Journal Articles
Shahid, Z, Beckmann, A, Sylla, A, Alpan, G,
Giannetti, C (2026)
Exploring the application of statistical and symbolic AI in supply chain risk management: a systematic literature review,
International Journal of Production Research, ISSN: 0020-7543. DOI:
10.1080/00207543.2026.2737934.
Reaney, IM, Jouhara, H, Reece, MJ, Koh, SCL, Button, CA,
Giannetti, C, Khesro, A, Vaidhyanathan, V (2026)
Sustainability and decarbonisation in the ceramics sector through resource and energy efficiency,
Journal of Materials Research, 41(14), ISSN: 0884-2914. DOI:
10.1557/s43578-026-01920-8.
O’Donovan, C,
Giannetti, C, Pleydell-Pearce, C (2025)
Real-time monitoring of molten zinc splatter using machine learning-based computer vision,
Journal of Intelligent Manufacturing, 36(5), pp.3399-3425, ISSN: 0956-5515. DOI:
10.1007/s10845-024-02418-y.
Giannetti, C, Borghini, E, Carr, A, Raleigh, J, Rackham, B (2025)
Deep learning for robust forecasting of hot metal silicon content in a blast furnace,
The International Journal of Advanced Manufacturing Technology, 136(9), pp.4045-4054, ISSN: 0268-3768. DOI:
10.1007/s00170-024-13214-6.
Beden, S, Lakshmanan, K,
Giannetti, C, Beckmann, A (2023)
Steelmaking Predictive Analytics Based on Random Forest and Semantic Reasoning,
Applied Sciences, 13(23), pp.12778-12778, DOI:
10.3390/app132312778.
Latham, S and
Giannetti, C (2023)
A Tool to Combine Expert Knowledge and Machine Learning for Defect Detection and Root Cause Analysis in a Hot Strip Mill,
SN Computer Science, 4(5), ISSN: 2662-995X. DOI:
10.1007/s42979-023-02104-5.
Lakshmanan, K, Roach, M,
Giannetti, C, Bhoite, S, George, D, Mortensen, T, Manduhu, M, Heravi, B, Kariyawasam, S, Xie, X (2023)
A Robust Vehicle Detection Model for LiDAR Sensor Using Simulation Data and Transfer Learning Methods,
AI, 4(2), pp.461-481, DOI:
10.3390/ai4020025.
O’Donovan, C, Popov, I, Todeschini, G,
Giannetti, C (2023)
Ladle pouring process parameter and quality estimation using Mask R-CNN and contrast-limited adaptive histogram equalisation,
International Journal of Advanced Manufacturing Technology, 126(3-4), pp.1397-1416, ISSN: 0268-3768. DOI:
10.1007/s00170-023-11151-4.
Flynn, JS,
Giannetti, C, Van Dijk, H (2023)
Anomaly Detection of DC Nut Runner Processes in Engine Assembly,
AI, 4(1), pp.234-254, DOI:
10.3390/ai4010010.
Todeschini, G, Kheta, K,
Giannetti, C (2022)
An image-based deep transfer learning approach to classify power quality disturbances,
Electric Power Systems Research, 213, ISSN: 0378-7796. DOI:
10.1016/j.epsr.2022.108795.
Cao, Q, Zanni-Merk, C, Samet, A, Reich, C, Beuvron, FDBD, Beckmann, A,
Giannetti, C (2022)
KSPMI: A Knowledge-based System for Predictive Maintenance in Industry 4.0,
Robotics and Computer Integrated Manufacturing, 74, ISSN: 0736-5845. DOI:
10.1016/j.rcim.2021.102281.
Griffiths, C,
Giannetti, C, Andrzejewski, K, Morgan, A (2022)
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 Transactions on Industrial Informatics, 18(2), pp.1102-1110, ISSN: 1551-3203. DOI:
10.1109/tii.2021.3082877.
Giannetti, C and Essien, A (2022)
Towards scalable and reusable predictive models for cyber twins in manufacturing systems,
Journal of Intelligent Manufacturing, 33(2), pp.441-455, ISSN: 0956-5515. DOI:
10.1007/s10845-021-01804-0.
Borghini, E,
Giannetti, C, Flynn, J, Todeschini, G (2021)
Data-Driven Energy Storage Scheduling to Minimise Peak Demand on Distribution Systems with PV Generation,
Energies, 14(12), pp.3453-3453, DOI:
10.3390/en14123453.
Flynn, J and
Giannetti, C (2021)
Using Convolutional Neural Networks to Map Houses Suitable for Electric Vehicle Home Charging,
AI, 2(1), pp.135-149, DOI:
10.3390/ai2010009.
