The global push for sustainable energy has heightened the demand for green hydrogen, which is crucial for decarbonizing heavy industry. However, current electrolysis plant capacities are insufficient. This research addresses the challenge through optimizing large-scale electrolysis construction via standardization, modularization, process optimization, and automation. This paper introduces H₂Giga, a project for mass-producing electrolyzers, and HyPLANT100, investigating large-scale electrolysis plant structure and construction processes. Modularizing electrolyzers enhances production efficiency and scalability. The integration of AutomationML facilitates seamless information exchange. A digital twin concept enables simulations, optimizations, and error identification before assembly. While construction site automation provides advantages, tasks like connection technologies and handling cables, tubes, and hoses require pre-assembly. This study identifies key tasks suitable for automation and estimating required components. The Enapter Multicore electrolyzer serves as a case study, showcasing robotic technology for tube fittings. In conclusion, this research underscores the significance of standardization, modularization, and automation in boosting the electrolysis production capacity for green hydrogen, contributing to ongoing efforts in decarbonizing the industrial sector and advancing the global energy transition.

Due to its high complexity and the varied assembly processes, hybrid assembly systems characterized by human–robot collaboration (HRC) are meaningful. Suitable use cases must be identified efficiently to ensure cost-effectiveness and successful deployment in the respective assembly systems. This paper presents a method for evaluating the potential of HRC to derive automation suitability based on existing or to-be-collected time data. This should enable a quick and favorable statement to be made about processes, for efficient application in potential analyses. The method is based on the Methods–Time–Measurement Basic System (MTM-1) procedure, widely used in the industry. This ensures good adaptability in an industrial context. It extends existing models and examines how much assembly activities and processes can be optimized by efficiently allocating between humans and robots. In the process model, the assembly processes are subdivided and analyzed with the help of the specified MTM motion time system. The suitability of the individual activities and sub-processes for automation are evaluated based on criteria derived from existing methods. Two four-field matrices were used to interpret and classify the analysis results. The process is assessed using an example product from electrolyzer production, which is currently mainly assembled by hand. To achieve high statement reliability, further work is required to classify the results comprehensively.

In this article, software is developed to automatically evaluate the suitability of automated assembly of products. To achieve this, a product data structure is devised using the standardized AutomationML format, allowing for abstract product descriptions without the need for specific 3D CAD models. The developed evaluation system with its evaluation scheme is based on established methods. The basis of the textual description of the product and the abstraction of domain-specific knowledge with the help of fuzzy logic enables an innovative automated evaluation of the product design. By using fuzzy logic, subjective evaluation criteria can also be considered. For this purpose, a rule base comprising 21 evaluation criteria is established, resulting in 2430 unique rule combinations through effective grouping. In an initial evaluation of the developed software, three different fastening types from electrolyzer production were evaluated and compared in the context of instrument panels due to the manufacturing-like production. Here, the validation approach shows that the software can evaluate the suitability of the products for automation relative to the products under consideration. For a comprehensive validation, a comparison between the software evaluation and the evaluations of an expert panel is required, which will be carried out in later work.