A Digital Twin Framework for Computer Hardware Design and Assembly: A Risk-Prioritized Approach

Abstract The rapid growth of artificial intelligence applications has intensified the demand for high-performance computing (HPC) servers, driving the need for more efficient and economical manufacturing processes. However, modern HPC servers present significant challenges: complex architectures vulnerable to assembly damage, compressed development cycles, strict cost constraints, and supply chain vulnerabilities across numerous subcomponents including printed circuit board assemblies (PCBAs) and processor modules. To address these challenges, we propose a Risk-Prioritized Digital Twin (RPDT) framework that enables concurrent optimization of design and assembly processes. The framework integrates three core components: failure modes and effects analysis (FMEA), visual kinematic simulation (VKS), and tolerance analysis. FMEA identifies high-risk components and processes. The combination of VKS and tolerance analysis enables early-stage risk detection through the superposition of static design tolerances and kinematic process parameters. We validate the RPDT framework through an industry case study of the system hardware development for a high-density HPC server. The results show that the RPDT framework has the potential to reduce physical build iterations, minimize material waste, and prevent costly soft-tooling and prototyping cycles.