Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Dominic, T.J. O'Sullivan"'
Publikováno v:
In Energy 1 November 2024 308
Publikováno v:
Data in Brief, Vol 48, Iss , Pp 109208- (2023)
This dataset was collected for the purpose of applying fault detection and diagnosis (FDD) techniques to real data from an industrial facility. The data for an air handling unit (AHU) is extracted from a building management system (BMS) and aligned w
Externí odkaz:
https://doaj.org/article/cf26858be4734842a31904455736aed5
Publikováno v:
International Journal of Prognostics and Health Management, Vol 10, Iss 1 (2019)
Wind turbines generate a wealth of data which can be effectively used to improve maintenance strategies and drive down operations and maintenance ( O & M ) costs, which account for 20-25 % of the cost of generation of wind energy. Data-driven techniq
Externí odkaz:
https://doaj.org/article/2940dddba94a473f8ea01cf5e96cfdf9
Publikováno v:
International Journal of Lean Six Sigma.
Purpose Quality management practitioners have yet to cease the potential of digitalisation. Furthermore, there is a lack of tools such as frameworks guiding practitioners in the digital transformation of their organisations. The purpose of this study
Energy efficient ventilation and indoor air quality in the context of COVID-19 - A systematic review
Autor:
Talie T. Moghadam, Carlos E. Ochoa Morales, Maria J. Lopez Zambrano, Ken Bruton, Dominic T.J. O'Sullivan
Publikováno v:
Renewable and Sustainable Energy Reviews. 182:113356
Publikováno v:
International Journal of Prognostics and Health Management, Vol 7, Iss 4 (2016)
Industrial big data analytics is an emerging multidisciplinary field, which incorporates aspects of engineering, statistics and computing, to produce data-driven insights that can enhance operational efficiencies, and produce knowledgebased competiti
Externí odkaz:
https://doaj.org/article/30436abe813a4bddb5af7df682517de6
Publikováno v:
International Journal of Prognostics and Health Management, Vol 7, Iss 3 (2016)
Integrated, real-time and open approaches relating to the development of industrial analytics capabilities are needed to support smart manufacturing. However, adopting industrial analytics can be challenging due to its multidisciplinary and cross-dep
Externí odkaz:
https://doaj.org/article/3b5053e883804164954bd714519f7a5e
Autor:
S M Shahnewaz Siddiquee, Kofi Afrifa Agyeman, Ken Bruton, Bianca Howard, Dominic T.J. O'Sullivan
Publikováno v:
2022 IEEE Texas Power and Energy Conference (TPEC).
Publikováno v:
Journal of Physics: Conference Series; 2017, Vol. 926 Issue 1, p1-1, 1p