Predictive Scheduling and Skill-Task Matching Intelligence: AI-Based Workforce Optimisation Frameworks in American Aerospace Manufacturing

Authors

  • Daniel Nikulin Professor of Electrical Engineering, National Research University – Moscow Institute of Electronic Technology (MIET)

Keywords:

predictive scheduling, skill-task matching intelligence, workforce optimisation frameworks, american aerospace manufacturing, machine learning

Abstract

While AI techniques have not been widely adopted in the aerospace business due to their great complexity and interdisciplinary nature, this paper aims to explore AI fields and techniques. In the context of AI techniques in the aerospace industry, the AI-based tools discussed in this review are specifically curated for workforce optimization. In general, workforce optimization can encompass not only employee scheduling and training, but also planning factory operations.

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Published

31-12-2025

Issue

Vol. 5 No. 2 (2025): Human-Computer Interaction Perspectives

Section

Articles

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How to Cite

[1]
“Predictive Scheduling and Skill-Task Matching Intelligence: AI-Based Workforce Optimisation Frameworks in American Aerospace Manufacturing”, Human-Computer Interaction Persp., vol. 5, no. 2, pp. 24–32, Dec. 2025, Accessed: Jun. 04, 2026. [Online]. Available: https://thesciencebrigade.com/hcip/article/view/812