In the context of Industry 4.0, simulation has emerged as a useful methodology for dealing with the complexity and dynamism of modern production systems. Simulating manufacturing processes is essential for optimizing the efficiency and flexibility of industrial systems. It enables the analysis and improvement of processes, serving as a key lever for innovation, optimization, and competitiveness in the Smart Factory era. This study focuses on the development of a simulation model for improving the Fischertechnik 4.0 Training Factory using AnyLogic® software. The model reproduces factory operations allowing risk-free testing of operational configurations and process improvements. By incorporating lean principles, the simulation model can identify and eliminate inefficiencies, streamline workflows, and reduce waste, leading to further enhancements in overall system performance. Key results reveal that targeted interventions significantly improve production performance, as evidenced by reductions in Production Lead Time, increases in Production Rhythm and Average Resource Utilization, and improvements in Overall Equipment Effectiveness (OEE).

Lean Simulation for Improving Production Scenarios: The FischerTechnik Case Study

Caterino, Mario;Rinaldi, Marta;
2025

Abstract

In the context of Industry 4.0, simulation has emerged as a useful methodology for dealing with the complexity and dynamism of modern production systems. Simulating manufacturing processes is essential for optimizing the efficiency and flexibility of industrial systems. It enables the analysis and improvement of processes, serving as a key lever for innovation, optimization, and competitiveness in the Smart Factory era. This study focuses on the development of a simulation model for improving the Fischertechnik 4.0 Training Factory using AnyLogic® software. The model reproduces factory operations allowing risk-free testing of operational configurations and process improvements. By incorporating lean principles, the simulation model can identify and eliminate inefficiencies, streamline workflows, and reduce waste, leading to further enhancements in overall system performance. Key results reveal that targeted interventions significantly improve production performance, as evidenced by reductions in Production Lead Time, increases in Production Rhythm and Average Resource Utilization, and improvements in Overall Equipment Effectiveness (OEE).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11591/586324
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