Optimizing Manufacturing Processes through Artificial Intelligence and Virtualization

Livrables

OPTIMAI commercialization and exploitation strategy - 1st version

This deliverable will report on OPTIMAIs exploitation strategy and includes interaction with standardization bodies It will be periodically updated

Forum and information pack for key stakeholders

This deliverable will report on communication activities with relevant stakeholders

The OPTIMAI architecture specifications - 1st version

This deliverable will document the technical requirements and architecture formal specification As such it will describe the overall system components with their interfaces This deliverable will be updated based on the developments of WP3 through WP6 in M18

State of the art survey

This deliverable will report on the state of the art in related scientific fields and will also identify related research initiatives

OPTIMAI commercialization and exploitation strategy - 2nd version

This deliverable will report on OPTIMAIs exploitation strategy and includes interaction with standardization bodies It will be periodically updated

Ethics recommendations and regulatory framework

It defines the ethics and legal framework for pilot deployment

The OPTIMAI architecture specifications - 2nd version

This deliverable will document the technical requirements and architecture formal specification As such it will describe the overall system components with their interfaces

User and ethics and legal requirements - 1st version

This deliverable will gather together the results from T21 defining the user requirements for the project resulting from a codesign methodology between endusers technology providers as well as ethics and legal experts

Report on communication and dissemination activities - 1st version

This report will monitor the execution of OPTIMAIs dissemination strategy

Training Material - 1st version

This deliverable provides the training material for OPTIMAI endusers This is the initial version

OPTIMAI use cases definition

This report will deliver a shared vision of the targeted OPTIMAI concepts within the context of the use cases Section 133 in the form of usage scenarios and KPIs

Communication and dissemination strategy

This report will define projects dissemination plan

User and ethics and legal requirements - 2nd version

This deliverable will gather together the results from T21 defining the user requirements for the project resulting from a codesign methodology between endusers technology providers as well as ethics and legal experts

Data Management Plan - 2nd version

This deliverable will describe the adopted plan and measures for managing data within the project It will describe the processes and guidelines for managing the research data inside the project including legal and ethical responsibilities ensuring compliance with the applicable legal framework

Data Management Plan - 1st version

This deliverable will describe the adopted plan and measures for managing data within the project It will describe the processes and guidelines for managing the research data inside the project including legal and ethical responsibilities ensuring compliance with the applicable legal framework

Project website and branding

This deliverable will establish projects profile to external entities

Publications

Short Survey of Artificial Intelligent Technologies for Defect Detection in Manufacturing

Auteurs: Elpiniki I. Papageorgiou, Theodosis Theodosiou, George Margetis, Nikolaos Dimitriou, Paschalis Charalampous, Dimitrios Tzovaras, Ioannis Samakovlis
Publié dans: International Conference on Information, Intelligence, Systems and Applications (IISA), Numéro 1, 2021
Éditeur: IEEE
DOI: 10.1109/iisa52424.2021.9555499

Autoencoders for Anomaly Detection in an Industrial Multivariate Time Series Dataset

Auteurs: Theodoros Tziolas, Konstantinos Papageorgiou, Theodosios Theodosiou, Elpiniki Papageorgiou, Theofilos Mastos and Angelos Papadopoulos
Publié dans: 8th International conference on Time Series and Forecasting (ITISE2022), Numéro 18(1), 2022, Page(s) 23
Éditeur: 8th International conference on Time Series and Forecasting (ITISE2022)
DOI: 10.3390/2022018023

A Deep Regression Framework Towards Laboratory Accuracy in the Shop Floor of Microelectronics

Auteurs: Apostolos Evangelidis, Nikolaos Dimitriou, Lampros Leontaris, Dimosthenis Ioannidis, Gregory Tinker, Dimitrios Tzovaras
Publié dans: IEEE Transactions on Industrial Informatics, Numéro 1, 2022, Page(s) 1-10, ISSN 1551-3203
Éditeur: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tii.2022.3182343

An Autonomous Illumination System for Vehicle Documentation Based on Deep Reinforcement Learning

Auteurs: Lampros Leontaris; Nikolaos Dimitriou; Dimosthenis Ioannidis; Konstantinos Votis; Dimitrios Tzovaras; Elpiniki I. Papageorgiou
Publié dans: IEEE Xplore, Numéro 1, 2021, Page(s) 75336 - 75348, ISSN 2169-3536
Éditeur: Institute of Electrical and Electronics Engineers Inc.
DOI: 10.1109/access.2021.3081736

Livrables

Publications

Partager cette page

Télécharger