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Digital Simulation and Validation for Large Wind Turbine Blade Production Lines
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Service Hotline:+86-19174888669
Application Scenarios
1. Material Receiving Simulation: Simulates the entire process of truck‑delivered materials, including unloading by forklift and subsequent storage, optimizes the layout of unloading stations, and eliminates inefficiencies caused by workers waiting for material delivery.
2. Warehouse Picking and Scheduling Simulation: Replicates forklift outbound picking and secondary put-away operations, optimizes picking workflows, and reduces workers’ non-value‑added travel time for retrieving materials.
3. Workstation Material Delivery Simulation: The simulation demonstrates a forklift precisely delivering materials to process buffer zones, ensuring materials are delivered on demand and preventing assembly workers from idling due to material shortages.
4. Blade Blank Transport Simulation: Digitally simulates in‑plant transport routes for blade‑shaped blanks, identifies and resolves bottlenecks in material handling, and ensures a continuous supply of materials to the assembly process.
5. Closed-loop waste‑material transport simulation: Simulates the centralized collection, transfer, and recycling of empty packaging and scrap materials, preventing debris from occupying work space and improving on-site assembly efficiency for workers.
Application Results
This project leverages an industrial simulation platform to construct a full‑scale digital twin simulation model for a large wind turbine blade manufacturing workshop, enabling comprehensive multi‑dimensional simulations of production line process flows and on‑site logistics systems, as well as performance validation and three‑dimensional dynamic visualization. Based on a discrete-event simulation framework, the project replicates the entire manual assembly process of blade production and integrates intelligent multi‑objective optimization algorithms to iteratively determine the optimal coordination between workforce allocation and production capacity. This approach minimizes on‑site staffing while maximizing blade output efficiency, coordinates and optimizes workshop resource allocation, balances production rhythms, and supports the transformation and upgrading of the blade manufacturing workshop into a state‑of‑the‑art smart factory benchmark.
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