Future Factory

• 15.30-15.50: Automation Technology for G1c Testing Based on Intelligent Detection by Bin WANG, General Manager, LSI Systems and CTO, Sampe China

Model interlaminar fracture toughness is an important physical property between the layers of composite materials, which is closely related to the interface debonding and layered failure of materials. Crack Monitoring of Fracture Toughness System Based on Damage-recognition Algorithm of Intelligence Vision, the deep neural network is used to accurately extract the effective features of cracks, and realize the pixel positioning of tiny cracks in the large field of view. The test process is simplified and the test results are automated, which greatly improves the accuracy of data and improves the test efficiency. 

• 15.50-16.10: Automation for Competitive Advantage – A Path to Component Fabrication with Reduced Touch Labor and Improved Quality by Mel CLAUSON, Director of Business Development, Composite Resources, SAMPE North America

Processing of Thermoset and Thermoplastic Composite Components frequently remains a high touch labor activity. This drives not only higher costs but the potential for quality defects. How can engineering design and automation be implemented to alleviate this for several geometric constructs?

• 16.10-16.30: Cutting Edge Automated CFRTP Fuselage Skin Panel Fabrication Process by Naoki SHIMADA, Kawasaki Heavy Industries, SAMPE Japan

In this presentation, innovative manufacturing process developed by Kawasaki Heavy Industries (KHI) that contributes to automated and high-rate production of thermoplastic composite skin panels for aircraft will be introduced. This process, called “local co-consolidation,” enables the automated and high-rate production of large-scale skin panels with complexity equivalent to traditional thermoset composite skin panels without using an autoclave. 

• 16.30-16.50: DTU’s Large AI Models and High-Performance Simulations for Wind Turbine Blade Damage Inspection and Assessment by Pr. Xiao CHEN, Head of Section, Structural Virtual Testing and Digitalization, DTU Denmark, SAMPE Europe  

This talk presents DTU’s latest research and innovation on large AI models and high-performance simulations to detect and analyze damage in composite wind turbine blades. Use case demonstrations to showcase advanced computer vision techniques for inspecting blade damage and high-performance simulations for assessing damage criticality in seconds.