Architectural Strategies for Integrating Material Requirements Planning (MRP) with Real-Time Supply Chain Data
DOI:
https://doi.org/10.22399/ijcesen.5547Keywords:
Material requirements planning, real-time supply chain data, digital twin architecture, event-driven replanning, supply chain visibilityAbstract
Material requirements planning is still within the planning backbone of most manufacturing supply chains, but the conventional basing on periodic, transaction-based data is becoming more out-of-step with the current event-driven digital world. This review discusses architectural approaches to connecting MRP to real-time supply chain information, with a focus on how technical conditions can be fulfilled to deem enhanced visibility as an intervention of disciplined planning instead of instability. A search of peer-reviewed journal articles and academic books was performed and sorted into a core corpus of twenty-four articles with a clear architectural implication published between 1997 and 2025 and coded according to the architecture class, latency, extent of planning, mode of validation, richness of real-time and depth of planning-closure. The evidence presented shows that the notion of ERP-oriented integration of transactions to analytics applications, cyber-physical system, digital twins, and reconfigurable network designs has changed significantly. This has however not kept up with the increase in the richness of data as compared to the actual planning closure. The studies were in general more observable and a relatively few studies had good mechanisms of converting heterogeneous events into uniform planning states and directed replanning behaviors. Event-driven architectures were related to increased scores in planning-closure when they were supported by both state estimation and semantic alignment and intervention gating. The old issue of MRP nervousness hence becomes very pertinent in the digital circumstances. Its further evolution is likely to be based on the layered architectures which will incorporate master-data discipline, semantic interoperability, probabilistic state estimation, and event-selective replanning. Additional empirical validation, benchmark data and hybrid operations-research and machine-learning designs are necessary. The review argues that progress in real-time MRP integration will depend on treating it not merely as a data-availability problem, but as an architectural control problem.
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