High-Performance Computing Simulation of Digital Twin Synchronization in Smart Manufacturing Projects: A Quantitative Analysis of Edge-Cloud Architectures

Abstract

This study examined the problem of weak digital twin synchronization in smart manufacturing projects, where delayed data exchange, fragmented edge-cloud architecture, limited simulation capacity, and poor virtual-physical alignment reduce production visibility, decision quality, predictive maintenance, and project performance. The purpose was to quantitatively assess how high-performance computing simulation and edge-cloud architecture improve digital twin synchronization effectiveness and smart manufacturing project performance. A quantitative, cross sectional, case-based design was used with structured five-point Likert survey data from 180 valid respondents representing engineering operations, IT and automation, data systems, project management, production supervision, and cloud or enterprise smart manufacturing cases. The key variables were high-performance computing simulation capability, edge computing capability, cloud computing capability, edge-cloud integration, digital twin synchronization effectiveness, and smart manufacturing project performance. The analysis plan included descriptive statistics, Cronbach’s alpha reliability testing, normality screening, Pearson correlation, regression modeling, hypothesis testing, Edge-Cloud Synchronization Performance Index analysis, and HPC Simulation Readiness and Architecture Maturity Mapping. Findings showed high agreement across all constructs, with digital twin synchronization effectiveness recording the highest mean score, M = 4.15, SD = 0.58, followed by high-performance computing simulation capability, M = 4.12, SD = 0.61, smart manufacturing project performance, M = 4.10, SD = 0.62, edge computing capability, M = 4.08, SD = 0.64, cloud computing capability, M = 4.01, SD = 0.67, and edge-cloud integration, M = 3.96, SD = 0.69. Reliability was strong, with Cronbach’s alpha values ranging from 0.801 to 0.913. Correlation results showed that synchronization effectiveness was strongly related to project performance, r = 0.721, while edge-cloud integration was strongly related to synchronization effectiveness, r = 0.696. Regression results showed that technological capabilities explained 62.4% of synchronization effectiveness, adjusted R² = 0.624, while the full model explained 67.8% of project performance, adjusted R² = 0.678. The study implies that firms should invest in HPC simulation, edge processing, cloud scalability, and integrated architecture to improve synchronization, decision quality, and project efficiency.