This paper investigates the effectiveness of dynamic switch-off policies in flow line production systems, aiming to balance energy efficiency and operational performance. A three-machine simulation model is developed and tested under steady-state and fluctuating processing conditions. The proposed policy, based on adaptive thresholds and Statistical Process Control (SPC) logic, is compared against two benchmarks: the traditional always-on model and a fixed switch-off policy. Simulation results demonstrate that the dynamic policy reduces customer-related performance measures—specifically queue lengths and waiting times—by approximately 50–56% compared to fixed policies. Crucially, this improvement is achieved while maintaining energy savings (~11%) and work-in-process reduction (~38%) comparable to the static approach. These benefits remain consistent even under high-variability scenarios, confirming the robustness of the proposed control architecture for Industry 4.0 sustainable manufacturing.
Enhancing Industry 4.0 Energy Efficiency: A Data-Driven Dynamic Control for Pull-Flow Lines
Renna, Paolo
2026-01-01
Abstract
This paper investigates the effectiveness of dynamic switch-off policies in flow line production systems, aiming to balance energy efficiency and operational performance. A three-machine simulation model is developed and tested under steady-state and fluctuating processing conditions. The proposed policy, based on adaptive thresholds and Statistical Process Control (SPC) logic, is compared against two benchmarks: the traditional always-on model and a fixed switch-off policy. Simulation results demonstrate that the dynamic policy reduces customer-related performance measures—specifically queue lengths and waiting times—by approximately 50–56% compared to fixed policies. Crucially, this improvement is achieved while maintaining energy savings (~11%) and work-in-process reduction (~38%) comparable to the static approach. These benefits remain consistent even under high-variability scenarios, confirming the robustness of the proposed control architecture for Industry 4.0 sustainable manufacturing.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
