Detection of anomalies in a transport system using automation agents with a reflective world model

Manufacturing systems need to become more flexible and agile in order to address permanently changing requirements. Agent-based manufacturing control systems are envisioned as a relevant solution. However, designing and deploying such systems is complex, and raises some concerns regarding safety, robustness and emergence of unforeseen behaviors. To address these concerns, we propose an approach in which automation agents are created by extending existing hardware and real-time control software with advanced capabilities for cooperation and run-time diagnosis. The main feature of an automation agent is the reflective world model - a symbolic model of the agent's world, including the agent itself. In this paper, we present the application of a reflective world model for automation agents to detect some anomalies in a pallet transport system. This work shows the suitability of the proposed approach for designing advanced run-time diagnosis capabilities, while preserving existing hardware and control software.