Interval estimation for k-out-of-n load-sharing systems. (4th March 2017)

• Record Type: Journal Article
• Authors: Kong, Yaonan; Ye, Zhisheng
• Is Part Of: IISE transactions. Volume 49:Number 3(2017)
• Page Start: 344
• Page End: 353
• Publication Date: 2017-03-04
• Subjects: Exponential distribution -- log-linear link function -- pivotal quantity -- generalized pivotal quantity -- reliability; Industrial engineering -- Periodicals; Systems engineering -- Periodicals; Industrial engineering; Systems engineering; Electronic journals; Periodicals; 670.285
• DOI: 10.1080/0740817X.2016.1217102
• Languages: English
• ISSNs: 2472-5854

Abstract

ABSTRACT: Load-sharing systems are commonly seen in industry; e.g., water pumps in a cooling system. In a load-sharing system, the stress level on each surviving component increases as components fail. The load-sharing nature of the component failure process creates difficulties in statistical inference for the system. This article develops two interval procedures for failure data from load-sharing systems. We assume that the component lifetime under each stress level follows an exponential distribution, a common distribution in reliability engineering. A log-linear link function is used to model the relationship between the stress levels and component lifetimes. In the two proposed interval procedures, we construct confidence intervals for the model parameters by using pivotal quantities and generalized pivotal quantities. Interval estimation for important reliability characteristics including the mean lifetime and the reliability of the load-sharing system is also discussed. A simulation study shows that the confidence intervals produced from the proposed procedures are more accurate compared with traditional approximate interval procedures, such as the large sample normal approximation and the bootstrap. A numerical example is used to demonstrate the performance of the proposed procedures.