Session | ||
Data-Driven Platforms and Applications in Production and Logistics: Digital Twins and AI for Sustainability
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Presentations | ||
Applying Machine Learning for Adaptive Scheduling and Execution of Material Handling in Smart Production Logistics KTH Royal Institute of Technology, Sweden Exploring Economic, Environmental, and Social Sustainability Impact of Digital Twin-based Services for Smart Production Logistics 1Sungkyunkwan University, South Korea; 2KTH Royal Institute of Technology, Sweden Design and Implementation of Digital Twin-Based Application for Global Manufacturing Enterprises 1Sungkyunkwan University, Korea, Republic of (South Korea); 2Advanced Institutes of Convergence Technology, Korea, Republic of (South Korea); 3Yura, Korea, Republic of (South Korea); 4DEXTA Inc., Korea, Republic of (South Korea) Assembly line worker assignment and balancing problem with positional constraints KAIST, Korea, Republic of (South Korea) When Softbots meet Digital Twins: Towards Supporting the Cognitive Operator 4.0 1Federal University of Santa Catarina, Brazil; 2Tecnológico de Monterrey, Mexico; 3University of Southern Santa Catarina, Brazil |