Reliability Modeling of Infrastructure Load-Sharing Systems With Workload Adjustment

• Published in: IEEE transactions on reliability Vol. 68; no. 4; pp. 1283 - 1295
• Main Authors: Sun, Qiuzhuang, Ye, Zhi-Sheng, Revie, Matthew, Walls, Lesley
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.12.2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Analytical models; Asset management; Component reliability; Cumulative work load (CWL); Data models; Degradation; degradation failure; delayed renewal process; Gamma process; Infrastructure; Load modeling; load-sharing system; Numerical analysis; Operating costs; Reliability; Reliability analysis; Reliability engineering; Statistical inference; Statistical methods; Sun; System effectiveness; Water resources; Water utilities; Workload
• ISSN: 0018-9529; 1558-1721
• DOI: 10.1109/TR.2019.2900845

Motivated by the need to support effective asset management of infrastructure systems, this paper presents a novel reliability model for a load-sharing system where the operator can adjust component work load to balance system degradation. The operator-intervention effect, combined with other system complexities, makes modeling reliability interesting and challenging. We first develop cost modeling for a load-sharing system that has experienced operational service at the time of analysis. The system replacement process is modeled as a delayed renewal process for which the expected operational cost of the system is derived. A numerical algorithm is proposed to compute the cost, and the error bound is shown to be of order O(n -1 ). Next, we extend modeling to consider multiple heterogeneous systems located at different sites within the infrastructure network. Heterogeneities here refer to possible cross-site differences in the operating environments and the operators' actions. When the heterogeneities are observable, we model as covariates; otherwise, we model as random effects. Statistical inference methods are developed for the proposed models. An example using real data from a water utility illustrates the logical model behavior given parameter choices as well as showing how analysis might inform asset management.