Engineering topics
Publications and source records attributed to White, A. L..
An approximation formula is derived for the probability of failure for fault-tolerant process-control computers. These computers use redundancy and reconfiguration to achieve high reliability. Finite-state Markov models capture the dynamic behavior of component failure and system recovery, and the approximation formula permits an estimation of system reliability by an easy examination of the model.
Upper and lower bounds are derived for the probability of failure for a class of highly reliable process control computers. The bounds are synthetic in the sense that the descriptions of component failure and system recovery are assumed to be obtained from different sources. The reliability model is constructed under the assumption that the processes are independent.
This paper determines the information required about system recovery to compute the reliability of a class of reconfigurable systems. Upper and lower bounds are derived for these systems. The class consists of those systems that satisfy five assumptions: the components fail independently at a low constant rate, fault occurrence and system reconfiguration are independent processes, the reliability model is semi-Markov, the recovery functions which describe system configuration have small means and variances, and the system is well designed. The bounds are easy to compute, and examples are included.
A way of considering a small but often used class of reliability model and approximating algebraically the systems reliability is shown. The models considered are appropriate for redundant reconfigurable digital control systems that operate for a short period of time without maintenance, and for such systems the method gives a formula in terms of component fault rates, system recovery rates, and system operating time.
A reliability estimation method for systems that continually accumulate faults because of imperfect diagnostics is developed and an application for redundant digital avionics is presented. The present method assumes that if a fault does not appear in a short period of time, it will remain hidden until a majority of components are faulty and the system fails. A certain proportion of a component's faults are detected in a short period of time, and a description of their detection is included in the reliability model. A Markov model of failure during flight for a nonreconfigurable five-plex is presented for a sequence of one-hour flights followed by maintenance.
This paper examines the reliability of three architectures for six components. For each architecture, the probabilities of the failure states are given by algebraic formulas involving the component fault rate, the system recovery rate, and the operating time. The dominant failure modes are identified, and the change in reliability is considered with respect to changes in fault rate, recovery rate, and operating time. The major conclusions concern the influence of system architecture on failure modes and parameter requirements. Without this knowledge, a system designer may pick an inappropriate structure.