Intelligent scheduling and monitoring for multi-product networked batch processes

Abstract

In this paper, we suggest a scheduling and on-line reactive rescheduling mechanism for networked batch processes that are the frequently appeared batch process type in chemical industry. In addition, an on-line process monitoring mechanism is also considered. We analyze the properties of the networked batch processes with suggestion of a rule-based completion time algorithm for a given processing sequence and production paths. We have studied on finding the initial optimized scheduling with almost satisfying the considered objective function by genetic algorithm. The used objective function in this problem is the minimization of the earliness and tardiness penalty cost function. The constructed reactive rescheduling mechanism is activated when the process deviate from the initial schedule. The deviation of the process is caught out by the monitoring system. The rescheduler modifies the processing times for the remaining batches after the deviation to minimize the effect of the deviation.