The rapid evolution from Industry 4.0 to Industry 5.0 is reshaping modern industrial systems by combining advanced digitalization with human-centric, sustainable, and resilient paradigms. While Industry 4.0 has focused on automation, cyber-physical systems, artificial intelligence, and data-driven decision-making, Industry 5.0 extends this vision by emphasizing human–machine collaboration, ethical AI, and sustainable value creation. In this context, optimization, control theory, and dynamical systems play a fundamental role as the mathematical backbone enabling the design, analysis, and operation of complex intelligent systems. These mathematical frameworks are essential for addressing challenges such as real-time decision-making, system stability, uncertainty management, and multi-objective performance in highly interconnected environments.
Discrete stochastic optimal control for multi-stakeholder
governance of crop rotation and fallow insurance
An integrated partial least squares structural equation modeling, artificial neural network, and importance–performance map analysis framework for Industry 4.0 readiness in university startups
