Produzione scientifica
su MBD e manifattura digitale

Journal of Intelligent Manufacturing (2026)

Semantically Enriched CAD Models for Digital Manufacturing: A Systematic Review of Model-Based Definition

Pacini A., Lupi F., Lanzetta M.

The digitalization of manufacturing processes has been driven by the evolution of Computer-Aided Design (CAD) software over the past half-century, transitioning from 2D, paper-based drawings to 3D, model-centric environments. Central to this transformation is the concept of the digital thread, which facilitates interconnected and seamless information flows across the product lifecycle. Realizing this vision from an operational perspective requires a robust information carrier capable of storing and transmitting essential information through a consistent data structure. Model-Based Definition (MBD) addresses this need by embedding semantic information directly into 3D CAD models, thereby supporting streamlined information exchange and aiming to replace traditional 2D documentation in Model-Based Enterprise (MBE) environments. Given the prominence and transformative potential of MBD, this study presents a systematic literature review covering two decades of fragmented research across diverse manufacturing processes and domains, offering a structured reference to unify prior efforts and support future implementation. The analysis of 132 systematically selected high-quality references from Scopus, Web of Science, leading software vendors, and national and international standards ensures a comprehensive and up-to-date synthesis. By consolidating key findings, this review delivers a state-of-the-art overview and outlines a roadmap for adoption in modern intelligent manufacturing systems. Particular attention is given to unmapped areas, laying a solid foundation for future research and standardization efforts, ultimately unveiling a potential game changer for the digital thread in manufacturing across sectors, organizational scales, and geographic regions.

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Preprint (2026)

The X-Formats Family: Linking Geometry and Semantics for Product-Centric Engineering Data Management

Pacini A., Lupi F., Lanzetta M.

Machine-readable semantic information, such as simulation settings, inspection configurations, machine parameters, process outcomes/logs, is central to digital manufacturing, enabling automation, interoperability, data traceability, and adaptive reconfiguration across the product lifecycle. When anchored to specific geometric entities, these semantic structures form the backbone of Model-Based Definition (MBD), a data engineering architecture in which the CAD model acts as the single source of truth to realize the digital thread. Within this architecture, both rule-based and machine-learning pipelines can orchestrate simulation, optimization, and control tasks using shared, semantically enriched models. Despite this potential, most engineering file formats either lack expressive, machine-readable semantics or encode them in ways that are format-specific, difficult to adapt to different needs, and hard to reuse. This letter presents a manifesto for the eXtended Formats (X-Formats) family, a lightweight stand-off markup approach that links structured annotations to engineering files without modifying the original source. Semantics can be defined independently of the underlying syntax (e.g., STL, B-rep, STEP, and DXF for CAD; PNG, JPEG, GIF, and SVG for images; MP4 and MOV for videos; GeoTIFF for geospatial data) and are anchored to file-specific entities that can be detected by external feature-extraction mechanisms. X-Formats structure semantics in a three-level hierarchy composed of property, layer, and schema, which is fundamental for supporting modular dataset design and allowing rapid customization across domains by replacing only the geometry-descriptor block. This letter introduces the core architectural principles, anchoring strategy, supporting tooling, and broader implications of this novel, product-centric, approach to engineering data management.

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