Competing Risks Analysis of Reliability, Survivability, and Prognostics and Health Management (PHM)

2008 ◽  
Author(s):  
Zhanshan Ma ◽  
Axel W. Krings
Keyword(s):  
Competing Risks ◽  
Health Management ◽  
Prognostics And Health Management ◽  
Competing Risks Analysis

A Review on Prognostics and Health Management : 2013~2018

2019 ◽  
Vol 19 (1) ◽  
pp. 68-84 ◽  
Author(s):  
Hyun Su Sim ◽  
Jun-Gyu Kang ◽  
Yong Soo Kim
Keyword(s):  
Health Management ◽  
Prognostics And Health Management

Remaining useful life estimation: a review on stochastic process-based approaches

2020 ◽  
Vol 14 ◽  
Author(s):  
Dangbo Du ◽  
Jianxun Zhang ◽  
Xiaosheng Si ◽  
Changhua Hu
Keyword(s):  
Stochastic Process ◽  
Health Management ◽  
Remaining Useful Life ◽  
Future Trends ◽  
Prognostics And Health Management ◽  
Inverse Gaussian ◽  
Life Estimation ◽  
Inverse Gaussian Process ◽  
Pros And Cons ◽  
Useful Life

Background: Remaining useful life (RUL) estimation is the central mission to the complex systems’ prognostics and health management. During last decades, numbers of developments and applications of the RUL estimation have proliferated. Objective: As one of the most popular approaches, stochastic process-based approach has been widely used for characterizing the degradation trajectories and estimating RULs. This paper aimed at reviewing the latest methods and patents on this topic. Methods: The review is concentrated on four common stochastic processes for degradation modelling and RUL estimation, i.e., Gamma process, Wiener process, inverse Gaussian process and Markov chain. Results: After a briefly review of these four models, we pointed out the pros and cons of them, as well as the improvement direction of each method. Conclusion: For better implementation, the applications of these four approaches on maintenance and decision-making are systematically introduced. Finally, the possible future trends are concluded tentatively.

scholarly journals Multiple imputation strategies for a bounded outcome variable in a competing risks analysis

2021 ◽  
Author(s):  
Elinor Curnow ◽  
Rachael A. Hughes ◽  
Kate Birnie ◽  
Michael J. Crowther ◽  
Margaret T. May ◽  
...  
Keyword(s):  
Multiple Imputation ◽  
Competing Risks ◽  
Outcome Variable ◽  
Competing Risks Analysis

scholarly journals Voluntary Withdrawals, Forced Resignations, Collective Retirements or Just Bad Fortune? A Competing Risks Analysis of Ministerial Turnover in the German Länder (1990-2010)

2016 ◽  
Vol 34 (1) ◽  
pp. 54-76
Author(s):  
Sebastian Jäckle
Keyword(s):  
Competing Risks ◽  
Prime Minister ◽  
The Other ◽  
Cox Models ◽  
Coalition Governments ◽  
German Länder ◽  
Competing Risks Analysis ◽  
Terminal Events ◽  
Hiring And Firing ◽  
High Level

This paper explores the determinants of ministerial duration within the German Länder between 1990 and 2010. In arguing that different terminal events ceasing ministerial tenures should be analyzed separately, it distinguishes four exit types: voluntary, forced, collective (ministers leaving office because their whole party does so) and exits that are neither volitional acts of the minister nor politically induced. Depending on the exit type, competing-risks Cox-models show different effects for one and the same variable on the hazard for ministerial turnover. Seniority in high-level politics for example helps not to be forced out of office while it has no effect on voluntary or collective exits. Heading an important ministry on the other hand increases the chances to rise to other positions in high politics or private business, but does not impact the other two hazards. The analysis furthermore shows that the principal-agent-logic known from Westminster systems with the prime minister being largely sovereign in hiring and firing cabinet members must be adapted to the German context of frequent coalition governments. In coalition governments, only ministers from the same party as the prime minister exhibit higher hazards for forced exits, while ministers from other coalition partners are much safer in that regard.

