ABB’s EXPLAIN Project Wins AI Innovation Award for Industrial Automation
ABB’s Corporate Research Centers received the ITEA Award of Excellence 2025. This prestigious award recognizes innovation in explainable AI for process industries. The EU-funded project involved partners from three countries.
Project Overview and Industry Significance
The EXPLAIN project developed transparent AI methods for industrial applications. It ran from 2022 to 2025 with fifteen international partners. According to MarketsandMarkets, the explainable AI market will reach $10.2 billion by 2028.
This growth reflects increasing demand for trustworthy industrial AI. The project combined cutting-edge research with practical applications. It ensured AI becomes reliable for daily industrial operations.
Mining Industry Application with Boliden
ABB collaborated with Boliden on flotation process optimization. They designed AI solutions for higher harmonization and efficiency. The project delivered concrete results through expert involvement.
Rasmus Tammia, Boliden’s AI program manager, confirmed the project’s success. He noted the innovative approach to industrial AI application. The mining sector benefits from these explainable AI methods.
Pulp and Paper Industry Implementation
ABB worked with Södra to improve pulp quality stability. They focused on digester process optimization and user-centered design. The project emphasized human-centered approaches for trust building.
Andreas Darnell from Södra Cell Technology Development praised the results. He highlighted valuable methods and tools for future applications. This approach creates optimal conditions for AI adoption.
Energy Sector Innovation with LEAG
ABB developed an AI-based anomaly detection system for power plants. The solution explains what is happening and why. This transparency helps operators trust AI predictions.
Dr. Jan Koltermann from LEAG appreciated the interdisciplinary collaboration. Scientists and industrial experts created a productive environment. The project provided valuable insights for power plant control rooms.
Technical Approach and Methodology
The EXPLAIN project focused on human-centered explainable AI (XAI). It enabled operators to trust and interact with AI systems. Users can even provide feedback to improve performance.
Key technical achievements include:
- ✅ New XAI methods for process industries
- ✅ Industry-tested prototypes
- ✅ 70+ scientific contributions
- ✅ Public guidebook for explainable AI
Project Partners and Collaboration Structure
Fifteen organizations participated from Germany, Sweden, and Netherlands. Academic institutions worked alongside industrial companies. This collaboration ensured both innovation and practicality.
Major participants included:
- ⚙️ ABB Corporate Research Centers
- ⚙️ Boliden and Södra (industrial partners)
- ⚙️ LEAG energy company
- ⚙️ Multiple European universities
Funding and International Support
National agencies from three countries provided financial support. Germany’s Federal Ministry of Research funded the German participants. Sweden’s Vinnova and Netherlands Enterprise Agency supported their national teams.
The ITEA framework enabled this international cooperation. EUREKA’s cluster program strengthens European digitalization competitiveness. Annual awards recognize groundbreaking project results.
Industrial Automation Implications
Explainable AI represents a crucial advancement for industrial automation. Modern control systems increasingly incorporate AI capabilities. However, transparency remains essential for operator acceptance.
PLCDCSHUB analysis indicates several key benefits:
- 🔧 Enhanced operator trust in AI recommendations
- 🔧 Improved decision-making transparency
- 🔧 Better integration with existing DCS and PLC systems
- 🔧 Reduced implementation resistance
Future Applications and Scaling
The project’s next phase will broaden industrial environment applications. Scaling results will amplify impact across process industries. More efficient data-driven operations will become achievable.
Dr. Jan-Henning Fabian, head of ABB Research Center Germany, expressed pride. He emphasized combining technology with industry collaboration. The project demonstrates how AI can be both understandable and useful.
Expert Analysis from World of PLC
Explainable AI addresses critical challenges in industrial automation. Traditional black-box AI systems often face operator skepticism. The EXPLAIN project methodology builds necessary trust.
Process industries particularly benefit from transparent AI. Mining, pulp and paper, and energy sectors demonstrate this clearly. Operators need to understand AI reasoning for critical decisions.
For professionals implementing industrial AI solutions,World of PLC provides comprehensive resources on control system integration. Our technical knowledge base covers AI implementation best practices.
Frequently Asked Questions
What is explainable AI (XAI) in industrial automation?
XAI provides transparent reasoning for AI decisions. It helps operators understand and trust automated recommendations in control systems.
Which industries benefited from the EXPLAIN project?
Mining, pulp and paper, and energy sectors implemented practical applications. Each demonstrated improved processes through transparent AI.
How does explainable AI impact control room operations?
It enhances operator confidence in AI recommendations. Transparent explanations support better decision-making and system acceptance.
