Publications
ENHANCING DEFECT TRACEABILITY AND DATA INTEGRITY IN INDUSTRY 4.0 USING BLOCKCHAIN TECHNOLOGY
Andreana Mitsiaki, Nikolaos Dimitriou, George Margetis, Konstantinos Votis, Dimitrios Tzovaras, “Enhancing Defect Traceability and Data Integrity in Industry 4.0 Using Blockchain Technology,” in Eccomas Proceedia SMART (2023), pp. 1173-1184, doi: 10.7712/150123.9866.443273
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AN ELEVATOR CALIBRATION RECOMMENDER SYSTEM FOR EFFECTIVE DEFECT DETECTION AND PREVENTION
George Margetis, Nikolaos Dimitriou, Elpiniki Papageorgiou, Theodosios Theodosiou, Konstantinos C. Apostolakis, Stavroula Ntoa, Despoina Gavgiotaki, Dimitrios Tzovaras, Constantine Stephanidis, “An Elevator Calibration Recommender System for Effective Defect Detection and Prevention,” in Eccomas Proceedia SMART (2023), pp. 1234-1245, doi: 10.7712/150123.9871.446205
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INSPECTION OF SURFACE DEFECTS IN METAL PROCESSING INDUSTRY USING UNET-BASED ARCHITECTURES
Lampros Leontaris, Nikolaos Dimitriou, Apostolos Nikolousis, Dimitrios Tzovaras, Elpiniki Papageorgiou, “Inspection of Surface Defects in Metal Processing Industry Using UNet-Based Architectures,” in Eccomas Proceedia SMART (2023), pp. 1221-1233, doi: 10.7712/150123.9870.444670
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CENTERNET-BASED MODELS FOR THE DETECTION OF DEFECTS IN AN INDUSTRIAL ANTENNA ASSEMBLY PROCESS
Theodosios Theodosiou, Theodoros Tziolas, Konstantinos Papageorgiou, Aikaterini Rapti, Elpiniki Papageorgiou, Sebastian Pantoja, Paschalis Charalampous, Nikolaos Dimitriou, Dimitrios Tzovaras, A. Cuiñas, J. Mourelle, Andreas Böttinger, George Margetis, “Centernet-based Models for the Detection of Defects in an Industrial Antenna Assembly Process,” in Eccomas Proceedia SMART (2023), pp. 1209-1220, doi: 10.7712/150123.9869.444634
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automated defect detection in battery line assembly via deep learning analysis
Anastasios Tzelepakis, Lampros Leontaris, Nikolaos Dimitriou, Evangelia Koukidou, Dimitrios Bollas, Aristoklis Karamanidis, Dimitrios Tzovaras, “Automated Defect Detection in Battery Line Assembly via Deep Learning Analysis,” in Eccomas Proceedia SMART (2023), pp. 1196-1208, doi: 10.7712/150123.9868.444540
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AI FOR DETECTING VARIATIONS IN THE OEE DATA RECEPTION RATE IN THE MANUFACTURING INDUSTRY
Clara I. Valero, Fernando Boronat, Manuel Esteve, Carlos E. Palau, “AI for Detecting Variations in the OEE Data Reception Rate in the Manufacturing Industry,” in Eccomas Proceedia SMART (2023), pp. 1185-1195, doi: 10.7712/150123.9867.444277
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EFFICIENTDET APPLICATION FOR DETECTION OF INCORRECT ASSEMBLIES IN THE ANTENNA MANUFACTURING PROCESS
Anna Feleki, Konstantinos Papageorgiou, Theodoros Tziolas, Aikaterini Rapti, Theodosios Theodosiou, Sebastian Pantoja, Paschalis Charalampous, Nikolaos Dimitriou, Dimitrios Tzovaras, A. Cuiñas, J. Mourelle, Elpiniki Papageorgiou, Andreas Böttinger, George Margetis, “Efficientdet Application for Detection of Incorrect Ass,” in Eccomas Proceedia SMART (2023), pp. 1270-1278, doi: 10.7712/150123.9874.444639
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HAND GESTURE RECOGNITION USING RECURRENT NEURAL NETWORKS AND SYNTHETIC DATA GENERATION
F. Sabbarese, L. Magliulo, P. Carratu, M. Romano, “Hand Gesture Recognition Using Recurrent Nueral Networks and Synthetic Data Generation,” in Eccomas Proceedia SMART (2023), pp. 1279-1290, doi: 10.7712/150123.9875.445104
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An Autonomous Illumination System for Vehicle Documentation Based on Deep Reinforcement Learning
L. Leontaris, N. Dimitriou, D. Ioannidis, K. Votis, D. Tzovaras and E. Papageorgiou, “An Autonomous Illumination System for Vehicle Documentation Based on Deep Reinforcement Learning,” in IEEE Access, vol. 9, pp. 75336-75348, 2021, doi: 10.1109/ACCESS.2021.3081736
Access on Zenodo: https://zenodo.org/record/8205143
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Short Survey of Artificial Intelligent Technologies for Defect Detection in Manufacturing
E. I. Papageorgiou et al., “Short Survey of Artificial Intelligent Technologies for Defect Detection in Manufacturing,” 2021 12th International Conference on Information, Intelligence, Systems & Applications (IISA), 2021, pp. 1-7, DOI: 10.1109/IISA52424.2021.9555499.
