Research On Parallel Simulation And Optimization Of Manufacturing System Under The Surge Of Unconventional Emergency Demand

Unconventional emergencies occur frequently,which constantly impact the demand end of manufacturing system,resulting in more and more uncertain demand of manufacturing system.In particular,the surge in demand caused by unconventional emergencies has the characteristics of suddenness,urgency,and complexity.The production capacity of the manufacturing system under normal conditions is not enough to meet the emergency supplies demand in this scenario.Failure to collect and integrate information on emergency supplies within a short period of time and respond to them in a timely manner will delay the disaster relief process.Therefore,how to respond to the surging manufacturing demand efficiently and quickly according to the evolution of unconventional events is the key to emergency rescue.To solve this problem,This paper takes the emergency materials manufacturing demand response in the context of COVID 19 outbreak at the end of 2019 as the background,combined with the discrete event system simulation,parallel control management theory and method ofqueuing theory and related theory,puts forward to“demand-task-response-plan-optimization” as the main line of the parallel simulation and optimization framework,construct the abstract model of the surge in demand for emergency response.An artificial scenario simulation model is established based on real scenarios,and the evolution of material requirements for real scenarios is predicted through multi-stage parallel simulation experiments.The simulation results are analyzed and optimization strategies are proposed.From the principle level,the discrete emergency response process abstract modeling,computational experiments and analysis optimization,and parallel management and control methods are provided to support the simulation decision-making of demand surge problems.Then take the surge of manufacturing demand for specific medical protective equipment as an example to predict the law of material demand in real public health emergencies.Furthermore,the production line optimization strategy under the situation of demand surge is proposed to verify the feasibility and operability of this method.The research results show that through the multi-stage parallel evolution and control of the simulation models of real and artificial scenarios,it is possible to quickly and accurately predict the change law of emergency materials demand in the“ future period” under unconventional emergencies;At the same time,the bottleneck of theproduction line of the manufacturing system is determined by the queuing network model,and it is optimized and improved.Make the system operational capability of the production line meet the manufacturing demand in the case of emergency material demand surge.The above methods not only provide scientific theoretical basis and powerful method support for timely response and application practice of demand surge,but also provide decision reference for emergency response and system optimization of demand surge in other fields.