Predictive Maintenance Estimation of Aircraft Health with Survival Analysis

2022 ◽  
pp. 416-426
Author(s):  
Jiaojiao Gu ◽  
Ke Liu ◽  
Jian Chen ◽  
Tao Sun
Keyword(s):  
Survival Analysis ◽  
Predictive Maintenance

scholarly journals Identification of Bridge Key Performance Indicators Using Survival Analysis for Future Network-Wide Structural Health Monitoring

Sensors ◽  
2020 ◽  
Vol 20 (23) ◽  
pp. 6894
Author(s):  
Nicola-Ann Stevens ◽  
Myra Lydon ◽  
Adele H. Marshall ◽  
Su Taylor
Keyword(s):  
Survival Analysis ◽  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Performance Indicators ◽  
Key Performance Indicators ◽  
Predictive Maintenance ◽  
Sensor Data ◽  
Transport Networks ◽  
Data Set ◽  
Structural Health

Machine learning and statistical approaches have transformed the management of infrastructure systems such as water, energy and modern transport networks. Artificial Intelligence-based solutions allow asset owners to predict future performance and optimize maintenance routines through the use of historic performance and real-time sensor data. The industrial adoption of such methods has been limited in the management of bridges within aging transport networks. Predictive maintenance at bridge network level is particularly complex due to the considerable level of heterogeneity encompassed across various bridge types and functions. This paper reviews some of the main approaches in bridge predictive maintenance modeling and outlines the challenges in their adaptation to the future network-wide management of bridges. Survival analysis techniques have been successfully applied to predict outcomes from a homogenous data set, such as bridge deck condition. This paper considers the complexities of European road networks in terms of bridge type, function and age to present a novel application of survival analysis based on sparse data obtained from visual inspections. This research is focused on analyzing existing inspection information to establish data foundations, which will pave the way for big data utilization, and inform on key performance indicators for future network-wide structural health monitoring.

The Survival Analysis for a Predictive Maintenance in Manufacturing

2021 ◽  
pp. 78-85
Author(s):  
Bahrudin Hrnjica ◽  
Selver Softic
Keyword(s):  
Survival Analysis ◽  
Predictive Maintenance

Risk for psychotherapy drop-out in survival analysis: The influence of general change mechanisms and symptom severity.

2020 ◽  
Vol 67 (6) ◽  
pp. 712-722
Author(s):  
Sebastian Gmeinwieser ◽  
Kai Sebastian Schneider ◽  
Maximilian Bardo ◽  
Timo Brockmeyer ◽  
York Hagmayer
Keyword(s):  
Survival Analysis ◽  
Symptom Severity ◽  
Drop Out ◽  
General Change ◽  
Change Mechanisms

Five-year Survival Analysis of a Cohort of Hepatocellular Carcinoma Patients Who Treated at the National Cancer Center, Korea

2007 ◽  
Vol 13 (4) ◽  
pp. 530 ◽  
Author(s):  
Kyung Woo Park ◽  
Joong-Won Park ◽  
Tae Hyun Kim ◽  
Jun Il Choi ◽  
Seong Hoon Kim ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Survival Analysis ◽  
Cancer Center

The Convergence between Predictive Maintenance and Augmented Reality to Aid Renewable Energy Equipment Availability

2014 ◽  
Vol 2 (5) ◽  
pp. 152
Author(s):  
José Manuel Torres Farinha ◽  
Inácio Adelino Fonseca ◽  
Rúben Silva Oliveira ◽  
Fernando Maciel Barbosa
Keyword(s):  
Renewable Energy ◽  
Augmented Reality ◽  
Predictive Maintenance ◽  
Equipment Availability ◽  
Energy Equipment
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