ABB’s EXPLAIN AI Project Wins ITEA Innovation Award for Industrial Automation

ABB’s Corporate Research Centers receive the ITEA Award of Excellence 2025. The EXPLAIN project develops transparent AI solutions for process industries. This recognition highlights ABB’s leadership in industrial artificial intelligence.

International Recognition for AI Innovation

The ITEA Award honors groundbreaking software innovation achievements. ABB’s research centers in Germany and Sweden led the project. They collaborated with partners across three European countries. Moreover, the project received EU research funding support.

Explainable AI Technology Development

The EXPLAIN project focuses on transparent artificial intelligence systems. It makes AI decisions understandable for industrial operators. This approach builds trust in automated systems. Consequently, operators can interact with AI recommendations confidently.

Mining Industry Application

ABB partnered with Boliden for flotation process optimization. The AI solution targets higher efficiency and harmonization. Industry experts participated throughout development. Furthermore, the project delivered concrete operational improvements.

Pulp and Paper Implementation

Södra collaborated on pulp quality stability enhancement. The system focuses on digester process optimization. User-centered design ensures practical applicability. Additionally, explainability features build operator trust.

Energy Sector Deployment

LEAG worked with ABB on anomaly detection systems. The solution explains power plant abnormalities clearly. Operators understand what, where and why issues occur. This transparency improves decision-making significantly.

Industrial AI Market Context

The industrial AI market demonstrates rapid expansion. According to MarketsandMarkets, it will reach $17.2 billion by 2028. Process industries increasingly adopt AI solutions. However, explainability remains a critical adoption barrier.

Project Scope and Partnerships

• Duration: 2022-2025 with 15 international partners
• Countries: Germany, Sweden and Netherlands participation
• Results: 70+ scientific contributions and industry prototypes
• Funding: Multiple national research agencies supported
• Output: Public guidebook for explainable AI implementation

Control System Integration

Explainable AI integrates with existing industrial automation platforms. It connects with DCS and PLC systems seamlessly. Operators receive understandable recommendations. Therefore, they can make informed control decisions.

Research Leadership Perspective

Dr. Jan-Henning Fabian leads ABB’s German Research Center. He emphasizes combining technology with industrial collaboration. The project demonstrates AI’s practical utility. Furthermore, it creates measurable customer benefits.

Industry Partner Testimonials

Boliden’s AI program manager acknowledges concrete project results. Södra’s engineers value the human-centered approach. LEAG’s digitalization lead highlights interdisciplinary collaboration. These partnerships validate the technology’s practical value.

PLCDCSHUB Industry Analysis

At PLCDCSHUB, we monitor AI’s growing role in industrial automation. Explainable AI addresses critical adoption barriers in control systems. The integration between industrial automation and AI becomes increasingly sophisticated. We observe similar transparency requirements across manufacturing sectors. These developments require both technical and human-factor considerations.

Power Plant Control Room Scenario

Consider a thermal power plant implementing EXPLAIN AI. The system detects abnormal turbine vibrations early. It explains the probable causes and recommended actions. Operators understand the reasoning behind maintenance suggestions. This approach prevents unexpected downtime effectively.

Frequently Asked Questions

• How does explainable AI differ from traditional black-box AI? Explainable AI provides reasoning behind its decisions, allowing operators to understand and trust recommendations rather than just receiving outputs.
• What industries benefit most from transparent AI systems? Highly regulated and safety-critical sectors like energy, mining, and chemicals gain significant advantages from understandable AI decision-making.
• How long do typical AI implementation projects require? Most industrial AI projects need 12-24 months for full implementation, including system integration, testing, and operator training phases.