SIMULATION-DRIVEN OPTIMIZATION FOR PRODUCTION PLANNING IN EQUIPMENT MANUFACTURING.

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Bibliographic Details
Title:	SIMULATION-DRIVEN OPTIMIZATION FOR PRODUCTION PLANNING IN EQUIPMENT MANUFACTURING.
Authors:	Chen, N.¹, Li, H. X.² lihanxiong@xauat.edu.cn, Ma, J.¹, Lv, N.¹
Source:	International Journal of Simulation Modelling (IJSIMM). Jun2026, Vol. 25 Issue 2, p318-329. 12p.
Subjects:	Production planning, Discrete event simulation, Scheduling, Manufacturing industry equipment, Dynamic simulation, Predictive control systems, Production scheduling
Abstract:	Equipment manufacturing is characterized by multi-variety, small-batch production and frequent dynamic disturbances. Conventional production simulation is mainly used for offline validation and is rarely integrated with production planning, which limits its applicability in dynamic environments. This study develops a simulation-driven closed-loop rolling optimization framework based on a multi-agent discrete event simulation model. The framework integrates rolling horizon control, real-time interaction between simulation and optimization, and disturbance-triggered rescheduling. A coupling mechanism between the simulation clock and optimization process is established to support continuous plan adjustment. Simulation experiments in a real manufacturing workshop show that the proposed approach reduces order tardiness and makespan while maintaining stable equipment utilization under dynamic disturbances, compared with offline simulation-based optimization and conventional scheduling methods. The results indicate that production simulation can be integrated into planning decisions and used for dynamic adjustment in complex manufacturing environments. [ABSTRACT FROM AUTHOR]
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Database:	Engineering Source

Description
Abstract:	Equipment manufacturing is characterized by multi-variety, small-batch production and frequent dynamic disturbances. Conventional production simulation is mainly used for offline validation and is rarely integrated with production planning, which limits its applicability in dynamic environments. This study develops a simulation-driven closed-loop rolling optimization framework based on a multi-agent discrete event simulation model. The framework integrates rolling horizon control, real-time interaction between simulation and optimization, and disturbance-triggered rescheduling. A coupling mechanism between the simulation clock and optimization process is established to support continuous plan adjustment. Simulation experiments in a real manufacturing workshop show that the proposed approach reduces order tardiness and makespan while maintaining stable equipment utilization under dynamic disturbances, compared with offline simulation-based optimization and conventional scheduling methods. The results indicate that production simulation can be integrated into planning decisions and used for dynamic adjustment in complex manufacturing environments. [ABSTRACT FROM AUTHOR]
ISSN:	17264529
DOI:	10.2507/IJSIMM25-2-CO7