Causal modeling for supervision

Abstract

Today, process control and monitoring are evolving to include plant safety and availability management, online diagnosis and maintenance policy. Human operators are at the highest hierarchical level in the organization of the control system. Supervision aims are to assist control operators in their decision-making tasks, to help them understand and identify operating situations underway in a man-machine cooperation objective. The paper demonstrates how developments in causal reasoning can contribute judiciously to the supervision problem. An original causal modeling that includes time management is described and used for simulation, explanation and diagnosis.