Michael Farnsworth
Michael Farnsworth
Research Associate, Sheffield University
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Zitiert von
Zitiert von
A review of optimisation techniques used in the composite recycling area: State-of-the-art and steps towards a research agenda
Y Liu, M Farnsworth, A Tiwari
Journal of Cleaner Production 140, 1775-1781, 2017
On the requirements of digital twin-driven autonomous maintenance
S Khan, M Farnsworth, R McWilliam, J Erkoyuncu
Annual Reviews in Control 50, 13-28, 2020
Applying a 6 DoF robotic arm and digital twin to automate fan-blade reconditioning for aerospace maintenance, repair, and overhaul
J Oyekan, M Farnsworth, W Hutabarat, D Miller, A Tiwari
Sensors 20 (16), 4637, 2020
Designing an AR interface to improve trust in Human-Robots collaboration
R Palmarini, IF del Amo, G Bertolino, G Dini, JA Erkoyuncu, R Roy, ...
Procedia CIRP 70, 350-355, 2018
Capturing, classification and concept generation for automated maintenance tasks
M Farnsworth, T Tomiyama
CIRP Annals 63 (1), 149-152, 2014
Modelling, simulation and optimisation of a piezoelectric energy harvester
M Farnsworth, A Tiwari, R Dorey
Procedia CIRP 22, 142-147, 2014
Design and optimisation of microelectromechanical systems: a review of the state-of-the-art
E Benkhelifa, M Farnsworth, A Tiwari, G Bandi, M Zhu
International Journal of Design Engineering 3 (1), 41-76, 2010
In-process monitoring in electrical machine manufacturing: A review of state of the art and future directions
D Tiwari, M Farnsworth, Z Zhang, GW Jewell, A Tiwari
Proceedings of the Institution of Mechanical Engineers, Part B: Journal of …, 2021
Autonomous maintenance for through-life engineering
M Farnsworth, C Bell, S Khan, T Tomiyama
Through-life Engineering Services: Motivation, Theory, and Practice, 395-419, 2015
Energy-efficient scheduling of flexible flow shop of composite recycling
Y Liu, M Farnsworth, A Tiwari
The International Journal of Advanced Manufacturing Technology 97, 117-127, 2018
An efficient evolutionary multi-objective framework for MEMS design optimisation: validation, comparison and analysis
M Farnsworth, E Benkhelifa, A Tiwari, M Zhu, M Moniri
Memetic Computing 3, 175-197, 2011
Zero-maintenance of electronic systems: Perspectives, challenges, and opportunities
R McWilliam, S Khan, M Farnsworth, C Bell
Microelectronics Reliability 85, 122-139, 2018
Maintenance task classification: towards automated robotic maintenance for industry
H Akrout, D Anson, G Bianchini, A Neveur, C Trinel, M Farnsworth, ...
Procedia Cirp 11, 367-372, 2013
Multi-level and multi-objective design optimisation of a MEMS bandpass filter
M Farnsworth, A Tiwari, M Zhu
Applied Soft Computing 52, 642-656, 2017
A review of digital wayfinding technologies in the transportation industry
S Peña Miñano, L Kirkwood, M Farnsworth, I Orlovs, E Shehab, ...
Advances in Manufacturing Technology XXXI, 207-212, 2017
Modelling, simulation and analysis of a self-healing energy harvester
M Farnsworth, A Tiwari
Procedia CIRP 38, 271-276, 2015
Deep transfer learning with self-attention for industry sensor fusion tasks
Z Zhang, M Farnsworth, B Song, D Tiwari, A Tiwari
IEEE Sensors Journal 22 (15), 15235-15247, 2022
New threats for old manufacturing problems: Secure IoT-Enabled monitoring of legacy production machinery
S Tedeschi, C Emmanouilidis, M Farnsworth, J Mehnen, R Roy
Advances in Production Management Systems. The Path to Intelligent …, 2017
A Novel Approach to Multi-level Evolutionary Design Optimization of a MEMS Device
M Farnsworth, E Benkhelifa, A Tiwari, M Zhu
Evolvable Systems: From Biology to Hardware, 322-334, 2010
A novel approach for No Fault Found decision-making
S Khan, M Farnsworth, J Erkoyuncu
CIRP Journal of Manufacturing Science and Technology 17, 18-31, 2017
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