Supporting group maintenance through prognostics-enhanced dynamic dependability prediction

Condition-based maintenance strategies adapt maintenance planning through the integration of online condition monitoring of assets. The accuracy and cost-effectiveness of these strategies can be improved by integrating prognostics predictions and grouping maintenance actions respectively. In complex industrial systems, however, effective condition-based maintenance is intricate. Such systems are comprised of repairable assets which can fail in different ways, with various effects, and typically governed by dynamics which include time-dependent and conditional events. In this context, system reliability prediction is complex and effective maintenance planning is virtually impossible prior to system deployment and hard even in the case of condition-based maintenance. Addressing these issues, this paper presents an online system maintenance method that takes into account the system dynamics. The method employs an online predictive diagnosis algorithm to distinguish between critical and non-critical assets. A prognostics-updated method for predicting the system health is then employed to yield well-informed, more accurate, condition-based suggestions for the maintenance of critical assets and for the group-based reactive repair of non-critical assets. The cost-effectiveness of the approach is discussed in a case study from the power industry

Risk Assessment of a Wind Turbine: A New FMECA-Based Tool With RPN Threshold Estimation

A wind turbine is a complex system used to convert the kinetic energy of the wind into electrical energy. During the turbine design phase, a risk assessment is mandatory to reduce the machine downtime and the Operation & Maintenance cost and to ensure service continuity. This paper proposes a procedure based on Failure Modes, Effects, and Criticality Analysis to take into account every possible criticality that could lead to a turbine shutdown. Currently, a standard procedure to be applied for evaluation of the risk priority number threshold is still not available. Trying to fill this need, this paper proposes a new approach for the Risk Priority Number (RPN) prioritization based on a statistical analysis and compares the proposed method with the only three quantitative prioritization techniques found in literature. The proposed procedure was applied to the electrical and electronic components included in a Spanish 2 MW on-shore wind turbine

State-of-research on performance indicators for bridge quality control and management

The present study provides a review of the most diffused technical and non-technical performance indicators adopted worldwide by infrastructure owners. This work, developed within the European COST Action TU 1406—“Quality specifications for roadway bridges, standardization at a European level,” aims to summarize the state-of-art maintenance scheduling practices adopted by bridge owners, mainly focusing on the identification and classification of the most diffused performance indicators (PIs). PIs are subdivided in technical and non-technical ones: for this latter subclass, PIs are classified in environmental, social and economic-targeted. The study aims to be a reference for researchers dealing with performance-based assessments and bridge maintenance and management practices.Peer ReviewedPostprint (published version

Reliability modelling of redundant safety systems without automatic diagnostics incorporating common cause failures and process demand

Sriramula’s work within the Lloyd’s Register Foundation Centre for Safety and Reliability Engineering at the University of Aberdeen is supported by Lloyd’s Register Foundation. The Foundation helps to protect life and property by supporting engineering-related education, public engagement and the application of re-search.Peer reviewedPostprin

Risk-informed approach to the safety improvement of the reactor protection system of the AGN-201K research reactor

Periodic safety reviews (PSRs) are conducted on operating nuclear power plants (NPPs) and have been mandated also for research reactors in Korea, in response to the Fukushima accident. One safety review tool, the probabilistic safety assessment (PSA), aims to identify weaknesses in the design and operation of the research reactor, and to evaluate and compare possible safety improvements. However, the PSA for research reactors is difficult due to scarce data availability. An important element in the analysis of research reactors is the reactor protection system (RPS), with its functionality and importance. In this view, we consider that of the AGN-201K, a zero-power reactor without forced decay heat removal systems, to demonstrate a risk-informed safety improvement study. By incorporating risk- and safety-significance importance measures, and sensitivity and uncertainty analyses, the proposed method identifies critical components in the RPS reliability model, systematically proposes potential safety improvements and ranks them to assist in the decision-making process. Keywords: Research reactor, Reactor protection system, Probabilistic safety assessment, Risk-informed design, Unavailability analysis, Sensitivity analysi

Average probability of failure on demand estimation for burner management systems

Proper estimation of Safety Integrity Level (SIL) depends largely on accurate estimation of Safety performance in terms of average Probability of Failure on Demand, (PFDavg). For complex architectures of logic solvers, sensors, and valves, this can be calculated by distinguishing combinations of subsystems with basic (K-out-of-N) KooN approach for identical components. In the case of the typical configurations of valves for a burner management systems with non-identical subsystem configurations the KooN approach does not apply. Hence, it becomes an issues to calculate the correct safety performance since some of the established methods give too optimistic results due to lack of Common cause Failure information and data on non-identical components or sub-systems. This paper formulates a Markov model for determination of average probability of failure on demand for non-identical components and also proposes a more conservative lowest failure rate approach and maximum beta factor contrary to pragmatic minimum or average beta for correct estimation of average probability of failure on demand. It can be deduced that the measure of safety performance for components or subsystems with unequal failure rates depends largely on common cause failure, but a single beta factor is not appropriate to model the commonality of the failure. The result revealed that both geometric mean and lowest failure rate approaches result in different values with the lowest failure rate being the most conservative and optimistic result.Keywords: burner management systems, probability of failure on demand, common cause failure, KooN configurations, and lowest failure rate, Markov Analysi