@Article{crph917,
AUTHOR = {Mandala, Vishwanadham},
TITLE = {Predictive Failure Analytics in Critical Automotive Applications: Enhancing Reliability and Safety through Advanced AI Techniques},
JOURNAL = {Current Research in Public Health},
VOLUME = {3},
YEAR = {2023},
NUMBER = {1},
PAGES = {4-16},
URL = {https://www.scipublications.com/journal/index.php/JAIBD/article/view/917},
ISSN = {2831-5162},
DOI = {10.31586/jaibd.2024.917},
ABSTRACT = {Failure prediction can be achieved through prognostics, which provides timely warnings before failure. Failure prediction is crucial in an effective prognostic system, allowing preventive maintenance actions to avoid downtime. The prognostics problem involves estimating the remaining useful life (RUL) of a system or component at any given time. The RUL is defined as the time from the current time to the time of failure. The goal is to make accurate predictions close to the failure time to provide early warnings. J S Grewal and J. Grewal provide a comprehensive definition of RUL in their paper "The Kalman Filter approach to RUL estimation." A process is a quadruple (XU f P), where X is the state space, U is the control space, P is the set of possible paths, and f represents the transition between states. The process involves applying control values to change the system's state over time.},
}

%0 Journal Article
%A Mandala, Vishwanadham
%D 2023
%J Current Research in Public Health

%@ 2831-5162
%V 3
%N 1
%P 4-16

%T Predictive Failure Analytics in Critical Automotive Applications: Enhancing Reliability and Safety through Advanced AI Techniques
%M doi:10.31586/jaibd.2024.917
%U https://www.scipublications.com/journal/index.php/JAIBD/article/view/917

TY  - JOUR
AU  - Mandala, Vishwanadham
TI  - Predictive Failure Analytics in Critical Automotive Applications: Enhancing Reliability and Safety through Advanced AI Techniques
T2  - Current Research in Public Health
PY  - 2023
VL  - 3
IS  - 1
SN  - 2831-5162
SP  - 4
EP  - 16
UR  - https://www.scipublications.com/journal/index.php/JAIBD/article/view/917
AB  - Failure prediction can be achieved through prognostics, which provides timely warnings before failure. Failure prediction is crucial in an effective prognostic system, allowing preventive maintenance actions to avoid downtime. The prognostics problem involves estimating the remaining useful life (RUL) of a system or component at any given time. The RUL is defined as the time from the current time to the time of failure. The goal is to make accurate predictions close to the failure time to provide early warnings. J S Grewal and J. Grewal provide a comprehensive definition of RUL in their paper "The Kalman Filter approach to RUL estimation." A process is a quadruple (XU f P), where X is the state space, U is the control space, P is the set of possible paths, and f represents the transition between states. The process involves applying control values to change the system's state over time.
DO  - Predictive Failure Analytics in Critical Automotive Applications: Enhancing Reliability and Safety through Advanced AI Techniques
TI  - 10.31586/jaibd.2024.917
ER  -