| Industrial waste heat recovery: A systematic approach E Woolley, Y Luo, A Simeone Sustainable Energy Technologies and Assessments 29, 50-59, 2018 | 193 | 2018 |
| Multiple sensor monitoring in nickel alloy turning for tool wear assessment via sensor fusion T Segreto, A Simeone, R Teti Procedia CIRP 12, 85-90, 2013 | 85 | 2013 |
| Intelligent cloud manufacturing platform for efficient resource sharing in smart manufacturing networks A Simeone, A Caggiano, L Boun, B Deng Procedia Cirp 79, 233-238, 2019 | 77 | 2019 |
| ANN tool wear modelling in the machining of nickel superalloy industrial products D D’Addona, T Segreto, A Simeone, R Teti CIRP Journal of Manufacturing Science and Technology 4 (1), 33-37, 2011 | 58 | 2011 |
| A decision support system for waste heat recovery in manufacturing A Simeone, Y Luo, E Woolley, S Rahimifard, C Boër CIRP Annals 65 (1), 21-24, 2016 | 57 | 2016 |
| Principal component analysis for feature extraction and NN pattern recognition in sensor monitoring of chip form during turning T Segreto, A Simeone, R Teti CIRP Journal of Manufacturing Science and Technology 7 (3), 202-209, 2014 | 57 | 2014 |
| Sensor fusion for tool state classification in nickel superalloy high performance cutting T Segreto, A Simeone, R Teti Procedia CIRP 1, 593-598, 2012 | 48 | 2012 |
| Intelligent decision-making support system for manufacturing solution recommendation in a cloud framework A Simeone, Y Zeng, A Caggiano The International Journal of Advanced Manufacturing Technology 112 (3), 1035 …, 2021 | 39 | 2021 |
| A coupled electrochemical-mechanical performance evaluation for safety design of lithium-ion batteries in electric vehicles: An integrated cell and system level approach X Niu, A Garg, A Goyal, A Simeone, N Bao, J Zhang, X Peng Journal of cleaner production 222, 633-645, 2019 | 33 | 2019 |
| Chip form classification in carbon steel turning through cutting force measurement and principal component analysis T Segreto, A Simeone, R Teti Procedia Cirp 2, 49-54, 2012 | 31 | 2012 |
| Clean-in-place monitoring of different food fouling materials using ultrasonic measurements J Escrig, E Woolley, S Rangappa, A Simeone, NJ Watson Food Control 104, 358-366, 2019 | 30 | 2019 |
| Product features characterization and customers’ preferences prediction based on purchasing data J Zhang, A Simeone, P Gu, B Hong CIRP Annals 67 (1), 149-152, 2018 | 30 | 2018 |
| Smart cloud manufacturing platform for resource efficiency improvement of additive manufacturing services A Simeone, A Caggiano, Y Zeng Procedia Cirp 88, 387-392, 2020 | 28 | 2020 |
| A multi-sensor approach for fouling level assessment in clean-in-place processes A Simeone, N Watson, I Sterritt, E Woolley Procedia Cirp 55, 134-139, 2016 | 28 | 2016 |
| A multi-sensor system for silkworm cocoon gender classification via image processing and support vector machine AN Joseph Raj, R Sundaram, VGV Mahesh, Z Zhuang, A Simeone Sensors 19 (12), 2656, 2019 | 27 | 2019 |
| Resource efficiency enhancement in sheet metal cutting industrial networks through cloud manufacturing A Simeone, B Deng, A Caggiano The International Journal of Advanced Manufacturing Technology 107 (3), 1345 …, 2020 | 26 | 2020 |
| A material flow modelling tool for resource efficient production planning in multi-product manufacturing systems O Gould, A Simeone, J Colwill, R Willey, S Rahimifard Procedia CIRP 41, 21-26, 2016 | 26 | 2016 |
| Residual stress condition monitoring via sensor fusion in turning of Inconel 718 A Simeone, T Segreto, R Teti Procedia CIRP 12, 67-72, 2013 | 24 | 2013 |
| Residual stress assessment in Inconel 718 machining through wavelet sensor signal analysis and sensor fusion pattern recognition T Segreto, S Karam, A Simeone, R Teti Procedia Cirp 9, 103-108, 2013 | 24 | 2013 |
| Monitoring the cleaning of food fouling in pipes using ultrasonic measurements and machine learning J Escrig, E Woolley, A Simeone, NJ Watson Food Control 116, 107309, 2020 | 22 | 2020 |
Elliot WoolleyLoughborough UniversityVerified email at lboro.ac.uk
