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Artificial intelligence (AI) has become integral to modern manufacturing processes, enabling increased efficiency, productivity, and automation.
The ethics implications of AI and machine learning are becoming increasingly relevant due to their implementations across several sectors. This is the case also for their application to the manufacturing domain, which is still a quite new application of AI technology.
Partner Spotlight – Ford Motor Company
Name: Javier Colomer Barberá Job title: New Technologies Engineer Organization: Ford Motor Company Bio: Javier Colomer is a Telecommunications Engineer from the Polytechnic University of Valencia.
XAI Model Guard: The XMANAI AI Models Security Framework
As manufacturing organizations are embracing the Industry 4.0 initiative that is revolutionizing the manufacturing sector towards the realization of smart factories, the adoption rate of technologies related to Artificial Intelligence (AI), machine learning, and analytics is also growing.
Explainable AI: a key to trust and acceptance of AI-based decision support systems Artificial intelligence is often based on complex algorithms and
Partner Spotlight – CNH Industrial
Name: Claudia Campanella Job title: Manager of Ergonomics-HMI-VR-AR Organization: CNH Industrial Bio: Claudia Campanella graduated in Industrial Design at the Polytechnic of Turin, realizing a thesis in physical ergonomics. She started working at Fiat Auto in 2000 and at the same time, she attended the Master in Ergonomics in which she created a thesis in cognitive ergonomics.
Archives
- Explaining Transformers
- How are the final MVP features contributing to the X-By-Design Concept?
- The Power of X-by-design: Pioneering Transparency and Explainability through Design
- Hackathon Event: Paving the Way to Transparent AI in Manufacturing with XMANAI
- Intelligent ETL Solutions for XMANAI: API- and File Data Harvester
- XMANAI Centralized Models Execution and Visualization Environment
- Industrialization Approaches to Explainability and the XMANAI Cases
- Ethics considerations for manufacturing XAI: the XMANAI Ethical Evaluation Framework
- Partner Spotlight – Ford Motor Company
- XAI Model Guard: The XMANAI AI Models Security Framework
- Explainable AI: a key to trust and acceptance of AI-based decision support systems
- Partner Spotlight – CNH Industrial
- Industrial Asset Graph Modelling in XMANAI
- XMANAI Validation Environment for AI Models
- zExplAIn, Improving Manufacturing Processes with Explainable AI
- XMANAI partner spotlight – Deep Blue
- Technical and Socio-Business assessments of AI Maturity in pilots of Explainable AI
- XMANAI partner spotlight – UNIMETRIK
- AI Algorithms Lifecycle Management and Collaboration
- XMANAI partner spotlight – Knowledgebiz
- XMANAI partner spotlight – UBITECH
- A First Glimpse into the XMANAI platform
- XMANAI partner spotlight – Whirlpool
- Overview requirements
- XMANAI partner spotlight – Athena Research Center
- Industrial Assets Provenance in XMANAI
- XMANAI partner spotlight – Innovalia Association
- The Draft Catalogue of XMANAI XAI Models
- XMANAI´s Evaluation Framework
- XMANAI partner spotlight – Suite5
- XMANAI Reference Architecture: Perspectives
- Security Aspects of Industrial Data Management
- XMANAI partner spotlight – AiDEAS
- What is the XMANAI Minimum Viable Product (MVP)?
- XAI in Manufacturing
- Data Asset Management in XMANAI
- XMANAI partner spotlight – Tyris AI
- XMANAI partner spotlight – Politecnico di Milano
- Education role in AI technology implementation in industry
- XMANAI partner spotlight – Fraunhofer FOKUS
- AI Requirements for Manufacturing in the XMANAI Project
- Have you ever heard about Graphical Neural Networks?
- A brief overview of XAI Landscape
- XMANAI partner spotlight – TXT e-solutions
- Outlook on the XMANAI industrial demonstration cases
- Why we should make use of AI in the manufacturing industry?
- Human Aspects in Decision making and AI
- Moving from “black box” to “glass box” Artificial Intelligence in Manufacturing, with XMANAI