TY - JOUR
T1 - Real-Time Data-Driven Out-of-Order Synchronization for Production and Intralogistics in Multiresource-Constrained Assembly Systems
AU - Li, Mingxing
AU - Li, Ming
AU - Guo, Daqiang
AU - Qu, Ting
AU - Huang, George Q.
N1 - Funding information:
This work was supported in part by the Several Funding Sources, including the National Key Research and Development Program of China under Grant 2021YFB3301701; in part by the National Natural Science Foundation of China under Grant 72231005; in part by the 2019 Guangdong Special Support Talent Program Innovation and Entrepreneurship Leading Team, China, under Grant 2019BT02S593; in part by the Departmental General Research Fund of PolyU under Grant P0045748; in part by the Projects of RIAM, PolyU under Grant P0046130; and in part by the RGC Collaborative Research Fund under Grant C7076-22G.
Publisher Copyright:
© 2013 IEEE.
PY - 2023/12/1
Y1 - 2023/12/1
N2 - This study aims to address a novel production and intralogistics synchronization (PiLSync) problem in multiresource-constrained assembly systems (MRCASs). PiLSync is highly complex due to the presence of multiple resources (operators, workstations, and materials) and the dynamic interactions between the resources and decisions. Moreover, various uncertainties, such as new/urgent job arrivals, uncertain operating times, equipment failures, and operator absences, further complicate this problem. Emerging Industry 4.0 technologies help capture and monitor the real-time PiL workflow, while existing methods are typically formulated to handle static or periodically updated inputs. Thus, it is difficult to explicitly incorporate real-time data into models, leading to a gap between production and intralogistic (PiL) decisions and actual executions under various uncertainties. In this article, out-of-order synchronization (OoOSync) is developed to facilitate flexible, resilient, and coordinated PiL operations in MRCASs. A sliding synchronization window is proposed as an effective decomposition tool to limit system complexity and localize demand uncertainty. Ticket validation governs interactions between resources and constraints under uncertainty. Finally, real-time data-driven synchronization mechanisms are developed for PiL decision/adjustment. The superiority of OoOSync is confirmed in computational experiments. This article is a pioneering study considering multiresource-constrained PiL operations under uncertainty. Additionally, this article offers a new perspective on using real-time data for decisions and operations subject to the dynamic interactions of resources.
AB - This study aims to address a novel production and intralogistics synchronization (PiLSync) problem in multiresource-constrained assembly systems (MRCASs). PiLSync is highly complex due to the presence of multiple resources (operators, workstations, and materials) and the dynamic interactions between the resources and decisions. Moreover, various uncertainties, such as new/urgent job arrivals, uncertain operating times, equipment failures, and operator absences, further complicate this problem. Emerging Industry 4.0 technologies help capture and monitor the real-time PiL workflow, while existing methods are typically formulated to handle static or periodically updated inputs. Thus, it is difficult to explicitly incorporate real-time data into models, leading to a gap between production and intralogistic (PiL) decisions and actual executions under various uncertainties. In this article, out-of-order synchronization (OoOSync) is developed to facilitate flexible, resilient, and coordinated PiL operations in MRCASs. A sliding synchronization window is proposed as an effective decomposition tool to limit system complexity and localize demand uncertainty. Ticket validation governs interactions between resources and constraints under uncertainty. Finally, real-time data-driven synchronization mechanisms are developed for PiL decision/adjustment. The superiority of OoOSync is confirmed in computational experiments. This article is a pioneering study considering multiresource-constrained PiL operations under uncertainty. Additionally, this article offers a new perspective on using real-time data for decisions and operations subject to the dynamic interactions of resources.
KW - Complexity and uncertainty
KW - data-driven decision
KW - multiresource-constrained assembly system (MRCAS)
KW - planning and scheduling
KW - production and intralogistics (PiLs)
UR - http://www.scopus.com/inward/record.url?scp=85168278062&partnerID=8YFLogxK
U2 - 10.1109/TSMC.2023.3298927
DO - 10.1109/TSMC.2023.3298927
M3 - Journal article
AN - SCOPUS:85168278062
SN - 2168-2216
VL - 53
SP - 7513
EP - 7525
JO - IEEE Transactions on Systems, Man, and Cybernetics: Systems
JF - IEEE Transactions on Systems, Man, and Cybernetics: Systems
IS - 12
ER -