Fault Tolerant Computer System for the A129 Helicopter

Quality & Reliability Eng

Ding

et al. 2018

Standby redundancy has been extensively applied to critical engineering systems to enhance system reliability. Researches on reliability evaluation for standby systems focus more on systems with binary‐state elements. However, multi‐state elements with different performances have played a significant role in engineering systems. This paper presents an approach for reliability analysis of standby systems composed of multi‐state elements with constant state transition rates and absorbing failure states. The approach allows modelling different standby systems beyond cold, warm and hot ones by taking into account differences in possible maintenance of elements in standby and operation modes and dependence of elements' operational behavior on their initial state at the time of activation. An iterative algorithm for reliability evaluation based on element state probabilities is suggested. Illustrating examples of evaluating reliability of different types of homogeneous and heterogeneous standby systems are demonstrated.

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Reliability analysis of standby systems with multi‐state elements subject to constant transition rates

Jia

Quality & Reliability Eng

Ding

et al. 2018

“…Standby redundancy techniques have been used to enhance system availability in practical engineering system designs such as computation systems, 1–3 flight controls, 4 space missions, 5,6 telecommunication systems, 7 and power plants. 8 In standby systems, selected components are in operating mode, while the remaining redundancy components are in standby mode.…”

Section: Introductionmentioning

confidence: 99%

1-out-of-N multi-state standby systems with state-dependent random replacement times

Proceedings of the Institution of Mechanical Engineers, Part O:

Jia

Ding

et al. 2017

Research on analysis of replacement time in standby systems has focused on systems with binary-state standby components. However, when the standby components are multi-state, the replacement time depends on the state of the standby component when it is activated for replacement. This article considers the impacts of state-dependent random replacement times on 1-out-of-N systems consisting of multi-state standby components. Numerical algorithms for evaluating the multi-state standby system's instantaneous availability, expected availability over system mission time and the expected mission completion time are proposed. A Markov state transition model is used to describe the component behaviour in standby mode. The time-to-failure of the operating component and the replacement time of the standby component can obey arbitrary types of distributions. Illustrative examples are provided to demonstrate the proposed numerical algorithms. The effects of the number of standby components, different replacement time distributions and activation sequences are also discussed.

“…T HE warm standby sparing technique has been widely applied to enhance the reliability and availability of critical systems in various application areas such as storage systems [1], high performance computing systems [2], flight controls [3], space missions [4], and power systems [5]- [7]. In a warm standby system, one or multiple elements are on-line and operating, with some elements serving as standby spares.…”

Section: Introductionmentioning

confidence: 99%

Heterogeneous 1-Out-of-N Warm Standby Systems With Dynamic Uneven Backups

Xing

2015

IEEE Trans. Rel.

In this paper, mission reliability, expected mission completion time, and cost of non-repairable 1-out-of-: G warm standby sparing systems subject to uneven backup actions are modeled and optimized. The backup actions are used to facilitate the data recovery process in the case of an online operating element failure, which enables an activated standby element to take over the mission task through subsequent data retrievals. Both data backup and retrieval times are dynamic, and physically dependent on the amount of work performed. The system elements are not necessarily identical; each element can be characterized by a different time-to-failure distribution, a different performance, and a different level of readiness to take over the system task during the warm standby mode. An iterative numerical method is first proposed to simultaneously evaluate mission reliability, expected mission completion time, and the cost of the considered heterogeneous warm standby systems. Due to the non-monotonic effect of the backup distribution on the mission reliability, time, and cost, we formulate and solve the optimal backup distribution problem considering different combinations of optimization objectives and constraints. In the case of system elements being non-identical, their activation order can influence the mission reliability, expected mission completion time, and mission cost significantly. Therefore, we also formulate and solve the optimal element sequencing problem for the considered system. Furthermore, new integrated optimization problems are formulated and addressed. The integrated optimization aims to identify the optimal combination of backup distribution and element activation order that maximizes the mission reliability, or minimizes the expected mission time or mission cost. As shown through examples, the proposed methodology can implement a tradeoff analysis among the three mission requirements of reliability, cost, and completion time, leading to the optimal decision on both backup and standby policies of warm standby systems.