Nonparametric Reliability Analysis of Spacecraft Failure Data

The application of reliability-based structural integrity enables the process of quantitative risk assessment as part of pipelines’ integrity management program (IMP). This paper explores two topics that present challenges in terms of the practical adoption of a reliability-based IMP. The first challenge is the balance between perceived and true risk when implementing a quantitative reliability-based integrity model. This is a cornerstone for building stakeholder confidence in the calculated probability of failure (PoF) which is applied to safety and economically driven integrity decisions. The second challenge is the assurance that all relevant sources of uncertainty have been incorporated, which is essential for ensuring an accurate representation of the risk of failure of the pipeline. The level of conservatism (i.e. sufficient margin of error to maintain safety) incorporated when addressing these challenges may create a situation where calculated PoFs become inflated; becoming disproportionate to the failure history and contradictory to the current safe operation of pipelines being modeled. Two different PoF calibration approaches are proposed as practical options to address these challenges. The first method calibrates model error using an operator’s in-service failure history (i.e. failures that occurred under normal operation). The second method uses a set of failure data (including hydrostatic test failures and in-service failures) as selected by the operator considering key factors to ensure adequate representation of their specific pipeline system. These options will be demonstrated by assessing the integrity reliability of a hypothetical pipeline system. This work is expected to help evaluate the feasibility of challenging current practices regarding practical inclusion of epistemic uncertainty in integrity reliability analysis of pipelines.

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Supply and failure data reliability analysis system

Microelectronics Reliability ◽

10.1016/0026-2714(87)90216-2 ◽

1987 ◽

Vol 27 (2) ◽

pp. 382

Keyword(s):

Reliability Analysis ◽

Data Reliability ◽

Failure Data ◽

Analysis System

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Case Study on Reliability of Automotive Painting Shop Robots

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.1125.516 ◽

2015 ◽

Vol 1125 ◽

pp. 516-520

Author(s):

Mohd Amin Abd Majid ◽

Ahmad Fauzi Fudzin

Keyword(s):

Reliability Analysis ◽

High Reliability ◽

Mean Time Between Failures ◽

Assembly Plant ◽

Failure Data ◽

Time Between Failures ◽

Plant Maintenance ◽

Automotive Assembly ◽

Mean Time

Robots in automotive assembly plant are crucial for automation of the plant. As the robots are expensive, they are the main contributor to plant investment. Thus, it is important for the robots to have high reliability. This paper presents the reliability analysis of robots at an automotive assembly plant. The analysis was based on operating hours and frequency of the failures of the robots. The data were acquired from plant maintenance data. Using seven years of failure data, the robots’ mean time between failures (MTBF) and reliability were evaluated. Constant failure rate was assumed in the analysis. From the analysis it is noted that the reliability of the robots at the plant varies from 15% to 62% and 2% to 39% for 10,000 hours and 20,000 hours respectively. These findings could assist the maintenance manager to schedule the maintenance and replacement of the robot at the plant.

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Maintenance Plan for a Fleet of Rotary Drill Rigs/Harmonogram Utrzymania I Konserwacji Floty Obrotowych Urządzeń Wiertniczych

Archives of Mining Sciences ◽

10.2478/amsc-2014-0031 ◽

2014 ◽

Vol 59 (2) ◽

pp. 441-453 ◽

Cited By ~ 1

Author(s):

Mohammad Javad Rahimdel ◽

Mohammad Ataei ◽

Reza Khalokakaei ◽

Seyed Hadi Hoseinie

Keyword(s):

Reliability Analysis ◽

Preventive Maintenance ◽

Performance Data ◽

Reliability Modeling ◽

Failure Data ◽

Sarcheshmeh Copper Mine ◽

Maintenance Program ◽

And Performance ◽

Drilling Rigs ◽

Maintenance Plan

Abstract In this paper a basic methodology was used for the reliability modeling and developing a maintenance program for a fleet of four drilling rigs. Failure and performance data was collected from Sarcheshmeh Copper Mine in Iran for a two-year period. Then the available data was classified and analyzed and reliability of all subsystems and whole rigs were modeled and studied. The failure data showed that, in all rigs, electrical, hydraulic and drilling systems are the most frequent failing subsystems of the machine. The reliability analysis showed that transmission system is the most reliable subsystem in all studied rigs. In order to calculate the reliability of whole fleet, it was assumed that operation of at least two drilling rigs is essential for satisfying the production goals. Therefore, probabilistic possibility of all fleet’s states were calculated. In this paper, 80% is selected as the desired level of reliability for developing of preventive maintenance program for each subsystem of the drilling rigs. Finally, the practical approaches were suggested for improving the maintenance operation and productivity of the studied fleet.

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An E-Bayesian method for reliability analysis of exponentially distributed products with zero-failure data

Eksploatacja i Niezawodnosc - Maintenance and Reliability ◽

10.17531/ein.2016.3.17 ◽

2016 ◽

Vol 18 (03) ◽

pp. 445-449 ◽

Cited By ~ 5

Author(s):

Yi-Chao Yin ◽

Hong-Zhong Huang ◽

Weiwen Peng ◽

Yan-Feng Li ◽

Jinhua Mi

Keyword(s):

Reliability Analysis ◽

Bayesian Method ◽

Failure Data

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Reliability Analysis Based on Improved Bayes Method of AMSAA Model

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.482-484.2336 ◽

2012 ◽

Vol 482-484 ◽

pp. 2336-2340

Author(s):

Yang Qiang ◽

Lei Zhang ◽

Zhi Li Sun ◽

Yi Liu ◽

Xue Bin Bai

Keyword(s):

Reliability Analysis ◽

Machine Tools ◽

Interval Estimation ◽

Point Estimation ◽

Life Data ◽

Failure Data ◽

Amsaa Model ◽

Nc Machine ◽

Nc Machine Tools ◽

Five Axis

Aiming at the defects that failure samples of five-axis NC machine tools is small, traditional reliability analysis is not accurate, this paper presents reliability analysis mode based on improved Bayesian method for AMSAA model. Firstly, we obtain the failure model of NC machine tools meets the AMSAA model according to goodness-of-fit test, and in order to meet the requirements of simplifying engineering calculations, this paper adpots a method of Coefficient equivalent which converts failure Data into index-life data; then using Bayesian methods to estimate reliability parameters for the Index-life data; for the last we proceed point estimation and interval estimation for the MTBF of the machine. Take High-speed five-axis NC machine tools t of VMC650m for example, the result proved that the method can take advantage of a small sample of the equipment to proceed point estimation and interval estimation for MTBF failure data, and provide a reference for the optimization of maintenance strategies and Diagnostic work of the NC machine tools.

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