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Synchronization-State driven rescheduling for multi-resource constrained production-logistics in cyber-physical modular integrated construction
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DOI：10.1007/s10845-026-02871-x.png)
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Abstract
En 中文
In Modular Integrated Construction (MiC), the module manufacturing is a complex process that involves integrated management of production and internal logistics with multiple resources such as human labor, assembly stations, equipment, and materials. And its complexity is further amplified by the presence of multi-source uncertainties. It is defined as a novel Multi-Resource Constrained Production-Logistics Synchronization (MRC-PLSync) problem. This paper proposes a Synchronization-State(Sync-State) driven rescheduling mechanism to address MRC-PLSync problem under uncertainty. Firstly, a stochastic programming model with Monte Carlo simulation is applied to handle uncertain processing time. Considering other uncertain events such as machine breakdowns and urgent orders, the Sync-State is then defined to evaluate real-time system state from two-dimension and four-perspective: “Material supply-production sync” and “production-site delivery sync” dimensions with “Scheduled State-Current State-Future State-Ideal State” perspectives. Based on the real-time Sync-State monitoring and analytics, the mechanism is able to capture the most suitable timing for rescheduling to balance immediate needs with long-term goals in dynamic environments. A case study highlights the superiority of the proposed strategy in terms of synchronization quality and improved system stability. This study is among the first attempt to discuss coordinated production-logistics management in MiC manufacturing under multi-resource constraints in dynamic environments. It provides a new perspective on MiC management decision-making with real-time system state analytics, adding to the growing body of research on smart decisions for Industry 4.0 construction.
Keywords:
Modular integrated construction
Manufacturing planning and control
Production-logistics synchronization
Uncertainty
Real time data-driven decision
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3.5K
Citations:
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