Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Benjamin Y. Choo"'
Publikováno v:
International Journal of Prognostics and Health Management, Vol 7, Iss 3 (2016)
The Adaptive Multi-scale Prognostics and Health Management (AM-PHM) is a methodology designed to enable PHM in smart manufacturing systems. In application, PHM information is not yet fully utilized in higher-level decisionmaking in manufacturing syst
Externí odkaz:
https://doaj.org/article/7dc28f9aa33645829a2972a2e6d1ca5d
Publikováno v:
International Journal of Prognostics and Health Management, Vol 7, Iss 3 (2016)
The Adaptive Multi-scale Prognostics and Health Management (AM-PHM) is a methodology designed to enable PHM in smart manufacturing systems. In application, PHM information is not yet fully utilized in higher-level decisionmaking in manufacturing syst
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::419a1cef4becc16c7ef2516d887c8813
https://doi.org/10.36001/ijphm.2016.v7i3.2412
https://doi.org/10.36001/ijphm.2016.v7i3.2412
Publikováno v:
Journal of Manufacturing Systems. 45:82-96
Prognostics and health management (PHM) uses process state information to inform decision making with the goal of improving maintenance activities, performance, safety, and reliability. In this paper, we present a new methodology for (i) targeting ar
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a7d31f1e1abe35764961b731290dca1a
https://doi.org/10.1016/j.jmsy.2017.07.002
https://doi.org/10.1016/j.jmsy.2017.07.002
Publikováno v:
International journal of prognostics and health management
The Adaptive Multi-scale Prognostics and Health Management (AM-PHM) is a methodology designed to enable PHM in smart manufacturing systems. In application, PHM information is not yet fully utilized in higher-level decision-making in manufacturing sys
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::fadd4269ade96c2d2156b9848c747c6d
https://pubmed.ncbi.nlm.nih.gov/28736651
https://pubmed.ncbi.nlm.nih.gov/28736651
Publikováno v:
ICPHM
Manufacturing facilities are laid out in a natural hierarchy of assembly lines, work cells, machines, and components. Currently, prognostics and health management (PHM) information is confined to the lowest levels of this hierarchy and finds primary
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e10532902d4804a5e2da78d16d43378a
https://doi.org/10.1109/icphm.2017.7998303
https://doi.org/10.1109/icphm.2017.7998303
Publikováno v:
IEEE transactions on cybernetics. 46(12)
With the emergence of the Microsoft Kinect sensor, many developer communities and research groups have found countless uses and have already published a wide variety of papers that utilize the raw depth images for their specific goals. New methods an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9c71c63c1339358539512d03dd2375b1
https://pubmed.ncbi.nlm.nih.gov/26584505
https://pubmed.ncbi.nlm.nih.gov/26584505
Publikováno v:
IECON
Noise characteristics for the Microsoft Kinect sensor are presented. Horizontal (x) and vertical (y) stochastic noise are measured using a novel 3D checker board. Results show that the noise is affected mostly by the depth at which the object is sens
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6ad673e93a7134b1ea3a0962c503a678
https://doi.org/10.1109/iecon.2014.7048876
https://doi.org/10.1109/iecon.2014.7048876
Autor:
Stephen Adams, Benjamin Y. Choo, Graham Crannel, Faraz Dadgostari, Peter A. Beling, Roy McIntyre, Ann Bolcavage
Publikováno v:
GND Network
SpringSim
SpringSim
Reinforcement learning (RL) is used for sequential decision making such as operating and maintaining manufacturing systems. In RL, the system is modeled as a Markov decision process with states, actions, rewards, and policies. A policy is learned thr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9e910429dc5a00c59977c0a0c4950084
https://id.culturegraph.org/K10Plus:1747838454
https://id.culturegraph.org/K10Plus:1747838454
