Research On Variable Weight Dynamic Rescheduling Theory Of Job Shop Driven By Real-Time Status

The uncertainties caused by complex workshop production environment and kinds of interruptions during the production process,and the research methods of dynamic scheduling are analyzed.According to Job shop production uncertain environment,the theoretical framework of variable weight dynamic rescheduling of Job shop driven by Real-Time Status is set up from the point of view of system and integration.The unexpected instances in production is classified and digital described,the results of the unexpected instances is analyzed to coupling with real-time condition and scheduling system.The current rescheduling driven mechanism lacks quantitative description,so it is difficult to estimate the impact of the frequency of rescheduling to system's gain and loss.In the view of this problem, the rescheduling driven mechanism is set up based on profit and loss model.After comprising the occurrence of disturbance with the original pre-scheduling program and rescheduling program,the loss function and the value of pre-scheduling implementation loss is used to determine whether there is a need to start rescheduling,so that to filter out unnecessary rescheduling and to reduce the system oscillations and time-delay problem.In view of that Job Shop rescheduling does not consider the problems coursed by error time processing accumulating of parts,the rescheduling driven mechanism is set up based on time threshold model, and the Gantt chart is monitored and continuously updated,to reduce the impact of hidden disturbance on production.The variable weight method of rescheduling based on the work piece selection rules is discussed.On one hand,dynamic weight is given to each work piece when it enter the optimize aggregate,to meet delivery requirements.On the other hand,each target's dynamic weight to the optimization goal is given to reduce the problem of the production process deviating from work goal.Strategy library is set up based on feature mapping to find the best scheduling scheme quickly.