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Meet the people behind knowlEdge: Victor Anaya

What is your personal background?

I have a Master’s Degree in Information Technology, and an Advanced Education Diploma on Enterprise Management and Engineering. I have been working in the application of IT technology and manufacturing processes management since I finished my degree at the Polytechnical University of Valencia. I have worked for public and private companies applying many of the technologies that are now considered the Industry 4.0. I have also complemented this experience with research in Industry 4.0 and 5.0 and the application of digital twin technologies and machine learning in the manufacturing field.

I am currently a product owner and a project manager at Information Catalyst S.L., exploring how companies can improve and gain a competitive advantage. My present work is on leading the ICE digital twin team and driving the usage of machine learning technologies on it. I am also part of the analytics team on ICE.

What is your organization’s role in knowlEdge?

ICE is the technical manager at the knowlEdge project, where we facilitate the work done by technical partners and try to make that the sum of our expertise provides a bigger value and impact that the isolated solutions we provide as a team. Coordinating the technical discussions in knowlEdge has been a very rewarding experience. ICE is also proud to lead the exploitation task in knowlEdge. Although knowlEdge is a research and innovation action, it is always interesting to keep a foot into the market perspective, not only from a commercial point of view but from a research and innovation approach, as there is a universe of AI solutions. Finally, ICE is in charge of providing the knowlEdge digital twin framework solution. A tool capable to integrate with several of the components of the platform and make sense run simulations to get for efficient AI solutions.

What fascinates you about Artificial Intelligence for manufacturing?

Artificial Intelligence (AI) is revolutionizing the manufacturing industry in fascinating ways, transforming traditional processes and introducing unprecedented levels of efficiency and innovation. One of the most captivating aspects of AI in manufacturing is its ability to optimize production processes. AI systems can analyze data from sensors and machinery on the factory floor, predicting when failures and breakdowns are likely to occur. This predictive maintenance capability allows manufacturers to ensure that resources and spare parts necessary for repair are on hand, reducing downtime and improving logistical planning
AI also plays a crucial role in quality control, analyzing sensor data in real time and detecting anomalies. Machine learning algorithms can predict potential failures or defects, enabling early identification and prevention of issues.
Furthermore, AI helps manufacturers improve energy efficiency and sustainability by analyzing energy usage patterns, identifying areas of waste, and suggesting optimization strategies.
The integration of AI in manufacturing is not just about automation, but also about creating smart, connected manufacturing plants where humans and machines work together, and data and analytics enable better predictions and decision-making at every stage of the process.

What are your expectations in knowlEdge?

The knowlEdge project is developing innovative AI methods and systems that can improve efficiency, safety, and sustainability in manufacturing processes. These advancements will enable manufacturing companies to securely manage distributed data, execute analytic algorithms, and redistribute knowledge towards a knowledge exchange society.
We acknowledge that applying these AI based solutions is a complex task for SMEs as it requires a strong expertise, so one of our expectations is to provide innovative solutions that can be easily applied to SMEs, helping them to stay competitive and benefit from the latest technological advancements in the manufacturing sector.
Lastly, we want to contribute to the growth of a knowledge exchange society. The knowlEdge Project will facilitate the sharing of knowledge and expertise among researchers, academics, policy makers, and manufacturing companies. This collaborative environment will foster innovation and problem-solving across different sectors, ultimately driving the 4th industrial revolution forward.

Which target groups can benefit from knowlEdge?

The knowlEdge Project is focused on developing AI-powered manufacturing services, processes, and products. Manufacturing companies can benefit from the project by adopting the new generation of AI methods, systems, and data management infrastructure to improve their manufacturing processes. The project aims to provide a framework that will enable manufacturing companies to securely manage distributed data and execute analytic algorithms to redistribute knowledge towards a knowledge exchange society.
Being a research and innovation action, knowlEdge aims to develop a new generation of AI methods, systems, and data management infrastructure, expanding these respective research fields. Researchers and academics can benefit from the project by studying the new generation of AI methods, systems, and data management infrastructure developed by the project. The project aims to provide a framework that will enable researchers and academics to securely execute analytic algorithms to redistribute knowledge towards a knowledge exchange society.

What is your vision beyond knowlEdge?

As any person part of this project, we want to increase the adoption of AI-powered manufacturing services, processes, and products that could lead to an increased efficiency, safety, and sustainability in the European manufacturing sector.
In the other hand, we want to empower researchers, academics, policy makers, and manufacturing companies sharing our knowledge and open source solutions sharing our expertise to solve complex problems.
My vision is that we can be part of the advancement of the 4th industrial revolution, providing end-to-end solutions that can lead to increased automation, digitization, and connectivity in the manufacturing sector. The advancement of the 4th industrial revolution could enable manufacturing companies to produce goods more efficiently, with higher quality, and at a lower cost.