Piontek, SimonSimonPiontekGäbler, MarcelMarcelGäblerLödding, HermannHermannLödding2025-01-132025-01-132024-05Procedia CIRP 58 (27): 427-435 (2024)https://tore.tuhh.de/handle/11420/52985Despite industrial production becoming more automated and digitalised, manual work remains indispensable. Work tasks are still largely carried out using conventional hand tools and paper-based documents, which leads to problems in productivity and quality. Smart hand tools can improve quality by controlling diameters, rotation speed or torque and documenting recorded feedback data. To do this, they need information on the current context, such as the tool's position or the production progress. In many cases, the context is either not integrated or is programmed statically into the tools with considerable effort. Digital assistance systems, on the other hand, gather and process data about the context in order to increase productivity by displaying information for conventional manual assembly processes. However, they do not support work processes carried out with smart tools. Integrating the tools into the assistance systems makes it possible to generate content and context for the tools in a generic and efficient manner, while also supporting value-adding and tool-dependent work tasks. This paper presents such an integrated digital assistance system in detail and validates it in a laboratory environment with regard to potentials and general usability.en2212-8271202427427435Elesvierhttps://creativecommons.org/licenses/by-nc-nd/4.0/Digital Assistance System | Digital Twin | IIoT | Smart ToolsTechnology::670: ManufacturingConference Paperhttps://doi.org/10.15480/882.1425210.1016/j.procir.2024.10.11010.15480/882.14252Conference Paper