Public deliverables 

D1.2 Legal and ethical requirements for human-machine interaction (PDF)

This report contains an overview of the integration of ethics into the first six months of the AI-PROFICIENT project. The overview includes a literature review of the current and past work upon Industrial AI ethics, a survey of related guides and principles, and observations regarding the state of the discipline and its particular character relative to other fields of AI ethics.

D1.3 Pilot-specific demonstration scenarios (PDF)

This report incorporates a specification of the demonstrator to be constructed per use case. This specification contains a description of the case, their potential solutions, and the requirements and preferences related to each solution.

D7.1 Roadmap for dissemination and communication first release (PDF)

This report sets out the dissemination and communication strategy as well as the plan to raise awareness, share knowledge, attract potential stakeholders in the context of the AI-PROFICIENT project, through various means, including the AI-PROFICIENT website, the use of Social Media, the distribution of communication material, publications in scientific and industrial journals, participation in events and organization of dedicated workshops with potential end-users and main outreach events. 

D7.2 Project identity kit and communication material (PDF)

This document will help you understand the essential elements of the AI-PROFICIENT identity. It explains how to use the identity and serves as a source of inspiration for you to continue building a strong brand people love to be a part of.

D1.5: AI-PROFICIENT system architecture

The aim of this document is to provide the architecture of the AI-PROFICIENT platform following the “ethics by design approach”.

D3.1: AI-PROFICIENT hybrid models and digital twins first version (state of the art, designing and specification)

This report presents the state of the art of hybrid modelling and digital twins, covering the techniques from first principles modelling to fully data based surrogate models and digital twins based on these approaches. On that basis, designing of the approach for selected use cases and the specifications in each case are described.

D4.1: Human-machine interaction and feedback mechanisms (Design and specification)

This report incorporates the description of the end user’s requirements related to the use cases in terms of the feedback management and the description for each one to manage it for a reinforcement learning approach.

D5.1: Communication middleware and IIoT interoperability – design and specification

The aim of this document is to provide the design and specification of AI-PROFICIENT platform middleware and interface towards smart components and edge AI.


AI-PROFICIENT Brochure (version 1)



  • Chaoub, A., Voisin, A., Cerisara, C., & Iung, B. (2021). Learning Representations with End-to-End Models for Improved Remaining Useful Life Prognostic. PHM Society European Conference, 6(1), 8.

  • López de Calle – Etxabe, K., Gómez – Omella, M., & Garate – Perez, E. (2021). Divide, Propagate and Conquer: Splitting a Complex Diagnosis Problem for Early Detection of Faults in a Manufacturing Production Line. PHM Society European Conference, 6(1), 9.
  • Esnaola-Gonzalez, Iker. (2021). Can Ontologies help making Machine Learning Systems Accountable?. 10.13140/RG.2.2.29339.18722.
  • Nguyen, Van-Thai & DO, Phuc & Voisin, Alexandre & Iung, Benoît. (2021). Reinforcement Learning for Maintenance Decision-Making of Multi-State Component Systems with Imperfect Maintenance. 2142-2149. 10.3850/978-981-18-2016-8_304-cd.
  • L. Berbakov and N. Tomašević, “Internet of Things Platform Architecture for Smart Factories,” 2021 International Balkan Conference on Communications and Networking (BalkanCom), 2021, pp. 157-160, doi: 10.1109/BalkanCom53780.2021.9593239.
  • López de Calle – Etxabe Kerman, Garate – Perez Eider, Arnaiz Aitor, “Towards a Circular Rotating Blade Wear Assessment Digital Twin for Manufacturing Lines”, IFAC-PapersOnLine, Volume 55, Issue 2, 2022, Pages 561-566, ISSN 2405-8963,