Trustworthy Smart Fabs via Professional Proxies: Scaling Safe and Sustainable by Design (SSbD) through Industrial Data Spaces
2026-06-08 • Cryptography and Security
Cryptography and SecurityArtificial IntelligenceComputational Engineering, Finance, and ScienceComputers and SocietyHuman-Computer InteractionSocial and Information Networks
AI summaryⓘ
The authors explain that new European rules for making advanced computer chips create big challenges for factories to share sustainability data while keeping secrets safe. To solve this, they propose a secure system where specialized digital agents work inside trusted hardware zones to manage data automatically. This system lets factories prove they follow rules without revealing sensitive process details, using secure data sharing and machine learning. Their approach helps companies meet green goals while protecting their valuable information.
Safe and Sustainable by Design (SSbD)Corporate Sustainability Due Diligence Directive (CSDDD)Carbon Border Adjustment Mechanism (CBAM)Trusted Execution Environments (TEEs)Virtual Metrology (VM)Federated Machine Learning (FML)Data Sovereignty ParadoxInternational Data Spaces (IDS)Industry 5.0Smart Fabs
Authors
Han-Teng Liao, Chang-Yi Kao, Karen Ang
Abstract
The convergence of the 2026 European Union Safe and Sustainable by Design (SSbD) framework, Corporate Sustainability Due Diligence Directive (CSDDD), and Carbon Border Adjustment Mechanism (CBAM) introduce a severe governance bottleneck for advanced semiconductor manufacturing facilities ("Smart Fabs"). Regulatory compliance demands have surpassed the capacity of manual corporate reporting, creating a direct conflict between multi-stakeholder transparency and corporate data privacy. This paper addresses this challenge by introducing a zero-trust socio-technical orchestration framework that operationalizes a six-layer SSbD reference architecture within trustworthy industrial data spaces. We propose a shift from reactive automation to autonomous governance through "Professional Proxies"-role-based agentic workflows executing within hardware-isolated trust zones. Structured as an interoperable network protocol stack, the framework coordinates an automated, five-step "relay race" between Facility, Process Engineering, and Finance proxy teams to align factory-floor yield models with macro-level sustainability mandates. By executing Virtual Metrology (VM) predictions and Federated Machine Learning (FML) inside hardware-rooted Trusted Execution Environments (TEEs), this architecture resolves the Data Sovereignty Paradox, demonstrating how fabs can export cryptographically signed compliance tokens via International Data Spaces (IDS) connectors without exposing proprietary process recipes. Ultimately, this framework provides technology managers with a verifiable, evidence-based pathway toward resilient, net-zero Industry 5.0 ecosystems.