• Formal modeling of production processes using Petri nets and related formalisms to capture concurrency, state transitions, and real-time control in flexible manufacturing systems [3], [11].

• Hierarchical control and scheduling architectures that organize decision-making across levels (policy, planning, execution) to handle disruptions and dynamic demand in manufacturing systems [9], [15], [12].

• Flexibility as a design objective: measures, architectures, and practices to absorb product variety and demand variability, including measures of flexibility and WIP/inventory considerations [6], [14], [13].

• Optimization and control under uncertainty: nonlinear production planning, optimal control of production rate, and hedging-point policies to balance inventory and backlog [1], [4], [8].

• Simulation and performance evaluation of manufacturing systems: simulation studies, mean-value analysis, and heuristic methods to assess design, scheduling, and control policies [20], [17], [12].