What kind of factory can represent the most advanced production site and manufacturing level of the photovoltaic manufacturing industry? In 2019, JinkoSolar carried out a pilot project of smart production solutions at its Shangrao base; in 2020, as part of the five-year strategic plan, JingkoSolar Branch selected two of the 11 factories in the world to focus on the transformation. The new factory adopts a fully automated manufacturing process, equipped with machine learning and artificial intelligence equipment automatic optimization system, intelligent self-maintenance system and intelligent production real-time status monitoring system, combined with cloud computing, manipulators, robots, sensor equipment, unmanned transport vehicles, large Data and machine self-learning, etc., allow machines to "communicate" with each other to create a more flexible production base.
A unified quality monitoring platform and the use of the same software language and protocol can facilitate the use of all employees, which can also make it easier to control costs and speed up production, and share knowledge and best practices among factories.
There are still great challenges in the process of transforming a single factory pilot project into a global deployment, and this can precisely reflect the true advantages of digitalization, especially the smart factory project requires an IT team, a factory operation management team, and internal technology. The personnel have very close cooperation. In the next 3 to 5 years, this "best practice" factory will update the IT system architecture and upgrade the automated assembly line based on all Jinko's existing production bases and production lines, so as to achieve further intelligentization of the factory floor and realize the realization of machines. The interconnection and intercommunication between machines, machines and people, and between people, to achieve the integration of the six streams of information flow, capital flow, technology flow, personnel flow, material flow and process flow, and on this basis Develop big data applications to enhance innovation, analysis and decision-making capabilities in manufacturing scenarios.