ArticleScientific reports2026
Adaptive human-robot collaboration in wind turbine manufacturing using digital twins.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
2 authors.
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Abstract
The push for higher wind turbine-rated capacity has spurred the development of larger generators, extended blade lengths, and taller towers. Wind turbines with capacities of up to 16 megawatts are available in the market, reflecting an almost 60% surge in design capacity over the past five years. However, due to frequent design changes and the diverse range of tasks involved, conventional automation methods are less practical, leading to a labor-intensive process. Handling and assembling these large components pose challenges to human capabilities. To address these challenges, this study proposes integrating collaborative robots (cobots) to develop a hybrid approach to automating wind turbine manufacturing. Employing cobots can reduce manufacturing costs, increase production speed, and improve working conditions. The article details the development of a mobile robotic assistant designed to collaborate with human operators during wind turbine assembly, based on a case study from a leading global wind turbine manufacturer. Besides highlighting the areas attractive for collaborative automation, the article's key contributions are to introduce a framework based on digital twin technology for the design, commissioning, and operation of robots. It also presents a human-robot interface using smartwatches to enable fluid interaction between humans and robots on production floors. The developed system can be scaled to other large-size component manufacturing involving intensive manual effort.
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