Modular asset management framework based on Petri-net formalisations and risk-aware maintenance

Abstract

Probabilistic risk analysis (PRA) is fundamental in safety assessment. Current PRA tools face notable limitations for complex systems, such as the heavily reliance on historical failure data. Moreover, existing tools cannot replicate complex asset management strategies easily, leading to inefficiency when analysing a multitude of scenarios. This paper addresses these limitations by introducing a Coloured Hybrid Petri Net (CHPN) framework for the PRA of complex systems. The framework integrates a hybrid system to capture the complex nature of degradation. Moreover, unlike other tools, the framework is modular. This provides a flexible approach to scenario modelling and ensures a more accurate understanding of the system. This paper also investigates the effect of maintenance policy on system performance. The paper evaluates condition-based maintenance (CBM) to two-levels of risk-based maintenance (RBM). The paper also presents a risk-aware policy that integrates a system-level RBM and CBM to capture the dynamic between components condition, health and their influence on system performance. This ensures a holistic view of system's safety and reliability. By integrating advanced modelling techniques and maintenance policies, the CHPN framework provides a new dimension to PRA to enable more accurate risk assessments, informed asset management strategies, and enhanced safety assurance for critical infrastructure.