The SACSO methodology for troubleshooting complex systems

Abstract

The paper describes the task of performing efficient decision-theoretic troubleshooting of electromechanical devices. In general, this task is NP-complete, but under fairly strict assumptions, a greedy approach will yield an optimal sequence of actions, as discussed in the paper. This set of assumptions is weaker than the set proposed by Heckerman et al. (1995). However, the printing system domain, which motivated the research and which is described in detail in the paper, does not meet the requirements for the greedy approach, and a heuristic method is used. The method takes value of identification of the fault into account and it also performs a partial two-step look-ahead analysis. We compare the results of the heuristic method with optimal sequences of actions, and find only minor differences between the two.

Binary integer programming solution for troubleshooting with dependent actions

“…Theorem 3.5 is not very surprising in view of similar but weaker results [4,5]. The author is not aware of a published full proof of the theorem, and therefore it is included here.…”

“…Jensen et al [5] describe an algorithm called Updating P/C. On i th step, 1 ≤ i ≤ n, the algorithm selects an action A ∈ A(e i−1 ) maximizing the ratio P(A | e i−1 ) c(A) .…”

“…We study a combinatorial problem known as single-fault troubleshooting with dependent actions [4,5]. The problem is NP-hard [12], and it is a straightforward generalization of problems known as min-sum set cover [3] and pipelined-set cover [9].…”

An Overview of the Development for Cable-Driven Parallel Manipulator

“…Then, Japan, France, and Germany implemented several different cable parallel robots, respectively [17][18][19]. One of the most crucial applications is to build receiving platform for large span radio telescopes, such as American Arecibo project, Chinese FAST project, and Canadian Lambert telescope [20][21][22].…”

Replacement policies for a complex system with unobservable components using dynamic Bayesian networks

“…3 Although DTTPs are characterized by their complex system structures, they have always been studied as a static problem. 4,5,6,7,8 Naturally, there are some problems for which a static troubleshooting can not be applied. These can be working systems which are under continuous or discrete time monitoring and produce undesirable faulty messages while they are working or systems which are not even observable.…”