A Copula-Based Sampling Method for Data-Driven Prognostics and Health Management

2013 ◽  
Author(s):  
Zhimin Xi ◽  
Rong Jing ◽  
Pingfeng Wang ◽  
Chao Hu
Keyword(s):  
Sampling Method ◽  
Failure Time ◽  
Health Management ◽  
Remaining Useful Life ◽  
Training Data ◽  
Data Driven ◽  
Prognostics And Health Management ◽  
Statistical Relationship ◽  
Cooling Fans ◽  
On Line

This paper develops a Copula-based sampling method for data-driven prognostics and health management (PHM). The principal idea is to first build statistical relationship between failure time and the time realizations at specified degradation levels on the basis of off-line training data sets, then identify possible failure times for on-line testing units based on the constructed statistical model and available on-line testing data. Specifically, three technical components are proposed to implement the methodology. First of all, a generic health index system is proposed to represent the health degradation of engineering systems. Next, a Copula-based modeling is proposed to build statistical relationship between failure time and the time realizations at specified degradation levels. Finally, a sampling approach is proposed to estimate the failure time and remaining useful life (RUL) of on-line testing units. Two case studies, including a bearing system in electric cooling fans and a 2008 IEEE PHM challenge problem, are employed to demonstrate the effectiveness of the proposed methodology.

scholarly journals Impact of Increasing Age on Cause-Specific Mortality and Morbidity in Patients With Stage I Non–Small-Cell Lung Cancer: A Competing Risks Analysis

2017 ◽  
Vol 35 (3) ◽  
pp. 281-290 ◽  
Author(s):  
Takashi Eguchi ◽  
Sarina Bains ◽  
Ming-Ching Lee ◽  
Kay See Tan ◽  
Boris Hristov ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Competing Risks ◽  
Independent Predictor ◽  
Forced Expiratory Volume ◽  
Stage I ◽  
Diffusing Capacity ◽  
Curative Intent ◽  
Mortality And Morbidity ◽  
Competing Risks Analysis ◽  
Specific Mortality

Purpose To perform competing risks analysis and determine short- and long-term cancer- and noncancer-specific mortality and morbidity in patients who had undergone resection for stage I non–small-cell lung cancer (NSCLC). Patients and Methods Of 5,371 consecutive patients who had undergone curative-intent resection of primary lung cancer at our institution (2000 to 2011), 2,186 with pathologic stage I NSCLC were included in the analysis. All preoperative clinical variables known to affect outcomes were included in the analysis, specifically, Charlson comorbidity index, predicted postoperative (ppo) diffusing capacity of the lung for carbon monoxide, and ppo forced expiratory volume in 1 second. Cause-specific mortality analysis was performed with competing risks analysis. Results Of 2,186 patients, 1,532 (70.1%) were ≥ 65 years of age, including 638 (29.2%) ≥ 75 years of age. In patients < 65, 65 to 74, and ≥ 75 years of age, 5-year lung cancer–specific cumulative incidence of death (CID) was 7.5%, 10.7%, and 13.2%, respectively (overall, 10.4%); noncancer-specific CID was 1.8%, 4.9%, and 9.0%, respectively (overall, 5.3%). In patients ≥ 65 years of age, for up to 2.5 years after resection, noncancer-specific CID was higher than lung cancer–specific CID; the higher noncancer-specific, early-phase mortality was enhanced in patients ≥ 75 years of age than in those 65 to 74 years of age. Multivariable analysis showed that low ppo diffusing capacity of lung for carbon monoxide was an independent predictor of severe morbidity ( P < .001), 1-year mortality ( P < .001), and noncancer-specific mortality ( P < .001), whereas low ppo forced expiratory volume in 1 second was an independent predictor of lung cancer–specific mortality ( P = .002). Conclusion In patients who undergo curative-intent resection of stage I NSCLC, noncancer-specific mortality is a significant competing event, with an increasing impact as patient age increases.

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