Reliability modelling and maintenance policy optimization for a repairable parallel system

This paper proposes an integrated approach for reliability modelling and maintenance scheduling of repairable parallel systems subject to hidden failures. The system consists of heterogeneous redundant subsystems whose failures are revealed only by inspections. Inspections at periodic times reveal the components state and repair actions are decided by the excursion of a basic state process describing the total number of failed components in each subsystem. Using the standard renewal arguments, the paper aims at minimizing the average cost rate by the joint determination of the optimal inspection interval, the partial repair threshold and the preventive replacement threshold. We illustrate the procedure for the case as the components' lifetimes conform to the Weibull distribution. Numerical examples are used to illustrate the proposed model and the response of the optimal solutions to the model's parameters.

Reliability modelling and maintenance policy optimization for a repairable parallel system

This paper proposes an integrated approach for reliability modelling and maintenance scheduling of repairable parallel systems subject to hidden failures. The system consists of heterogeneous redundant subsystems whose failures are revealed only by inspections. Inspections at periodic times reveal the components state and repair actions are decided by the excursion of a basic state process describing the total number of failed components in each subsystem. Using the standard renewal arguments, the paper aims at minimizing the average cost rate by the joint determination of the optimal inspection interval, the partial repair threshold and the preventive replacement threshold. We illustrate the procedure for the case as the components' lifetimes conform to the Weibull distribution. Numerical examples are used to illustrate the proposed model and the response of the optimal solutions to the model's parameters.

A Markovian Control Approach to Maintenance Optimization of a System with Stochastic Dependence and Hidden Failures

Given partial information, this paper considers both disruption and maintenance scheduling problem for a parallel-series system with failure interactions and hidden failures. By projection on an observed history, the filtering treatment contributes to detecting an unobservable disruption time at which one of subsystems experiences failure. The model is developed by setting it in a Markovian control framework with partial information pattern in which a control process as a repair level impacts on the system availability via maintaining both the inspection and the disruption intensity at a desirable level. Since each repair and maintenance action incurs cost, the problem is to determine an optimal control process that balances the amount of maintenance and maintenance costs. The optimal control process emerges as the solution of deterministic Hamilton Jacobi equations, and a recursive scheme is used to solve them. We illustrate the procedure for the case when the failure time of components is defined as the first passage time of a Wiener process. The proposed model is illustrated through numerical examples.

Hierarchical Reasoning about Faults in Cyber-Physical Energy Systems using Temporal Causal Diagrams

fault management systems that observe the state of the system, decide if there is an anomaly and then take automated actions to isolate faults. For example, in electrical networks relays and breaks isolate faults in order to arrest failure propagation and protect the healthy parts of the system. However, due to the limited situational awareness and hidden failures the protection devices themselves, through their operation (or mis-operation) may cause overloading and the disconnection of parts of an otherwise healthy system. Additionally, often there can be faults in the management system itself leading to situations where it is difficult to isolate failures. Our work presented in this paper is geared towards solution of this problem by describing the formalism of Temporal Causal Diagrams (TCD-s) that augment the failure models for the physical systems with discrete time models of protection elements, accounting for the complex interactions between the protection devices and the physical plants. We use the case study of the standard Western System Coordinating Council (WSCC) 9 bus system to describe four different fault scenarios and illustrate how our approach can help isolate these failures. Though, we use power networks as exemplars in this paper our approach can be applied to other distributed cyberphysical systems, for example water networks.