Aldoumani, N,
Giannetti, C, Abdallah, Z, Belblidia, F, Khodaparast, HH, Friswell, MI, Sienz, J (2020)
Optimisation of the Filament Winding Approach Using a Newly Developed In-House Uncertainty Model,
Eng, 1(2), DOI:
10.3390/eng1020008.
Essien, A and
Giannetti, C (2020)
A Deep Learning Model for Smart Manufacturing Using Convolutional LSTM Neural Network Autoencoders,
IEEE Transactions on Industrial Informatics, 16(9), pp.6069-6078, ISSN: 1551-3203. DOI:
10.1109/tii.2020.2967556.
Cooper, MP, Griffiths, CA, Andrzejewski, KT,
Giannetti, C (2019)
Motion optimisation for improved cycle time and reduced vibration in robotic assembly of electronic components,
Aims Electronics and Electrical Engineering, 3(3), pp.274-289, DOI:
10.3934/ElectrEng.2019.3.274.
Giannetti, C, Lucini, B, Vadacchino, D (2019)
Machine Learning as a universal tool for quantitative investigations of phase transitions,
Nuclear Physics B, 944, ISSN: 0550-3213. DOI:
10.1016/j.nuclphysb.2019.114639.
Li, C, Yang, C,
Giannetti, C (2019)
Segmentation and generalisation for writing skills transfer from humans to robots,
Cognitive Computation and Systems, 1(1), pp.20-25, DOI:
10.1049/ccs.2018.0005.
Andrzejewski, KT, Cooper, MP, Griffiths, CA,
Giannetti, C (2018)
Optimisation process for robotic assembly of electronic components,
International Journal of Advanced Manufacturing Technology, 99(9-12), pp.2523-2535, ISSN: 0268-3768. DOI:
10.1007/s00170-018-2645-y.
Aldoumani, N, Haddad Khodaparast, H,
Giannetti, C, Abdallah, Z, Cameron, IM, Friswell, MI, Sienz, J (2018)
A robust design of an innovative shaped rebar system using a novel uncertainty model,
Structural and Multidisciplinary Optimization, 58(4), pp.1351-1365, ISSN: 1615-147X. DOI:
10.1007/s00158-018-2050-z.
Giannetti, C and Ransing, RS (2016)
Risk based uncertainty quantification to improve robustness of manufacturing operations,
Computers and Industrial Engineering, 101, pp.70-80, ISSN: 0360-8352. DOI:
10.1016/j.cie.2016.08.002.
Ransing, RS, Batbooti, RS,
Giannetti, C, Ransing, MR (2016)
A quality correlation algorithm for tolerance synthesis in manufacturing operations,
Computers and Industrial Engineering, 93, pp.1-11, ISSN: 0360-8352. DOI:
10.1016/j.cie.2015.12.008.
Giannetti, C, Ransing, MR, Ransing, RS, Bould, DC, Gethin, DT, Sienz, J (2015)
Organisational Knowledge Management for Defect Reduction and Sustainable Development in Foundries,
International Journal of Knowledge and Systems Science, 6(3), pp.18-37, ISSN: 1947-8208. DOI:
10.4018/ijkss.2015070102.
Giannetti, C, Ransing, RS, Ransing, MR, Bould, DC, Gethin, DT, Sienz, J (2014)
A novel variable selection approach based on co-linearity index to discover optimal process settings by analysing mixed data,
Computers and Industrial Engineering, 72(1), pp.217-229, ISSN: 0360-8352. DOI:
10.1016/j.cie.2014.03.017.
Ransing, RS,
Giannetti, C, Ransing, MR, James, MW (2013)
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,
Computers in Industry, 64(5), pp.514-523, ISSN: 0166-3615. DOI:
10.1016/j.compind.2013.02.009.
Conferences
Shahid, Z, Beckmann, A, Sylla, A,
Giannetti, C, Alpan, G (2025)
Ontology-Based Approach to Supplier Risk Management Using Large Language Models. In
, IFAC Papersonline, pp.2826-2831, DOI:
10.1016/j.ifacol.2025.09.475.
Gibbs, R,
Giannetti, C, Baynes, T, Pleydell-Pierce, C (2024)
Leveraging Machine Learning Insights at the Hot Strip Rolling Mill, Tata Steel, Port Talbot. In
, Conference Record IEEE Instrumentation and Measurement Technology Conference. DOI:
10.1109/I2MTC60896.2024.10560883.
O'Donovan, C,
Giannetti, C, Pleydell-Pearce, C (2024)
Revolutionising the Sustainability of Steel Manufacturing Using Computer Vision. In
, Procedia Computer Science, pp.1729-1738, DOI:
10.1016/j.procs.2024.01.171.
O'Donovan, C,
Giannetti, C, Pleydell-Pearce, C (2023)
Enabling Sustainable Steel Production with Computer Vision. In
, Advances in Transdisciplinary Engineering, pp.37-42, DOI:
10.3233/ATDE230897.
