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This research paper presents a comprehensive methodology for the design and implementation of worker assistance systems, with a focus on enhancing technology acceptance in industrial settings. A systematic literature review was conducted to analyze existing approaches, identify gaps, and define requirements for the methodology. The proposed methodology TERA-AS (Tasks, Environment, Relevance, Acceptance of Assistance Systems) begins with a detailed analysis of the initial working environment, capturing physical strain, task complexity, and job-specific conditions using a structured questionnaire and guidelines. A catalog of necessary assistance functions is then derived, and a system matrix matches these needs to 16 different assistance systems, facilitating the selection of an optimal solution based on a cost-benefit analysis. TERA-AS emphasizes employee involvement in system design and clear communication throughout the implementation process to foster technology acceptance. Therefore, this approach not only focuses on creating technologically and economically viable assistance functions, but also ensures technology acceptance. It was applied in a real-world industrial use case, specifically in control cabinet manufacturing. The tested system was a laser projection optical assistance system based on AI-generated positional data. Evaluation of the system showed significant time savings for manual assembly processes —approximately 69.05 % in wiring and 26.04 % in electrical assembly—despite involving untrained personnel. Feedback from operators highlighted both the system's effectiveness and areas for improvement, such as material provision and user interface design. Overall, TERA-AS provides a structured methodology to digital worker assistance system implementation, ensuring successful adoption through early employee engagement and continuous system improvement. • Review to identify gaps and establish requirements for an effective methodology. • Comprehensive methodology for designing and implementing worker assistance systems. • Applies system matrix to match identified needs to 16 different assistance systems. • Real-world application showed significant time savings with untrained personnel. • Provides a structured methodology to manage and process industrial information.