Transformation of Industrial Data into Strategic Decisions: Perspectives from Advanced Manufacturing Madrid 2025
At the 16th edition of Advanced Manufacturing Madrid, held at IFEMA, Madrid, on November 5 and 6, 2025, sessions focused on converting industrial data into strategic decisions through AI and machine learning. One of the standout presentations was "Transformation of Industrial Data into Strategic Decisions," which brought together specialists and operations managers to discuss how to leverage data to automate analysis, predict behaviors, and optimize processes autonomously.
Organization and technology forum This year's technology forum space was organized by Global Lean TECH FORUM 4.0, with Sales Layer and Solter as sponsors. The proposal "Applied Solutions for Metal Intralogistics" aimed to inspire, connect, and transform the understanding of intralogistics, showcasing how Lean methodology and digitalization are revolutionizing the supply chain in the metallurgical sector. With optimized flows, standardization, and visual management, the forum demonstrated that operational excellence is possible in high-speed and precision environments through real experiences, presentations, and success stories.
The presentation by Zeus Gargallo Zeus Gargallo, Expansion and Projects Director at Netretina AI and a member of the NAiOS team, participated in an interactive session focused on transforming operational data into real-time decisions. The talk addressed key questions: how to implement systems that learn from operations? what challenges does predictive AI present? and how to leverage this data to autonomously optimize efficiency?
Implementation of systems that learn from operations Gargallo emphasized the importance of going beyond data collection. Systems must learn from operations in real-time, adapt to process variations, and provide quick responses to reduce errors and increase efficiency. The integration of models that update with plant data facilitates more informed and agile decision-making.
Challenges of predictive AI Among the challenges are the quality and quantity of data, the need for data governance, and the ability of systems to handle unexpected changes in the environment. The session emphasized that predictions must be accompanied by understanding, explainability, and mitigation plans to ensure reliable implementation.
Hidden patterns and real-time recommendations The presentation highlighted how AI technologies can detect patterns that remain invisible to the human eye and generate real-time recommendations. This approach enables proactive operational adjustments, optimizing resources, reducing downtime, and improving strategic decision-making.
Impact and takeaways for companies
- Data-driven operational transformation: plants can turn data into concrete actions without constant manual intervention.
- Faster and more accurate decisions: AI provides real-time recommendations for process adjustments.
- Increased efficiency and cost reduction: automation of analysis and prediction of failures for preventive maintenance.
- Need for governance and data quality: investment in clean data, security, and compliance.
Conclusion Zeus Gargallo's participation in Advanced Manufacturing Madrid 2025 provided practical insights on how companies can transform industrial data into strategic decisions, overcoming challenges of predictive AI and leveraging complex patterns to optimize operations in real-time. The event highlighted that the collaboration between Netretina AI and NAiOS is at the forefront of these implementations.
About the event
- Event: Advanced Manufacturing Madrid 2025
- Dates: November 5–6, 2025
- Location: IFEMA, Madrid
- Highlighted session: Transformation of Industrial Data into Strategic Decisions
- Speaker: Zeus Gargallo, Expansion and Projects Director at Netretina AI (member of the NAiOS team)
- Official site: https://www.advancedmanufacturingmadrid.com/es/conferencias/espacio-foro-tecnologico/
