Core Viewpoint - The introduction of the TAOIX system's flight scheduling module by China Southern Airlines aims to enhance the efficiency and safety of operations during the peak summer travel season through comprehensive digitalization [1][2]. Group 1: Digital Transformation in Flight Scheduling - The new flight scheduling module utilizes operations research and artificial intelligence to improve task distribution and personnel matching, addressing inefficiencies in traditional scheduling methods [2]. - The module covers various maintenance scenarios, creating a closed-loop management system that enhances scheduling efficiency by reducing reliance on manual notifications [2][3]. - The intelligent scheduling algorithm and real-time monitoring capabilities allow for precise task and personnel matching, significantly improving the scientific and efficient nature of scheduling [2][3]. Group 2: Real-time Data Integration and Response - The module introduces a digital monitoring mechanism that connects with multiple data platforms, enabling a dynamic response system to flight changes [3]. - Automatic alert functions provide timely notifications to staff and management, facilitating quick task handling and improving overall operational efficiency [3]. - The system supports real-time tracking of key performance indicators, aiding in decision-making for scheduling strategies and resource allocation [3]. Group 3: Nationwide Implementation and Future Directions - The flight scheduling module has been successfully piloted in several bases, with significant improvements noted in monitoring and task management [4]. - The module has been rolled out to 17 maintenance units, expanding the coverage of digital scheduling [4]. - Future initiatives will focus on standardizing processes, digitizing management, and enhancing decision-making capabilities to further advance the digital transformation in maintenance operations [4].

Group 1 - The essence of digital supply chains lies in building capabilities for end-to-end integration and innovation, rather than merely applying specific technologies or tasks [2] - Three key suggestions for AI application in supply chains include establishing a foundation for data and process integration, avoiding an exclusive focus on large models, and combining AI with operations research for better decision-making [2][4] - The evolution of China's supply chain has gone through four stages, from execution-focused to strategic integration, user-centric digital connections, and now to building supply chain ecosystems [3] Group 2 - Current trends in supply chain management emphasize rapid response, resilience, reconstruction, and green low-carbon initiatives, all of which are fundamentally supported by digitalization [4] - Future supply chain capabilities will depend on deeper data integration and analysis, merging operations research models with AI technology to enhance decision-making processes [5] - Successful logistics companies have transitioned from human management to system management, focusing on optimizing data usage to improve employee experience and customer value [5] Group 3 - The diversification of channels leads to order fragmentation, with many brands unaware of the full fulfillment path, resulting in high costs and inefficiencies [6] - AI and big data analytics play a crucial role in optimizing supply chain operations, such as determining warehouse locations and balancing inventory levels [6] - Multi-point intelligent supply chains utilize AI for efficient route planning and inventory management, significantly improving operational metrics like delivery efficiency and stock availability [7]