Year: 2026
Type: article
Abstract: As Digital Twins gain importance in mechanical and plant engineering, the need for structured, interoperable, and machine-interpretable product information becomes increasingly apparent. This development highlights a long-standing challenge. Technical Documentation, although an integral component of products and essential for legal compliance and knowledge transfer, is still predominantly created in static and insufficiently accessible formats. Such formats limit its contribution to Digital Twin implementations and, more broadly, its potential value within digital manufacturing ecosystems. To better understand this discrepancy and identify pathways for strengthening the role of Technical Documentation, an interview study with experts from mechanical and plant engineering was conducted. Using Kuckartz’s structuring qualitative content analysis, the study reveals key challenges and requirements related to enhancing Technical Documentation for Digital Twin integration and enabling new use cases for artificial intelligence. Above all, the results show that heterogeneous cultural and legal frameworks in global target markets and the difficulty of obtaining accurate information for creating and updating Technical Documentation are central barriers that necessitate a holistic organizational knowledge strategy as well as interorganizational standards and processes. Based on these findings, measures for the further development of Technical Documentation in Digital Twin contexts are derived and presented. Taken together, the contribution of this article is to form a structured basis for conceptualizing a reference process for Technical Documentation, which in turn constitutes an essential step toward establishing a standardized documentation scheme.
Source: Procedia CIRP
Institutions: TU Dortmund University, University of Technology Sydney
Language: English
Subfield: Industrial and Manufacturing Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W7207850723