Research On Dynamic Scheduling Of Flexible Manufacturing Shop Floor Based On The Internet Of Manufacturing Things

The shop floor is usually the smallest materialized unit to study the allocation of manufacturing resources,production optimization scheduling and manufacturing system management and control.Combined with Internet of manufacturing things(IoMT)and multi-agent technology,the interaction among equipments can be realized without human intervention,so that the equipment in the whole shop floor system has the ability of self perception,self decision-making,self execution and collaborative execution of complex tasks.Route flexibility is an effective way to solve the problem of changeable requirements of shop floor manufacturing and unstable production execution.Based on the idea of nonlinear integrated process planning and shop scheduling,a hierarchical multi-objective optimization method is proposed.Dijkstra-based process route planning method is proposed to solve the optimization problem of process route,which can realize the automatic optimization of process route.In the stage of machine allocation and process scheduling,a shop scheduling algorithm PN-ACO and its heuristic function are proposed based on Petri net and Ant Colony Optimization(ACO)algorithm,which can realize the modeling and heuristic function of flexible process route.In order to test the performance of PN-ACO algorithm in solving shop floor scheduling problems,standard examples are tested.FJSP standard example is selected for comparative test.The experimental results show the superiority of the PN-ACO algorithm in solving FJSP problems,and also prove the effectiveness of the proposed heuristic function?_gh and the efficiency of the search mechanism.An example of security parts manufacturing system scheduling verifies the feasibility and efficiency of the proposed flexible process route shop scheduling method.Taking the monthly production scheduling optimization of a train axle processing shop floor as an example,the results show that the total processing time is 26.3 days,which is 12.3%shorter than the original plan,thus proving the engineering application ability of PN-ACO algorithm.Robustness and stability are two important indicators of dynamic shop floor rescheduling under complete information disturbance.It is usually difficult to determine the importance of the two indicators.At present,the weight method is often used,and a large number of weight optimization experiments are needed to solve the problem.A dynamic scheduling method based on non-cooperative dynamic game is proposed to solve the dynamic scheduling problem which is difficult to determine the weight of multi-objective.A rolling window rescheduling mechanism is proposed to solve the problem of game method failure under multiple game stage and frequent rescheduling.From the comparative experiments,it can be concluded that the rescheduling results obtained by HGW have no significant increase compared with the initial scheduling results.Index RD,the relative error of plan is 11.33%and index MID,the point moment of that is the 13.74,which are both more efficient than the comparison method.It can be proved that the HGW algorithm proposed by the paper is efficient in solving dynamic shop floor scheduling problems.Aiming at the disturbance recovery problem under incomplete information disturbance,i.e.the disturbance occurring time,the disturbance ending time and the disturbance frequency is uncertain,the timed automata is used to monitor disturbance events in real time,and a shop floor scheduling method based on virtual queue control is proposed.At the decision time point,the deviation caused by abnormal events to the shop floor is calculated and triggered if the threshold is reached.Adjusting the virtual queue ensures that the total running time of the system will not deteriorate further,thus realizing the adaptive scheduling of the shop floor under incomplete disturbance information.At the same time,it is also a concrete embodiment of multi-agent-based job shop scheduling in manufacturing system driven by IoMT.Through an engineering example,it can be seen that the adaptive scheduling method simplifies the rule system in the dynamic scheduling control of the shop floor and makes the scheduling control of the shop floor easier to realize.The development of prototype system standardizes the business process of IoMT,and provides a more realistic design parameter assistance for more complex intelligent manufacturing system design.