Focus on Second Open Call winners: Enhancing Energy Efficiency with AI-Powered Anomaly Detection in Machine Tools – ADEPT Predictive Maintenance Case

WHAT ABOUT THE EXPERIMENT?

The transition from Industry 4.0 to Industry 5.0 is highlighting the importance of optimizing energy efficiency while ensuring safer and human-centric productivity in manufacturing environments. Machine tools (MTs), often the most energy-intensive assets in a production line, can exhibit abnormal energy consumption patterns indicative of malfunctions, inefficiencies, or suboptimal operation. Detecting these anomalies in real-time and diagnosing their root causes are critical for reducing operational costs and improving safety and sustainability. Therefore, this project aims to develop an AI-based anomaly detection system for energy consumption in machine tools powered by Large Language Models (LLMs) and Generative AI (GenAI) to aid in decision-making related to detected anomalies. The project will focus on three core components:

• AI for Anomaly Detection: Machine learning (ML) models to detect deviations in energy consumption patterns.

• LLMs/GenAI for Decision Support: LLMs and GenAI to interpret anomalies, suggest potential causes, and recommend remedial actions based on domain-specific knowledge and historical data.

• LLMs/GenAI for Explainability: Leveraging LLMs and GenAI to enhance the interpretability and transparency of AI models by translating complex detection mechanisms and predictions into human-understandable explanations.

The ADEPT approach and solutions will be implemented and demonstrated at the SCORTA manufacturing facilities in Milan, Italy (in Lombardia Region)..

WHAT IS THE EXPECTED IMPACT?

The project drives SCORTA's technological impact by making advanced AI and machine learning accessible and empowering these businesses to implement predictive maintenance without needing specialized AI expertise. It optimizes energy efficiency and resource utilization, which lowers operational costs and aligns with European sustainability goals. Integrating LLMs for decision support simplifies AI-driven insights, making data actionable and understandable for all employees, which promotes the rapid adoption of digital tools. This ultimately enhances operational efficiency, worker safety, and competitive positioning for SMEs, enabling them to thrive in an increasingly digital and sustainable industrial landscape.

SCORTA, through ADEPT solution, expects to improve the daily operations of its production machines. SCORTA expects to increase 15-20% net profitability (within 1-2 years from the end of the project) thanks to the reduction of process operative cost. ADEPT solution will also generate new business opportunities for SCORTA as the company can sell the new digital service to their customers, which can indirectly benefit from this experiment results.