Access on Zenodo: https://zenodo.org/record/8207954
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A Deep Regression Framework Towards Laboratory Accuracy in the Shop Floor of Microelectronics
A. Evangelidis, N. Dimitriou, L. Leontaris, D. Ioannidis, G. Tinker and D. Tzovaras, “A Deep Regression Framework Towards Laboratory Accuracy in the Shop Floor of Microelectronics,” in IEEE Transactions on Industrial Informatics, 2022, doi: 10.1109/TII.2022.3182343.
Access on Zenodo: https://zenodo.org/record/8208007
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Autoencoders for Anomaly Detection in an Industrial Multivariate Time Series Dataset
Theodoros Tziolas, Konstantinos Papageorgiou, Theodosios Theodosiou, Elpiniki Papageorgiou, Theofilos Mastos and Angelos Papadopoulos. “Autoencoders for Anomaly Detection in an Industrial Multivariate Time Series Dataset” in MDPI Engineering Proceedings, 2022, https://doi.org/10.3390/engproc2022018023.
Access on Zenodo: https://zenodo.org/record/8208030
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Aligning Emerging Technologies onto I4.0 principles: Towards a Novel Architecture for Zero-defect Manufacturing
G. Margetis, K. C. Apostolakis, N. Dimitriou, D. Tzovaras and C. Stephanidis, “Aligning Emerging Technologies onto I4.0 principles: Towards a Novel Architecture for Zero-defect Manufacturing,” 2022 IEEE 27th International Conference on Emerging Technologies and Factory Automation (ETFA), 2022, pp. 1-8, doi: 10.1109/ETFA52439.2022.9921492.
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Wafer Map Defect Pattern Recognition using Imbalanced Datasets
T. Tziolas et al., “Wafer Map Defect Pattern Recognition using Imbalanced Datasets,” 2022 13th International Conference on Information, Intelligence, Systems & Applications (IISA), 2022, pp. 1-8, doi: 10.1109/IISA56318.2022.9904402.
Dilemmas in Legal Governance
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A systematic review on machine learning methods for root cause analysis towards zero-defect manufacturing
Papageorgiou K, Theodosiou T, Rapti A, Papageorgiou EI, Dimitriou N, Tzovaras D and Margetis G (2022), A systematic review on machine learning methods for root cause analysis towards zero-defect manufacturing. Front. Manuf. Technol. 2:972712. doi: 10.3389/fmtec.2022.972712
Access on Zenodo: https://zenodo.org/record/8208184
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An easy Hand Gesture Recognition System for XR-based collaborative purposes
N. Capece, G. Manfredi, V. Macellaro and P. Carratù, “An easy Hand Gesture Recognition System for XR-based collaborative purposes,” 2022 IEEE International Conference on Metrology for Extended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE), Rome, Italy, 2022, pp. 121-126, DOI: 10.1109/MetroXRAINE54828.2022.9967592
Access on Zenodo: https://zenodo.org/record/8208271
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4ZDM Workshop: OPTIMAI Progress
Achieved
N. Dimitriou.
European Zero Defect Manufacturing ZDM Landscape State of Play, 8 July 2021, virtual workshop.