Global supply chains (SC) face escalating disruptions from economic crises, geopolitical tensions, sanctions, and trade wars, exposing critical vulnerabilities that challenge traditional risk management strategies. While substantial research exists on SC resilience (SCRES) and SC robustness (SCROB), these attributes are typically examined in isolation, lacking an integrated assessment framework to enhance SC performance. This study bridges this gap by unifying SCRES and SCROB through a novel SC Resistance Index (SCRESIS Idx). This proposed index leverages digital twin (DT) technology and simulation-based analysis to quantify and evaluate SCRESIS. The methodology employs discrete-event simulation (DES) and agent-based modeling (ABM) to evaluate SC performance under disruptions. Findings demonstrate that integrating resilience and robustness enhances SC visibility, strategic agility, and operational efficiency, enabling proactive decision-making. Future research should evaluate the framework in real-world applications and investigate the integration of artificial neural networks (ANNs) to confirm simulation results through a cross-validation process. This would improve accuracy and strengthen the AI-driven SCRES and SCROB approach.