GENAI WORKBENCH: AI-Assisted Analysis and Synthesis of Engineering Systems from Multimodal Engineering Data

2026-02-27

AI Summary

This work addresses the critical gap in current engineering design platforms, which lack native systems engineering frameworks, leading to a disconnect between system-level requirements and component design and thereby increasing integration risks. To bridge this gap, the paper proposes a Model-Based Systems Engineering (MBSE) environment built on an open-source PLM platform that uniquely integrates multimodal engineering data with generative AI. By establishing a unified digital thread linking document semantics, B-rep geometry, and system relationship graphs, the approach enables AI-driven automatic requirement extraction and generation of system architectures such as Design Structure Matrices (DSMs). The methodology synergistically combines vision-language models, semantic extraction, geometric processing, and graph-based modeling to seamlessly connect systems engineering with detailed design workflows, offering a comprehensive foundation for data-driven, integrated intelligent engineering design.

Technology Category

• Cognitive Modeling & Cognitive Systems: Agent Architectures
• Intelligent Robots: Multimodal Perception & Sensor Fusion
• Computer Vision: Multi-modal Vision

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Social Networks and Social Media: Generative AI / large language models and their impact on social systems

Abstract

Modern engineering design platforms excel at discipline-specific tasks such as CAD, CAM, and CAE, but often lack native systems engineering frameworks. This creates a disconnect where system-level requirements and architectures are managed separately from detailed component design, hindering holistic development and increasing integration risks. To address this, we present the conceptual framework for the GenAI Workbench, a Model-Based Systems Engineering (MBSE) environment that integrates systems engineering principles into the designer's workflow. Built on an open-source PLM platform, it establishes a unified digital thread by linking semantic data from documents, physical B-rep geometry, and relational system graphs. The workbench facilitates an AI-assisted workflow where a designer can ingest source documents, from which the system automatically extracts requirements and uses vision-language models to generate an initial system architecture, such as a Design Structure Matrix (DSM). This paper presents the conceptual architecture, proposed methodology, and anticipated impact of this work-in-progress framework, which aims to foster a more integrated, data-driven, and informed engineering design methodology.

Problem

• systems engineering
• engineering design
• integration gap
• digital thread
• model-based systems engineering

Innovation

• GenAI Workbench
• Model-Based Systems Engineering
• Multimodal Engineering Data
• Vision-Language Models
• Digital Thread