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Meet the people behind knowlEdge: Stefan Walter

What is your personal background?

I have a social and natural science background and hold a Doctor of Social Sciences degree from the University of Lapland. My academic expertise lies in addressing systems and management science questions, examining policy impacts on the economy, and understanding wider implications, particularly regarding sustainability and the capacity to adapt to changing conditions.

I am currently a senior researcher in the Intelligent Supply Chains and Logistics research team, which is part of VTT’s Cognitive Production Industry research area. In this role, I have focused primarily on exploring how different digital technologies can improve supply chain performance. I have also been involved in identifying ways to improve supply chain resilience. In addition, I have a keen interest in contributing to the development of future visions for manufacturing and supply chains.

My present work builds on several years in different positions in the logistics industry, where I developed expertise in logistics and supply chain management issues. I have also been teaching relevant courses in higher education within the same subject area.

What is your organization’s role in knowlEdge?

VTT is responsible for the overall coordination of the project, which addresses the need for effective management, coordination and management procedures, risk mitigation and ensuring timely and accurate reporting. We also provide conceptual developments for digital twins, integrating design principles based on state-of-the-art techniques and methodologies, and facilitate the implementation of the pilot use cases. The latter also includes the implementation methodology and prepares the ground for technology deployment and the evaluation of the use cases. Furthermore, VTT actively engages in dissemination and communication efforts, including providing valuable input for business model development, enabling the optimal utilisation of AI technologies.

What fascinates you about Artificial Intelligence for manufacturing?

What fascinates me about artificial intelligence for manufacturing is how it enhances numerous processes that had to be until recently tackled by humans or basic software applications. The advancements in AI enable us to automate and optimize complex tasks, resulting in increased efficiency, accuracy and productivity.

Additionally, engaging in artificial intelligence research does not only provide us with innovative solutions. It also gives us valuable insights into our own human capabilities. It highlights the distinct qualities, which cannot be replicated by machines equipped with artificial intelligence. This helps us to understand ourselves better and appreciate the particularities of human intelligence and creativity.

What are your expectations in knowlEdge?

Of course, I have high expectations. I anticipate that the project will successfully fulfill its research plan and deliver meaningful outcomes. One of my main hopes is that knowlEdge will make a substantial impact on all partners involved, providing them with a valuable learning experience and upgrading their expertise in AI applications. This will enable them to improve their marketable research and development work.

Also, I believe that the project’s solutions have the potential to create a profound impact on users. When it comes to improving innovation capacity and facilitating the integration of new knowledge, the project can drive advancements in industrial practices and processes. The solutions developed through knowlEdge can also have positive societal and environmental impacts, promoting sustainability and addressing key challenges in curbing resource and energy use.

The impact of these solutions can be even more significant when adopted across industries via the knowlEdge platform. The ability to scale and implement the project’s outcomes across different sectors amplifies the potential for widespread positive change.

Which target groups can benefit from knowlEdge?

The primary target group that can benefit from knowlEdge is of course the manufacturing and process industries. The implementation of AI technologies in those industries, as demonstrated through the pilot use cases, directly benefits operations by enhancing efficiency, reducing costs, optimizing production and improving quality.

In addition to those industries, associated value network partners such as suppliers and customers can also derive benefits. By having access to more accurate real-time information and AI-projected operations in production, these partners can gain a clearer understanding of the production processes and of the benefits of deploying AI solutions. Network partners will be able to make more informed decisions and align their operations.

AI-related companies, including software developers, can likewise derive significant benefits from the solutions developed in the knowlEdge project. By leveraging these resources, relevant companies can improve their capabilities, offer more sophisticated solutions and expand their market opportunities.

I would like to point out that through the advanced human-AI collaboration incorporated in knowlEdge, the project is especially targeting user acceptance of artificial intelligence. This is achieved, for example, through human-centred design, which involves iterative co-design processes to define user needs. It is also accomplished by consistently ensuring that users remain in the loop and are empowered to make AI-supported decisions. High user acceptance is key in the development of AI in virtually any deployment context. Therefore, the findings of the project are also transferable to other domains and industries.

What is your vision beyond knowlEdge?

The research and development of fundamental rules for interaction between humans and artificial intelligence in the project will have a long-term impact on the way industrial companies and their partners are managed in production networks. The technologies applied, including the overall deployment architecture, facilitate the decentralisation of activities. This innovative approach combines artificial intelligence processes with human intelligence “at the edge” and offers a new perspective on human empowerment in production.

The project acknowledges the fact that situational requirements can vary depending on the specific application context. By using the developed technologies, these situational requirements can be managed much more flexibly, resulting in more robust and resilient operations. This adaptability increases the overall efficiency and effectiveness of industrial processes.

It is important to point out that even long-term developments like the industrial metaverse ultimately depend on the pioneering work done in projects like knowlEdge. The metaverse, built on social interaction through the use of appropriate technologies, depends on the foundation laid by projects exploring human-AI interactions and advances in industrial processes. The insights and knowledge gained from knowlEdge are helping to shape the future of industrial management and technology integration.