Optimum Search Routines for Automatic Fault Location

This paper comprises an extension of Model I of a recent paper of Gluss, (1959) Opns. Res. 7, 468–477, and its purpose is to dictate strategies that minimize the expected cost (in time) of locating a fault in a complex system of equipment. These strategies are specialized for use with automatic testing equipment The model assumes that the complex system consists of N modules containing n(1), …, n(N) elements respectively, that the cost of examining the modules are t₁, …, t_N respectively, and that the costs of examining the elements within the rth module are t_r1, …, t_rn(r). It is further assumed that module tests are performed to find which module is faulty before element tests are performed, and that there exist probabilities at each stage that errors of two kinds can be made (1) that the test fails to detect an actual fault in the module or item tested, (2) that the test finds a fault that does not exist. The estimation of the probabilities of faults lying in respective modules or elements is performed in a different way from that in Gluss' paper they are computed from element reliability data by manipulation of their λ parameters, where λ is the element failure rate. Furthermore, consideration is given to fault symptoms that are supplied by weighting the probabilities according to the symptom information. Because of the anticipated difficulty in obtaining the necessary parameter estimates, the analysis may be most useful for its illumination of the influence the several required estimates have on the optimum search routine.