While IoT, big data, AI and machine learning technologies are increasingly applied to improve production process and management, predictive and advance warning mechanisms can be integrated with AI algorithms to help manufacturers better upgrade their automation capabilities and overall operating efficiencies, according to Allen Chen, deputy general manager of SAS Taiwan. Chen said that in incorporating AI and IoT into their manufacturing operations, most enterprises hope to get better decision-making support from the combination of AI and production process management while also pursuing improvements in prediction optimization, computer image recognition, visual operation and display, and data integration and management, so as to reduce operating cost. In terms of smart manufacturing alone, the incorporation of software programs integrating AI, machine learning and IoT applications can help the manufacturing end predict yield rates and provide advance warnings in case of poor equipment conditions. It can also help collect product information and environment data including temperatures and humidity at the customer end, so as to offer valuable references for better after-sales services and product upgrades. As a result, this will help manufacturers carry out digital transformation and production optimization at a faster pace, Chen said.