Reliability evaluation of multi-state series systems with performance sharing
Creators
- 1. School of Mathematics, Southeast University, Nanjing 211189 (China)
- 2. School of Mechanical Engineering, Southeast University, Nanjing 211189 (China)
Description
Highlights: • A new multi-state system with performance sharing is proposed. • The surplus performance of each unit can be shared by its adjacent units. • The entire system fails if the demand of any unit is not satisfied. • An algorithm based on the UGF technique is developed for reliability evaluation. • Analytical and numerical examples are provided to validate the proposed method. In this paper, a new reliability model for a multi-state system (MSS) with performance sharing is proposed. The MSS consists of N multi-state units connected in series. Each unit in the system has a random performance level and a random demand. If the performance of a unit exceeds its demand, the surplus performance can be transmitted to its adjacent units through intermediate transmitters. Each transmitter has a random capacity, through which only a limited amount of performance can be transmitted. The entire system fails if the demand of any unit is not satisfied. An algorithm based on the universal generating function (UGF) is developed to evaluate the reliability of the system. Analytical and numerical examples are provided to validate the proposed method. Examples show that the developed algorithm is efficient in system reliability evaluation.
Availability note (English)
Available from http://dx.doi.org/10.1016/j.ress.2018.01.012Additional details
Identifiers
- DOI
- 10.1016/j.ress.2018.01.012;
- PII
- S0951832017305069;
Publishing Information
- Journal Title
- Reliability Engineering and System Safety
- Journal Volume
- 173
- Journal Page Range
- p. 58-63
- ISSN
- 0951-8320
- CODEN
- RESSEP
INIS
- Country of Publication
- United Kingdom
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 52112479
- Subject category
- S42: ENGINEERING;
- Descriptors DEI
- ALGORITHMS; CAPACITY; EVALUATION; PERFORMANCE; RANDOMNESS; RELIABILITY; STOCHASTIC PROCESSES
- Descriptors DEC
- MATHEMATICAL LOGIC
Optional Information
- Copyright
- Copyright (c) 2018 Elsevier Ltd. All rights reserved.