Cinzia Giannetti

22 papers B 2C 4Journal 12Unranked 4
YearRankTypeTitle / Venue / Authors
2025 J jnl
Real-time monitoring of molten zinc splatter using machine learning-based computer vision.
J. Intell. Manuf.
Callum O'Donovan, Cinzia Giannetti, Cameron Pleydell-Pearce
2024 — conf
Leveraging Machine Learning Insights at the Hot Strip Rolling Mill, Tata Steel, Port Talbot.
I2MTC
Robert Gibbs, Cinzia Giannetti, Thomas Baynes, Cameron Pleydell-Pearce
2023 B conf
A Hybrid Modelling Approach Based on Deep Learning for the Prediction of the Silicon Content in the Blast Furnace.
KES
Kayal Lakshmanan, Aurash Karimi, Alex Carr, Philippe Wauters, Michael Auinger, Cameron Pleydell-Pearce, Cinzia Giannetti
2023 J jnl
A Tool to Combine Expert Knowledge and Machine Learning for Defect Detection and Root Cause Analysis in a Hot Strip Mill.
SN Comput. Sci.
Samuel Latham, Cinzia Giannetti
2023 C conf
Revolutionising the Sustainability of Steel Manufacturing Using Computer Vision.
ISM
Callum O'Donovan, Cinzia Giannetti, Cameron Pleydell-Pearce
2022 J jnl
Comparison of a Bat and Genetic Algorithm Generated Sequence Against Lead Through Programming When Assembling a PCB Using a Six-Axis Robot With Multiple Motions and Speeds.
IEEE Trans. Ind. Informatics
Christian Andrew Griffiths, Cinzia Giannetti, Kamil T. Andrzejewski, Adam Morgan
2022 B conf
Data modelling and Remaining Useful Life estimation of rolls in a steel making cold rolling process.
KES
Kayal Lakshmanan, Eugenio Borghini, Arnold Beckmann, Cameron Pleydell-Pearce, Cinzia Giannetti
2022 J jnl
KSPMI: A Knowledge-based System for Predictive Maintenance in Industry 4.0.
Robotics Comput. Integr. Manuf.
Qiushi Cao, Cecilia Zanni-Merk, Ahmed Samet, Christoph Reich, François de Bertrand de Beuvron, Arnold Beckmann, Cinzia Giannetti
2022 — conf
Root Cause Classification of Temperature-related Failure Modes in a Hot Strip Mill.
IN4PL
Samuel Latham, Cinzia Giannetti
2022 J jnl
Towards scalable and reusable predictive models for cyber twins in manufacturing systems.
J. Intell. Manuf.
Cinzia Giannetti, Aniekan Essien
2021 — conf
A Novel Deep Learning Power Quality Disturbance Classification Method using Autoencoders.
ICAART (2)
Callum O'Donovan, Cinzia Giannetti, Grazia Todeschini
2021 C conf
Making Green Transport a Reality: A Classification Based Data Analysis Method to Identify Properties Suitable for Electric Vehicle Charging Point Installation.
IGARSS
James Flynn, Eleanor Brealy, Cinzia Giannetti
2020 J jnl
A Deep Learning Model for Smart Manufacturing Using Convolutional LSTM Neural Network Autoencoders.
IEEE Trans. Ind. Informatics
Aniekan Essien, Cinzia Giannetti
2019 C conf
A Deep Learning Framework for Univariate Time Series Prediction Using Convolutional LSTM Stacked Autoencoders.
INISTA
Aniekan Essien, Cinzia Giannetti
2019 — conf
A Scalable Deep Convolutional LSTM Neural Network for Large-Scale Urban Traffic Flow Prediction using Recurrence Plots.
AFRICON
Aniekan Essien, Godwin Chukwkelu, Cinzia Giannetti
2019 J jnl
Segmentation and generalisation for writing skills transfer from humans to robots.
Cogn. Comput. Syst.
Chunxu Li, Chenguang Yang, Cinzia Giannetti
2017 C conf
A framework for improving process robustness with quantification of uncertainties in Industry 4.0.
INISTA
Cinzia Giannetti
2016 J jnl
A quality correlation algorithm for tolerance synthesis in manufacturing operations.
Comput. Ind. Eng.
Rajesh S. Ransing, Raed S. Batbooti, Cinzia Giannetti, Meghana R. Ransing
2016 J jnl
Risk based uncertainty quantification to improve robustness of manufacturing operations.
Comput. Ind. Eng.
Cinzia Giannetti, Rajesh S. Ransing
2015 J jnl
Organisational Knowledge Management for Defect Reduction and Sustainable Development in Foundries.
Int. J. Knowl. Syst. Sci.
Cinzia Giannetti, Meghana R. Ransing, Rajesh S. Ransing, David C. Bould, David T. Gethin, Johann Sienz
2014 J jnl
A novel variable selection approach based on co-linearity index to discover optimal process settings by analysing mixed data.
Comput. Ind. Eng.
Cinzia Giannetti, Rajesh S. Ransing, Meghana R. Ransing, David C. Bould, David T. Gethin, Johann Sienz
2013 J jnl
A coupled penalty matrix approach and principal component based co-linearity index technique to discover product specific foundry process knowledge from in-process data in order to reduce defects.
Comput. Ind.
Rajesh S. Ransing, Cinzia Giannetti, Meghana R. Ransing, M. W. James