An industrial big data pipeline for data-driven analytics maintenance applications in large-scale smart manufacturing facilities P O’Donovan, K Leahy, K Bruton, DTJ O’Sullivan Journal of big data 2, 1-26, 2015 | 403 | 2015 |
Big data in manufacturing: a systematic mapping study P O’donovan, K Leahy, K Bruton, DTJ O’Sullivan Journal of Big Data 2, 1-22, 2015 | 284 | 2015 |
A fog computing industrial cyber-physical system for embedded low-latency machine learning Industry 4.0 applications P O'donovan, C Gallagher, K Bruton, DTJ O'Sullivan Manufacturing letters 15, 139-142, 2018 | 174 | 2018 |
Review of automated fault detection and diagnostic tools in air handling units K Bruton, P Raftery, B Kennedy, MM Keane, DTJ O’sullivan Energy efficiency 7, 335-351, 2014 | 108 | 2014 |
A systematic mapping of the advancing use of machine learning techniques for predictive maintenance in the manufacturing sector M Nacchia, F Fruggiero, A Lambiase, K Bruton Applied Sciences 11 (6), 2546, 2021 | 88 | 2021 |
Development and alpha testing of a cloud based automated fault detection and diagnosis tool for Air Handling Units K Bruton, P Raftery, P O'Donovan, N Aughney, MM Keane, DTJ O'Sullivan Automation in Construction 39, 70-83, 2014 | 80 | 2014 |
A robust prescriptive framework and performance metric for diagnosing and predicting wind turbine faults based on SCADA and alarms data with case study K Leahy, C Gallagher, P O’Donovan, K Bruton, DTJ O’Sullivan Energies 11 (7), 1738, 2018 | 68 | 2018 |
The suitability of machine learning to minimise uncertainty in the measurement and verification of energy savings CV Gallagher, K Bruton, K Leahy, DTJ O’Sullivan Energy and Buildings 158, 647-655, 2018 | 66 | 2018 |
Comparative analysis of the AHU InFO fault detection and diagnostic expert tool for AHUs with APAR K Bruton, D Coakley, P Raftery, DO Cusack, MM Keane, DTJ O’sullivan Energy Efficiency 8, 299-322, 2015 | 62 | 2015 |
Development and application of a machine learning supported methodology for measurement and verification (M&V) 2.0 CV Gallagher, K Leahy, P O’Donovan, K Bruton, DTJ O’Sullivan Energy and Buildings 167, 8-22, 2018 | 60 | 2018 |
Data-driven quality improvement approach to reducing waste in manufacturing R Clancy, D O'Sullivan, K Bruton The TQM Journal 35 (1), 51-72, 2023 | 49 | 2023 |
Progress in demand response and it’s industrial applications SMS Siddiquee, B Howard, K Bruton, A Brem, DTJ O'Sullivan Frontiers in Energy Research 9, 673176, 2021 | 46 | 2021 |
Automatically identifying and predicting unplanned wind turbine stoppages using scada and alarms system data: Case study and results K Leahy, C Gallagher, K Bruton, P O’Donovan, DTJ O’Sullivan Journal of Physics: Conference Series 926 (1), 012011, 2017 | 42 | 2017 |
A case-study in the introduction of a digital twin in a large-scale smart manufacturing facility J O’Sullivan, D O’Sullivan, K Bruton Procedia Manufacturing 51, 1523-1530, 2020 | 40 | 2020 |
Case study: the implementation of a data-driven industrial analytics methodology and platform for smart manufacturing P O’Donovan, K Bruton, DTJ O’Sullivan International Journal of Prognostics and Health Management 7 (3), 2016 | 40 | 2016 |
IAMM: A maturity model for measuring industrial analytics capabilities in large-scale manufacturing facilities P O'Donovan, K Bruton, DTJ O'Sullivan PHM Society, 2016 | 40 | 2016 |
Energy efficient ventilation and indoor air quality in the context of COVID-19-A systematic review TT Moghadam, CEO Morales, MJL Zambrano, K Bruton, DTJ O'Sullivan Renewable and Sustainable Energy Reviews, 113356, 2023 | 38 | 2023 |
How do companies certified to ISO 50001 and ISO 14001 perform in LEED and BREEAM assessments? A Brem, DÓ Cusack, MM Adrita, DTJ O’Sullivan, K Bruton Energy efficiency 13, 751-766, 2020 | 36 | 2020 |
Industrial smart and micro grid systems–A systematic mapping study A Brem, MM Adrita, DTJ O’Sullivan, K Bruton Journal of Cleaner Production 244, 118828, 2020 | 36 | 2020 |
The true value of water: A case-study in manufacturing process water-management BP Walsh, K Bruton, DTJ O'Sullivan Journal of cleaner production 141, 551-567, 2017 | 28 | 2017 |