Results from testing of a "cloud based" automated fault detection and diagnosis tool for AHU's. - Ken Bruton; Daniel Coakley; Peter O'Donovan; Marcus M. Keane; Dominic T. J. O'Sullivan (ETFA, 2013)

Implementing the Green Batch: A case study: Continuous statistical evaluation to achieve the most energy efficient and reliable process. - Kevin Leahy 002; Ken Bruton; Dominic O'Sullivan (ETFA, 2014)

Big data in manufacturing: a systematic mapping study. - Peter O'Donovan; Kevin Leahy 002; Ken Bruton; Dominic T. J. O'Sullivan (J. Big Data, 2015)

An industrial big data pipeline for data-driven analytics maintenance applications in large-scale smart manufacturing facilities. - Peter O'Donovan; Kevin Leahy 002; Ken Bruton; Dominic T. J. O'Sullivan (J. Big Data, 2015)

Utilising the Cross Industry Standard Process for Data Mining to Reduce Uncertainty in the Measurement and Verification of Energy Savings. - Colm V. Gallagher; Ken Bruton; Dominic T. J. O'Sullivan (DMBD, 2016)

Development and application of a machine learning supported methodology for measurement and verification (M&V) 2.0. - Colm V. Gallagher; Kevin Leahy 002; Peter O'Donovan; Ken Bruton; Dominic T. J. O'Sullivan (CoRR, 2018)

Industry 4.0 driven statistical analysis of investment casting process demonstrates the value of digitalisation. - Rose Clancy; Ken Bruton; Dominic O'Sullivan; Dermot Keogh (ISM, 2021)

Using Model Selection and Reduction to Develop an Empirical Model to Predict Energy Consumption of a CNC Machine. - Liam Morris; Rose Clancy; Andriy Hryshchenko; Dominic O'Sullivan; Ken Bruton (ISoLA (4), 2022)