| With the development of the society,more and more modern factories adopt the automatic production line to get higher production efficiency.LCD(Liquid Crystal Display)is the most representative industry.Automated laminating production lines are widely used in these factories.So the research of this production line has important significance.In this thesis,the related research is based on the full lamination of the LCD industry,including coordination control optimization research of multi-station system.The full laminating production line usually consists of machining center and feeding mechanism.The goal of this system is to put the finished product on the conveyor belt so as to satisfy next procedures.Firstly,this thesis setups a Discrete-Time Markov Decision Process(DTMDP)optimization model,considering vacancies of the bank,products position information and the processing time of the current products in the machining center as the state and considering the unloading operation,waiting operation or the feeding operation as the optional action.Next,we use the theory optimization method and simulation optimization method to find the optimal strategy of DTMDP model,through policy iteration algorithm and the Q-learning algorithm based on Simulated Annealing.After that,we made a series of comparative experiments.Furthermore,we analyzed these simulation results and verified the effectiveness of our mechanism.In addition,in order to satisfy the need of practical production line better,we further research the coordination control optimization of multi-station production line on the basic of improved model and mechanism.In this thesis,we use a multi-agent Q-learning algorithm based on performance potential to simulate the model of product handling of full lamination production line with multi-station.The results prove that our cooperative control method can improve the balance of system's load rate and the activation of machining center. |
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