Automatic Sorting Machine Of Cigarettes Control Strategy Optimization And Simulation

Nowadays automated picking systems of cigarette, are more and more extensive in cigarette distribution center. Most of the automated picking systems are composed by some single picking machines. The difference of single picking machines' picking time in the picking process, weakened the working performance of the picking system. So, there is a urgent demand to investigate the control policy of automated picking system.Two control policies are designed in the paper, the model of check the present belt position, and the model of allocate the belt positions in advance. The principle of check the present belt position model is, to check whether the belt position to pick the cigarette, is occupied by other cigarettes. Can pick cigarette if the position is not be occupied, and the state of this position changed to be occupied. If the position is be occupied, then this cigarette can not be picked. The principle of the model of allocate the belt positions in advance is, distribute the positions on the belt to single picking machines, and record the picking time when the single picking machine will pick a cigarette.As the picking process is in succession, order by order, the paper analyses the picking policy of sequential order picking. After optimizing, the belt's position of cigarette can be calculated, so next order can be picked after a few distance from previous order, not need to wait until all of the cigarettes of the previous order move away from the picking machine area. So the interval between two orders is be shortened, the efficiency of picking cigarettes can be improved.The paper has designed a simulation program, for simulate the picking condition of different picking policies. The main actions of simulation are cigarettes fall on the belt from picking machine, and cigarettes move forwards in the belt. Picking condition of different picking models can be seen intuitively through simulation program. This program still can offer picking information of simulation, such as picking time, efficiency, etc. The data of order can be input artificially, or read from database. The program can simulate the real picking...