Peter O'Donovan
Peter O'Donovan
Director, PepsiCo Global R&D
Verified email at - Homepage
Cited by
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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
Big data in manufacturing: a systematic mapping study
P O'Donovan, K Leahy, K Bruton, DTJ O'Sullivan
Journal of Big Data, 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, 2018
A comparison of fog and cloud computing cyber-physical interfaces for Industry 4.0 real-time embedded machine learning engineering applications
P O’Donovan, C Gallagher, K Leahy, DTJ O’Sullivan
Computers in Industry 110, 12-35, 2019
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
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
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
Issues with Data Quality for Wind Turbine Condition Monitoring and Reliability Analyses
K Leahy, C Gallagher, P O'Donovan, DTJ O'Sullivan
Energies, 2019
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, 21, 2016
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
IAMM: A Maturity Model for Measuring Industrial Analytics Capabilities in Large-scale Manufacturing Facilities
P O'Donovan, K Bruton, DTJ O'Sullivan
Internation Journal of Prognostics and Health Management 7, 11, 2016
A Systematic Analysis of Real-World Energy Blockchain Initiatives
P O'Donovan, DTJ O'Sullivan
Future Internet 11 (174), 2019
IntelliMaV: A cloud computing measurement and verification 2.0 application for automated, near real-time energy savings quantification and performance deviation detection
CV Gallagher, K Leahy, P O’Donovan, K Bruton, DTJ O’Sullivan
Energy and buildings 185, 26-38, 2019
Cluster analysis of wind turbine alarms for characterising and classifying stoppages
K Leahy, C Gallagher, P O'Donovan, DTJ O'Sullivan
IET Renewable Power Generation 12 (10), 1146-1154, 2018
A cloud-based distributed data collection system for decentralised wastewater treatment plants
P O’Donovan, D Coburn, E Jones, L Hannon, M Glavin, D Mullins, ...
Procedia Engineering 119, 464-469, 2015
Enabling effective operational decision making on a combined heat and power system using the 5C architecture
K Bruton, BP Walsh, D óg Cusack, P O’Donovan, DTJ O'Sullivan
Procedia CIRP 55, 296-301, 2016
Design and development of a software tool to assist ISO 50001 implementation in the manufacturing sector
K Bruton, P O’Donovan, A McGregor, DDTJ O’Sullivan
Proceedings of the Institution of Mechanical Engineers, Part B: Journal of …, 2018
A data pipeline for PHM data-driven analytics in large-scale smart manufacturing facilities
P O’Donovan, K Leahy, D Cusack, K Bruton, DTJ O’Sullivan
Annual Conference of the Prognostics and Health Management Society, 2015
Waternomics: a cross-site data collection to support the development of a water information platform
P O’Donovan, D Coakley, J Mink, E Curry, E Clifford
Procedia Engineering 119, 458-463, 2015
Development of an Online Expert Rule based Automated Fault Detection and Diagnostic (AFDD) tool for Air Handling Units: Beta Test Results
K Bruton, D Coakley, P O'Donovan, M Keane, D O'Sullivan
Energy Systems Laboratory (http://esl. tamu. edu), 2013
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