Research On The Simulation And Optimization Of Repairable Spare Parts Supply Support Policy For Complex Equipment

Equipment spare parts support supply faces the challenges from complexity of system structure and dynamic uncertainty. In order to cope with the challenges, some measures should be taken which include improving the efficiency of security effectively and reducing the overall support cost. Consequently, the optimization of spare parts support is of great importance to equipment support. This paper propose that dynamic regulations within optimization and control of spare parts supply support management based on system dynamics and chaotic time series theory which will have impact on the equipment life cycle support. The research was developed from the following three aspects:Explore the equipment spare parts demand prediction method to realize the accurate support for spare parts; Explore dynamic mechanism of equipment spare parts support system, which will benefit to the support strategy optimization; Spare parts supply support risk dynamic assessment and management, which could reduce the risk in the process of spare parts supply support. The main research contents are described as below:(l)Spare parts demand prediction system dynamics model was established from the optical angle of system science. First of all, analysis the demand of spare parts of multiple factors and the control feedback relationship between them; Then, through the simulation results of spare parts demand prediction model to explore the cause of the dynamics and complexity changes within the system. Finally, the model was optimized and considered logistics delay and information delay factor, with different strategy to test the model, finally get the dynamics of a cycle spare parts demand prediction results. The experimental results showed that the error within the acceptable range, which could provide a reference for spare parts demand prediction. On the basis of above study, consider the chaotic characteristics of the historical data, the method of chaotic time series prediction of spare parts demand was proposed, by using the theory of chaotic time series, then realized phase space reconstruction and made improvement of the model, finally got precisely results of spare parts demand prediction.(2)Spare parts supply support system dynamics model was established based on the internal dynamic mechanism. First, as for single-echelon spare parts supply support system was regarded as the research object, analyzed the causal relationship and the control feedback among influencing factors within the system, single-echelon spare parts supply support dynamics model is established, explore spare parts logistics regulations and system dynamic mechanism, then analyze the behavior of the complexity and dynamic coordination mechanism, moreover determined the scope of the key parameters which influenced the stability of the system. Reasonable spare parts supply and system stable state strategy were proposed; And regarded multi-echelon spare parts supply support system as research object, the multi-echelon support network system dynamics model was established. To explore the complex of structure complexity that brings to the system and feedback causal relationships between crossover mechanism, analyzed the connotation of the information feedback control, and mechanism of the dynamic characteristics of system operation. The experimental results showed that the optimized strategy could reduce cost, provide timely and accurate service, and simultaneously increase the efficiency of the security in an all-round way.(3)Considering the uncertain factors within the complicated spare parts supply network that complexity and high degrees, nonlinear characteristics could bring the system risk. The spare parts supply support will influence enterprise operation and bring losses, while quantitative evaluation could weaken the influence. The whole process of spare parts support was taken into consideration that each link may be involved in management and information risk factors were classified. Spare parts supply support risk assessment model was established and dynamically assessed and forecast the process of spare parts supply support, and then compared the simulation results of different risk factors that influenced system, the impact on the risk degree was adjusted. The final spare parts support strategies and optimization scheme were proposed after the experiment. Experimental results show that the optimized strategy can reduce the potential risk, avoid economic losses for the enterprise.