Engineering Smart Manufacturing Systems to Address Labor Shortages in U.S. Industry: A Scalable Framework for Workforce Resilience and Productivity

Abstract

Labor shortages have emerged as a significant challenge for the U.S. manufacturing sector, affecting production efficiency, workforce stability, and organizational competitiveness. In response, smart manufacturing technologies have gained increasing attention as strategic tools for improving productivity while reducing operational dependence on scarce labor resources. This study investigated the influence of Smart Manufacturing Systems on Industrial Productivity, with Workforce Resilience serving as a mediating variable and Labor Shortage Severity acting as a moderating variable. A quantitative, explanatory, cross-sectional research design was employed using survey data collected from 412 manufacturing professionals representing automotive, aerospace, electronics, food processing, pharmaceutical, machinery, and industrial equipment industries across the United States. Data were analyzed using SPSS and Partial Least Squares Structural Equation Modeling (PLS-SEM) to examine direct, indirect, and moderating relationships among the study variables. The findings revealed that Smart Manufacturing Systems had a significant positive effect on Industrial Productivity (β = 0.451, p < 0.001) and Workforce Resilience (β = 0.638, p < 0.001). Workforce Resilience also demonstrated a significant positive influence on Industrial Productivity (β = 0.426, p < 0.001), confirming its role as an important organizational capability within digitally enabled manufacturing environments. Mediation analysis indicated a significant indirect effect of Smart Manufacturing Systems on Industrial Productivity through Workforce Resilience (β = 0.272, p < 0.001), demonstrating partial mediation. The moderation analysis further showed that Labor Shortage Severity significantly strengthened the relationship between Smart Manufacturing Systems and Workforce Resilience (β = 0.183, p < 0.001). The structural model explained 45.1% of the variance in Workforce Resilience (R² = 0.451) and 63.5% of the variance in Industrial Productivity (R² = 0.635), indicating strong explanatory power. Effect size analysis revealed that Smart Manufacturing Systems exerted large effects on both Workforce Resilience (f² = 0.491) and Industrial Productivity (f² = 0.336). The study concluded that smart manufacturing technologies significantly enhanced industrial productivity through both direct technological benefits and indirect workforce-related mechanisms. The findings provide empirical evidence that integrating advanced manufacturing technologies with workforce resilience capabilities offers an effective framework for addressing labor shortages and sustaining productivity performance in U.S. manufacturing organizations.