ABB’s EXPLAIN Project Wins AI Innovation Award, Making Industrial Automation Smarter

Industrial automation is rapidly evolving with artificial intelligence. However, the “black box” nature of many AI systems has hindered widespread trust and adoption in critical process industries. A recent award-winning project led by ABB tackles this challenge head-on, demonstrating how explainable AI (XAI) is becoming a practical reality for operators.

Project EXPLAIN: A New Era of Transparent AI for Industry

The international research project EXPLAIN has received the ITEA Award of Excellence 2025 for Innovation. ABB’s Corporate Research Centers in Germany and Sweden spearheaded this initiative. The project’s core mission was to develop AI that is not just powerful but also transparent and understandable for end-users. This directly addresses a key barrier in industrial automation, where understanding the “why” behind an AI’s decision is as crucial as the decision itself. According to a report by MarketsandMarkets, the global XAI market is projected to grow from $4.4 billion in 2022 to $21.0 billion by 2030, underscoring the critical industry demand for clarity in AI.

Real-World Applications Across Key Industries

The project’s success is rooted in its practical, industry-driven use cases. EXPLAIN moved beyond theoretical research to validate XAI in live operational environments. These applications show how AI can be integrated into control systems and factory automation workflows to enhance decision-making.

• Mining: ABB collaborated with Boliden to optimize flotation processes. The AI solution provided insights into process variables, targeting higher efficiency and harmonization.
• Pulp & Paper: Together with Södra, the team improved pulp quality stability in digester operations. The focus was on user-centered design, ensuring the AI’s outputs were interpretable by plant engineers.
• Energy: ABB and LEAG developed an AI-based anomaly detection system for power plants. Crucially, the system explains what is happening, where, and why, making predictions actionable for control room operators.

Why Explainable AI is the Future of Industrial Control

Trust is the foundation of any technology deployed in high-stakes industrial environments. As a result, XAI is no longer a luxury but a necessity. For professionals working with PLCs and DCS, an AI that can explain its reasoning acts like a highly skilled assistant. It provides context and justification, which empowers operators to trust and effectively manage automated systems. This shift is vital for the next generation of smart factories and process plants. From our perspective at PLCDCSHUB, the principles demonstrated by EXPLAIN align perfectly with the need for reliable and interpretable data driving modern control systems. To explore robust control system components that can form the backbone of such intelligent operations, visit our comprehensive product directory at PLCDCSHUB.

Key Outcomes and Lasting Impact

The three-year project, concluding in 2025, has delivered substantial results. It involved 15 partners from industry and academia across three European countries. The tangible outputs include new XAI methodologies, industry-tested prototypes, and over 70 scientific publications. Moreover, the consortium produced a public guidebook for implementing explainable AI in process industries. This resource provides invaluable guidance for engineers and managers looking to adopt AI responsibly.

Driving the Future of Data-Driven Operations

The next phase for this technology involves scaling these proven solutions. The goal is to extend the benefits of explainable AI to a wider range of industrial environments. Therefore, we can expect to see these techniques trickle down into more standard industrial automation platforms. This will enable more efficient, safe, and data-driven operations across the globe. The work by ABB and its partners clearly demonstrates that the future of industrial AI is not just about intelligence, but about intelligible and collaborative partnership between humans and machines.

Frequently Asked Questions (FAQ)

• What is Explainable AI (XAI) in simple terms? XAI refers to artificial intelligence systems that can explain their decisions and reasoning in a way that humans can understand, moving away from “black box” models.
• How does XAI benefit factory automation? It builds operator trust, simplifies troubleshooting, ensures regulatory compliance, and helps optimize complex processes like those managed by PLCs and DCS.
• Is XAI only for large corporations? While pioneered by industry leaders, the methodologies and tools are increasingly accessible, allowing businesses of various sizes to adopt transparent AI solutions.