Imagine a smart assistant that knows exactly when to take over a boring or dangerous task and when to step back and let the human lead. It uses a digital mirror of the workplace to figure out the best balance in real-time based on how confident the machine is and how the person is doing. This keeps workers from getting stressed while making sure the job gets done faster and safer.
Modern organizations struggle to find the right balance between human effort and machine automation in unpredictable environments. This leads to employee stress, inefficiency, and a lack of trust in AI decision-making.
A digital twin service platform and software building blocks for Sliding Work Sharing (SWS) that adjust the human-robot task balance in real-time.
If you are a warehouse operator dealing with repetitive manual sorting and high employee burnout — this project developed a sliding work-sharing system that shifts tasks between humans and robots based on the situation. This reduces stress on employees and increases work efficiency.
If you are a hospital facility dealing with complex decision-making and staff shortages — this project developed a digital twin service platform that supports operators in diverse tasks. This increases confidence in the decision-making process for medical staff.
If you are a smart farm equipment provider dealing with unpredictable outdoor environments — this project developed software building blocks for sliding work sharing. This allows robots to handle tedious labor while humans manage complex exceptions.
Based on available project data, no specific pricing or cost structures are provided as the project is currently in the research and development phase.
Yes, the project is designed for industrial scale, utilizing 6 pilots across diverse sectors including manufacturing and logistics to ensure the tools work in real-world environments.
Based on available project data, specific licensing terms are not listed, but the project involves a consortium of 18 partners including 9 industry members.
The project develops a digital twin service platform and software building blocks designed to be applied across different AI and robotics services in various sectors.
The project runs from 2024-01-01 to 2026-12-31, with current activities focused on defining technical specifications and requirements.
The project features a strong commercial orientation with a 50% industry ratio, comprising 9 industrial partners (including 6 SMEs) and 6 universities. This balance suggests a high likelihood of practical application, as the research is directly tied to the needs of 18 partners across 8 different countries.
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