In traditional manufacturing, increasing production line capacity often involves physical trials, leading to downtime, high costs, and operational risks. This paper presents a bidirectional digital twin developed for the Fischertechnik Smart Factory Kit, enabling real-time simulation and validation of production line modifications before actual deployment.
The digital twin integrates with a Siemens PLC to mirror real-world operations, capturing live production data and visualizing key parameters like cycle time and machine utilization in a 3D environment. Engineers can test various optimization scenarios adjusting conveyor speeds, optimizing robot paths, and modifying buffer sizes to enhance efficiency. The best-performing configurations are identified based on throughput, cycle time, and resource utilization, and validated changes are automatically deployed to the PLC, ensuring seamless implementation.
Beyond capacity optimization, this solution improves overall production efficiency by minimizing idle time, balancing workloads, and reducing unplanned disruptions. Additionally, by simulating product variations and process changes virtually, the digital twin helps in identifying design simplifications, reducing product complexity, and streamlining manufacturing workflows.
Many manufacturers currently rely on multiple siloed solutions for predictive maintenance, production efficiency monitoring, simulations, and analytics, resulting in data integration challenges, inconsistent insights, limited real-time visibility, increased operational costs, and inefficiencies in decision-making and scalability. A digital twin of the manufacturing system acts as an integrated solution, combining all these capabilities in real time. By bridging technology gaps and providing a unified view of the entire production process, it enhances decision-making, maximizes resource utilization, and ensures seamless technology adoption across the factory.
This approach significantly reduces downtime, accelerates decision-making, and enhances automation, demonstrating the potential of digital twins in optimizing manufacturing processes.
Keywords:
Digital Twin, Smart Manufacturing, Siemens PLC, OPC UA, Predictive Maintenance, Industrial Automation, AI-based Production Planning, Industry 4.0