Adaptive Labour Allocation and Productivity Modelling: AI-Based Workforce Optimisation Strategies in American Manufacturing Operations

Authors

  • Yasushi Wada Associate Professor of Mechanical Engineering, Tohoku University

Keywords:

adaptive labour allocation, productivity modelling, workforce optimisation strategies, american manufacturing operations, machine learning

Abstract

The American manufacturing sector is facing a critical war for talent. Predictions estimate that the United States will be short 2.1M skilled workers by 2030, equating to a $1 trillion loss in revenue. With labor costs accounting for 60% of all manufacturing costs, manufacturers are focused on exploring new initiatives to optimize their workforce utilization. Organizations that reimagine, rethink, and redesign how they execute their most vital tasks will emerge from the war for talent.

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Published

30-06-2021

How to Cite

[1]
“Adaptive Labour Allocation and Productivity Modelling: AI-Based Workforce Optimisation Strategies in American Manufacturing Operations”, Human-Computer Interaction Persp., vol. 1, no. 1, pp. 32–42, Jun. 2021, Accessed: Jun. 04, 2026. [Online]. Available: https://thesciencebrigade.com/hcip/article/view/782