Predictive transportation control for high throughput and short turnaround time

In factory automation (FA) and laboratory automation (LA), an automation system alternates between transporting work-piece objects to an area that is appropriate for the purpose and then processing them. This kind of automation system needs high scalability. Therefore, the automation system is made up of various combinations of autonomous modules. That is, the automation system is a kind of system of systems (SoS). In the automation system, we often require high throughput (TP) and short turnaround time (TAT) for high priority objects. However, there is a tradeoff between these capabilities. In this research, we propose a queue-based model for defining congestion of the automation system. Then, we describe the difficulty in achieving high TP and short TAT simultaneously. Then, we propose a novel control method that is based on future congestion. A part of the effectiveness has been evaluated by simulations.