Tool wear monitoring using naive Bayes classifiers J Karandikar, T McLeay, S Turner, T Schmitz The International Journal of Advanced Manufacturing Technology 77, 1613-1626, 2015 | 101 | 2015 |
Using spindle noise to monitor tool wear in a turning process N Seemuang, T McLeay, T Slatter The International Journal of Advanced Manufacturing Technology 86, 2781-2790, 2016 | 76 | 2016 |
A Bayesian framework to estimate part quality and associated uncertainties in multistage manufacturing M Papananias, TE McLeay, M Mahfouf, V Kadirkamanathan computers in industry 105, 35-47, 2019 | 36 | 2019 |
A multivariate control chart for autocorrelated tool wear processes K Harris, K Triantafyllopoulos, E Stillman, T McLeay Quality and Reliability Engineering International 32 (6), 2093-2106, 2016 | 26 | 2016 |
Inspection by exception: A new machine learning-based approach for multistage manufacturing M Papananias, TE McLeay, O Obajemu, M Mahfouf, V Kadirkamanathan Applied Soft Computing 97, 106787, 2020 | 21 | 2020 |
An intelligent metrology informatics system based on neural networks for multistage manufacturing processes M Papananias, TE McLeay, M Mahfouf, V Kadirkamanathan Procedia CIRP 82, 444-449, 2019 | 18 | 2019 |
A novel approach to machining process fault detection using unsupervised learning T McLeay, MS Turner, K Worden Proceedings of the Institution of Mechanical Engineers, Part B: Journal of …, 2021 | 13 | 2021 |
Online damage detection of cutting tools using Dirichlet process mixture models CT Wickramarachchi, TJ Rogers, TE McLeay, W Leahy, EJ Cross Mechanical Systems and Signal Processing 180, 109434, 2022 | 9 | 2022 |
A two-step machining and active learning approach for right-first-time robotic countersinking through in-process error compensation and prediction of depth of cuts M Leco, T McLeay, V Kadirkamanathan Robotics and Computer-Integrated Manufacturing 77, 102345, 2022 | 9 | 2022 |
A Bayesian information fusion approach for end product quality estimation using machine learning and on-machine probing M Papananias, TE McLeay, M Mahfouf, V Kadirkamanathan Journal of Manufacturing Processes 76, 475-485, 2022 | 9 | 2022 |
Failure mode analysis to define process monitoring systems T Mcleay, MS Turner Journal of machine engineering 11 (4), 118--129, 2011 | 9 | 2011 |
Remaining useful tool life predictions using Bayesian inference J Karandikar, T McLeay, S Turner, T Schmitz International Manufacturing Science and Engineering Conference 55461 …, 2013 | 7 | 2013 |
Machining distortion in asymmetrical residual stress profiles R Bilkhu, S Ayvar-Soberanis, C Pinna, T McLeay Procedia CIRP 82, 395-399, 2019 | 6 | 2019 |
Tool wear inspection of polycrystalline cubic boron nitride inserts C Wickramarachchi, TE McLeay, S Ayvar-Soberanis, W Leahy, EJ Cross Special Topics in Structural Dynamics, Volume 5: Proceedings of the 36th …, 2019 | 6 | 2019 |
Development of a new machine learning-based informatics system for product health monitoring M Papananias, O Obajemu, TE McLeay, M Mahfouf, V Kadirkamanathan Procedia CIRP 93, 473-478, 2020 | 5 | 2020 |
A probabilistic framework for online structural health monitoring: active learning from machining data streams LA Bull, K Worden, TJ Rogers, C Wickramarachchi, EJ Cross, T McLeay, ... Journal of Physics: Conference Series 1264 (1), 012028, 2019 | 5 | 2019 |
Unsupervised monitoring of machining processes TE McLeay University of Sheffield, 2016 | 5 | 2016 |
A probabilistic framework for product health monitoring in multistage manufacturing using Unsupervised Artificial Neural Networks and Gaussian Processes M Papananias, TE McLeay, M Mahfouf, V Kadirkamanathan Proceedings of the Institution of Mechanical Engineers, Part B: Journal of …, 2023 | 4 | 2023 |
An interpretable machine learning based approach for process to areal surface metrology informatics O Obajemu, M Mahfouf, M Papananias, TE McLeay, V Kadirkamanathan Surface Topography: Metrology and Properties 9 (4), 044001, 2021 | 4 | 2021 |
Work holding assessment of an UV adhesive and fixture design method S Yao, E Ozturk, D Curtis, T McLeay The International Journal of Advanced Manufacturing Technology 106, 741-752, 2020 | 4 | 2020 |