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Failure
Published in Nikhilesh Krishnamurthy, Amitabh Saran, Building Software, 2007
Nikhilesh Krishnamurthy, Amitabh Saran
Dependability is a combination of reliability — the probability that a system operates through a given operation specification — and availability — the probability that the system will be available at any required instant. Most software adopts the findings of Nowlan and Heap with respect to failures. During the initial stages of the system, when it is being used fresh in production, the failure rates are high. “Burn-in” is a concept used in the electrical and mechanical industries, wherein machines run for short periods of time after assembly so that the obvious defects can be captured before being shipped to a customer. In the software industry, alpha and beta programs are the burn-in. In fact, most customers are wary of accepting the first commercial release (v 1.0) of a software product. The longer a system is used, the higher the probability that more problems have been unearthed and removed.
Intelligent Vehicle Technologies
Published in Nicolas Navet, Françoise Simonot-Lion, Automotive Embedded Systems Handbook, 2017
Dependability is a generic term associated with functional and dysfunctional properties of a system or subsystem. Dependability attributes are most frequently referred to by their acronym—RAMS: “reliability,” which designates the continuity of a system’s service and is often measured by its mean time between failures (MTSF); “availability,” which designates a system’s readiness for service; “maintainability,” which designates a system’s ability to recover from a failure and is often measured by its mean time to repair (MTSR); and “safety,” which designates the risk of catastrophic (lethal) failure, a combination of probability and gravity. “Security” may also be mentioned, being a system’s ability to authorize known users to operate it and resist malicious attacks.
Reliability and Security
Published in Brian Roffel, Patrick Chin, Computer Control in the Process Industries, 2017
A system is usually evaluated in terms of its dependability. Dependability is more than reliability or availability –it also includes security and integrity. Availability is a measure of how often the system is available for performing the functions it is supposed to do. Security has to deal with mechanisms that guard against unauthorized system use or inadvertent misuse. Diagnostic and security actions have to be taken when malfunctions are detected to alert the operator and protect the system (or maintain functional system integrity). System security comprises hardware and software components. One example in this area is error prevention through keylocking functions.
A sliding mode observer-based robust fault-tolerant control allocation for descriptor systems
Published in Journal of Control and Decision, 2023
Ariful Mashud, Manas Kumar Bera
Any safety-critical system, such as a spaceship, an aircraft, a chemical factory, or a nuclear power plant, requires increased dependability and safety to avoid hazardous or emergencies resulting from actuator faults or failure. Fault-tolerant control (FTC) techniques are essential in any safety-critical system to prevent the controlled system from failing or stalling. The FTC scheme can be classified into two broad terms: passive and active FTC. The passive FTC scheme employs a fixed control structure to maintain satisfactory system performance despite system uncertainties and failures. The faults are estimated using a reliable fault detection and identification mechanism in the active FTC, and the information is used to reconfigure the underlying controller structure (Gao et al., 2015; Zhiwei et al., 2015).
Six Phase Transmission Line Protection Using Bat Algorithm Tuned Stacked Sparse Autoencoder
Published in Electric Power Components and Systems, 2023
Tirupathi Rao Althi, Ebha Koley, Subhojit Ghosh, Sunil Kumar Shukla
Furthermore, to access the reliability of the proposed scheme, the following three standard statistical indices have been considered for different fault scenarios (fault type, fault location, fault resistance and fault inception angle) and power system eventualities (i.e. variation in voltage, frequency, short circuit capacity of the source (SCC), X/R ratio of source, and loading conditions).Dependability: It represents the possible misdetection of faults and is estimated as the percentage of accurately detected fault cases to the total number of actual fault cases.Security: It represents the risk of relay maloperation by generating false tripping signal and is estimated as percentage of total no-fault cases to the total number of the actual no-fault cases.Accuracy: It represents the ability in correctly detecting the fault cases and is estimated as percentage of the total number of accurately predicted test cases (fault and no-fault) over the total number of test cases.
The study of structural properties of linear time-invariant systems and their dependability: a Monte Carlo simulation approach
Published in International Journal of Systems Science: Operations & Logistics, 2018
In classical dependability theory, the system's reliability is defined as the ability of an item to perform a required function, under given environmental and operational conditions and for a stated period of time (ISO 8402) (Rausand & Hoyland, 2004). As explained above, some structural properties are essential for a feedback system to achieve the mission it was designed for. Thus, it seems natural to extend the definition of the classical reliability to the structural properties. The definition of structural properties’ reliability was first introduced in Maza et al. (2012) as the probability that a system satisfies the studied property under some environmental and operational conditions. In Maza et al. (2012), the controllability property was studied and only the actuators were assumed to be prone to failures. The authors proposed to use the graphical conditions to compute the set of actuators which are essential for the system's reachability. Knowing the failure rate of these actuators, the reliability of controllability can be computed easily. In Dakil et al. (2015), more general and realistic cases where all the system's components can fail are considered. For that, the authors defined new graphs to study the system's controllability/observability where the graphical conditions of connectivity (CC1) and complete matching (CC2) were rewritten based on these graphs (§II.c). Conditions (CC1) and (CC2) are used to compute the set of system's components that are necessary and sufficient for the controllability and observability. The reliability of these is then computed based on the probability to satisfy the graphical conditions (Boukhobza et al., 2006; Dion et al., 2003).