Reliability Analysis of Corroding Pipelines Considering the Growth and Generation of Corrosion Defects

Author(s):  
H. Qin ◽  
W. Zhou

This paper presents a methodology to evaluate the reliability of corroding pipelines by simultaneously considering the growth and generation of corrosion defects. The non-homogeneous Poisson process is employed to model the generation of corrosion defects, whereas the non-homogeneous gamma process is used to characterize the growth of corrosion defects once generated. The parameters included in the non-homogeneous Poisson process and non-homogeneous gamma process are evaluated from the inline inspection data using a hierarchical Bayesian model. The measurement errors associated with the inline inspection tools are taken into account in the Bayesian updating. The time-dependent failure probability of the corroding pipeline is evaluated using the Monte Carlo simulation technique. The methodology is illustrated using a natural gas pipeline that has been subjected to multiple inline inspections over a period of time. The results illustrate the necessity to incorporate the generation of new corrosion defects in the reliability analysis of corroding pipelines.

2019 ◽  
Vol 37 (2) ◽  
pp. 223-242
Author(s):  
Nicolas La Roche-Carrier ◽  
Guyh Dituba Ngoma ◽  
Yasar Kocaefe ◽  
Fouad Erchiqui

Purpose Reliability plays an important role in the execution of the maintenance improvement and the understanding of its concepts is essential to predict the type of maintenance according to the equipment state. Thereby, a computational tool was developed and programming with VBA in Excel® for reliability and failure analysis in a mining context. The paper aims to discuss these issues. Design/methodology/approach The developed approach use the modeling of stochastic processes, such as the renewal process, the non-homogeneous Poisson process and less conventional method as the Bayesian approach, by considering Jeffreys non-informative prior. The resolution gives the best associated model, the parameters estimation, the mean time between failure and the reliability estimate. This approach is validated with the reliability analysis of inter-failure times from underground rock bolters subsystems, over a two-year period. Findings Results show that Weibull and lognormal probability distribution fit to the most subsystems inter-failure times. The study revealed that the bolting head, the rock drill, the screen handler, the electric/electronic system, the hydraulic system, the drilling feeder and the structural consume the most repair frequency. The hydraulic and electric/electronic subsystems represent the lowest reliability after 50 operation hours. Originality/value For the first time, this case study defines practical failures and reliability information for rock bolter subsystems based on real operation data. This paper is useful to the comparative evaluation of rock bolter by detecting the weakest elements and understanding failure patterns in the individual observation subsystems on the overall machine performance.


1995 ◽  
Vol 32 (03) ◽  
pp. 707-726 ◽  
Author(s):  
Patrick Homble ◽  
William P. McCormick

Shot noise processes form an important class of stochastic processes modeling phenomena which occur as shocks to a system and with effects that diminish over time. In this paper we present extreme value results for two cases — a homogeneous Poisson process of shocks and a non-homogeneous Poisson process with periodic intensity function. Shocks occur with a random amplitude having either a gamma or Weibull density and dissipate via a compactly supported impulse response function. This work continues work of Hsing and Teugels (1989) and Doney and O'Brien (1991) to the case of random amplitudes.


1982 ◽  
Vol 19 (4) ◽  
pp. 803-814 ◽  
Author(s):  
Mitsushi Tamari

The decision-maker drives a car along a straight highway towards his destination and looks for a parking place. When he finds a parking place, he can either park there and walk the distance to his destination or continue driving. Parking places are assumed to occur in accordance with a Poisson process along the highway. The decision-maker does not know the distance Y to his destination exactly in advance. Only an a priori distribution is assumed for Y and cases of typically important distribution are examined. When we take as loss the distance the decision-maker must walk and wish to minimize the expected loss, the optimal stopping rule and the minimum expected loss are obtained. In Section 3 a generalization to the cases of a non-homogeneous Poisson process and a renewal process is considered.


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