IIoT, a graph theory-based heuristic under the multi-deep RMFS is used for computing the shortest path. A-star, Dijkstra, and genetic heuristic algorithms are applied for comparison. A simulation with a consideration of the different types of collisions is conducted for different algorithms. By providing a new three-tier IIoT architecture which includes the suppliers, RMFS, and the disposal center, a model is developed with different storage location assignment rules and strategies under the particular parties to minimize the operation costs. IIoT enables resource synchronization and information sharing, and the path will be generated under different order scenarios with different algorithms. The results show that different storage assignment rules and strategies may lead to 30% cost differences compared to the company's current practice with random storage.
KW - Industrial internet of things
KW - Internet of things
KW - Robotic mobile fulfillment system
KW - Storage location assignment
KW - Warehouse management
UR - http://www.scopus.com/inward/record.url?scp=85123849519&partnerID=8YFLogxK
U2 - 10.1016/j.aei.2022.101540
DO - 10.1016/j.aei.2022.101540
M3 - Journal article
AN - SCOPUS:85123849519
SN - 1474-0346
VL - 52
JO - Advanced Engineering Informatics
JF - Advanced Engineering Informatics
M1 - 101540
ER -