Lakshmanan, K, Karimi, A, Carr, A, Wauters, P, Auinger, M, Pleydell-Pearce, C,
Giannetti, C (2023)
A Hybrid Modelling Approach Based on Deep Learning for the Prediction of the Silicon Content in the Blast Furnace. In
, Procedia Computer Science, pp.2204-2213, DOI:
10.1016/j.procs.2023.10.211.
Latham, S and
Giannetti, C (2022)
Root Cause Classification of Temperature-related Failure Modes in a Hot Strip Mill. In
, In4pl Proceedings of the International Conference on Innovative Intelligent Industrial Production and Logistics, pp.36-45, DOI:
10.5220/0011380300003329.
Lakshmanan, K, Borghini, E, Beckmann, A, Pleydell-Pearce, C,
Giannetti, C (2022)
Data modelling and Remaining Useful Life estimation of rolls in a steel making cold rolling process. In
, Procedia Computer Science, pp.1057-1066, DOI:
10.1016/j.procs.2022.09.161.
Borghini, E and
Giannetti, C (2021)
Short Term Load Forecasting Using TabNet: A Comparative Study with Traditional State-of-the-Art Regression Models. In
International Conference on Time Series and Forecasting, The 7th International Conference on Time Series and Forecasting, pp.6-6, DOI:
10.3390/engproc2021005006.
Flynn, J, Brealy, E,
Giannetti, C (2021)
MAKING GREEN TRANSPORT A REALITY: A CLASSIFICATION BASED DATA ANALYSIS METHOD TO IDENTIFY PROPERTIES SUITABLE FOR ELECTRIC VEHICLE CHARGING POINT INSTALLATION. In
, International Geoscience and Remote Sensing Symposium IGARSS, pp.6229-6232, DOI:
10.1109/IGARSS47720.2021.9553748.
O'Donovan, C,
Giannetti, C, Todeschini, G (2021)
A novel deep learning power quality disturbance classification method using autoencoders. In
, Icaart 2021 Proceedings of the 13th International Conference on Agents and Artificial Intelligence, pp.373-380, DOI:
10.5220/0010347103730380.
Latham, S and
Giannetti, C (2021)
Pre-Trained CNN for Classification of Time Series Images of Anti-Necking Control in a Hot Strip Mill. In
The Proceedings of The 9th IIAE International Conference on Industrial Application Engineering 2020, pp.77-84, DOI:
10.12792/iciae2021.015.
Fairclough, SM,
Giannetti, C, Wagner, I, Shakeel, H (2020)
Colorimetric sensor for pH monitoring of liquid samples using bubble wrap and mobile phone camera. In
, Fleps 2020 IEEE International Conference on Flexible and Printable Sensors and Systems. DOI:
10.1109/FLEPS49123.2020.9239445.
Essien, AE, Chukwkelu, G,
Giannetti, C (2019)
A Scalable Deep Convolutional LSTM Neural Network for Large-Scale Urban Traffic Flow Prediction using Recurrence Plots. In
, IEEE AFRICON Conference. DOI:
10.1109/AFRICON46755.2019.9134031.
Essien, A and
Giannetti, C (2019)
A Deep Learning Framework for Univariate Time Series Prediction Using Convolutional LSTM Stacked Autoencoders. In
, IEEE International Symposium on Innovations in Intelligent Systems and Applications Inista 2019 Proceedings. DOI:
10.1109/INISTA.2019.8778417.
Giannetti, C, Essien, A, Pang, YO (2019) A novel deep learning approach for event detection in smart manufacturing. In
, Proceedings of International Conference on Computers and Industrial Engineering CIE.
Giannetti, C (2017)
A framework for improving process robustness with quantification of uncertainties in Industry 4.0. In
, Proceedings 2017 IEEE International Conference on Innovations in Intelligent Systems and Applications Inista 2017, pp.189-194, DOI:
10.1109/INISTA.2017.8001155.
Md. Roshan, H,
Giannetti, C, Ransing, MR, Ransing, RS (2014) "If only my foundry knew what it knows⋯": a 7Epsilon perspective on root cause analysis and corrective action plans for ISO9001:2008. In
, 71st World Foundry Congress Advanced Sustainable Foundry Wfc 2014.
Giannetti, C, Ransing, MR, Ransing, RS, Bould, DC, Gethin, DT, Sienz, J (2014) Product specific process knowledge discovery using co-linearity index and penalty functions to support process FMEA in the steel industry. In
, CIE 2014 44th International Conference on Computers and Industrial Engineering and Imss 2014 9th International Symposium on Intelligent Manufacturing and Service Systems Joint International Symposium on the Social Impacts of Developments in Information Manufacturing and Service Systems Proceedings, pp.305-319.
