The rate of occurrence of failures (ROCOF) is a widely utilized indicator for assessing a system's performance over time, yet it does not fully disclose the instantaneous behavior of a system. This paper introduces new measures to complement the ROCOF, providing a more comprehensive understanding of system reliability, particularly for Markov systems. We define the Rate of Occurrence of Repairs (ROCOR), which quantifies the system's instantaneous tendency to transition from failure to working states, and the rate of inoccurrence (ROI), which measures the propensity to remain within the current subset of states (either working or failure) without transitioning out. Explicit expressions for the computation of these rates are derived for Markov systems. Furthermore, a total mobility rate (TMR) is proposed, integrating these individual rates to capture the overall dynamism of the system. The utility of these new indicators is demonstrated through a significant real-world application to wind farm management. The results from the wind farm study show that ROCOR, ROI, and TMR, when used in conjunction with ROCOF, reveal nuanced operational dynamics and reliability characteristics that are not discernible from static measures like Weibull parameters or ROCOF alone. These indicators can distinguish between sites with similar long-term wind profiles by identifying different “reliability logics,” such as persistence-driven versus transition-driven behaviors. This enriched, time-dependent perspective provides valuable information for maintenance scheduling, operational strategies, and risk assessment, ultimately enhancing the ability to manage complex systems effectively. © 2026 John Wiley & Sons Ltd.

Instantaneous Failure, Repair, and Mobility Rates for Markov Reliability Systems: A Wind-Farm Application

D'Amico Guglielmo;Petroni Filippo
2026-01-01

Abstract

The rate of occurrence of failures (ROCOF) is a widely utilized indicator for assessing a system's performance over time, yet it does not fully disclose the instantaneous behavior of a system. This paper introduces new measures to complement the ROCOF, providing a more comprehensive understanding of system reliability, particularly for Markov systems. We define the Rate of Occurrence of Repairs (ROCOR), which quantifies the system's instantaneous tendency to transition from failure to working states, and the rate of inoccurrence (ROI), which measures the propensity to remain within the current subset of states (either working or failure) without transitioning out. Explicit expressions for the computation of these rates are derived for Markov systems. Furthermore, a total mobility rate (TMR) is proposed, integrating these individual rates to capture the overall dynamism of the system. The utility of these new indicators is demonstrated through a significant real-world application to wind farm management. The results from the wind farm study show that ROCOR, ROI, and TMR, when used in conjunction with ROCOF, reveal nuanced operational dynamics and reliability characteristics that are not discernible from static measures like Weibull parameters or ROCOF alone. These indicators can distinguish between sites with similar long-term wind profiles by identifying different “reliability logics,” such as persistence-driven versus transition-driven behaviors. This enriched, time-dependent perspective provides valuable information for maintenance scheduling, operational strategies, and risk assessment, ultimately enhancing the ability to manage complex systems effectively. © 2026 John Wiley & Sons Ltd.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11564/876814
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