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GrandhooMengxi New Energy Intelligent Solution
Overview
Due to the scattered storage of data in different organizations or institutions, there are situations in all industries where data cannot be effectively integrated and shared. Even within the same organization, there are different departments, teams or business units, and each department may have its own data management methods and systems, resulting in data being scattered and stored in different places, forming data silos. Moreover, different data formats, naming rules, etc. are used between multiple sources of data, resulting in poor data interoperability. In addition to this, data is often duplicated, redundant, inconsistent, etc., and needs to be cleaned and integrated. However, high-quality data analysis applications require accurate, diverse and real-time training data, so there is an urgent need for a solution that can integrate data from multiple sources in the industry, ensure consistency of data meaning and can be continuously updated.
The " Industry Data Standardization Solution " of Rock System supports automatic analysis of data characteristics, matching and identification of fields with the same meaning, management of field standards, formulation of industry common data specifications, entity disambiguation, entity fusion, automatic identification of related data, which helps to improve the quality and management efficiency of data, and promotes sharing and use of data, unleashing the potential value of data. and use, and release the potential value of data.
Challenges
The delivery time of the production line is tight, and the inspection cycle of the sub-capacity cabinet equipment is long
The production and manufacturing process has many nodes and complex processes, and material changes are greatly affected by market conditions.
Production link data is generated in real time, with large scale and high accuracy requirements
Periodic maintenance of equipment affects production efficiency
Architecture
Benefits
High precision
The system conducts in-depth correlation analysis on production data, identifies the main factors affecting battery capacity, predicts capacity performance under different production conditions, such as new battery capacity, old battery capacity degradation, etc., promptly discovers capacity problems during the production process, and takes corresponding measures. Measures are adjusted and improved to improve the overall capacity performance of the battery, and the capacity prediction accuracy error is ≤0.1%
High reliability
The system can adapt to the impact of production line processes caused by changes in materials or processes, monitor battery cell capacity predictions in real time, and automatically adjust the weight of the adaptation model and model parameters to ensure the accuracy of the predicted capacity and achieve more than 99% battery capacity prediction. Error ≤0.1%. At the same time, the system supports hot standby deployment to ensure high reliability in long-term operation on the production line
Digitizing
The system can adapt to the impact of production line processes caused by changes in materials or processes, monitor battery cell capacity predictions in real time, and automatically adjust the weight of the adaptation model and model parameters to ensure the accuracy of the predicted capacity and achieve more than 99% battery capacity prediction. Error ≤0.1%. At the same time, the system supports hot standby deployment to ensure high reliability in long-term operation on the production line
Visualization
The system helps users intuitively understand various changes and trends in the battery production process by visually displaying massive production data. Users can understand key indicators and data in the battery production process at a glance, including battery production change curves, battery forecast statistical charts, etc., helping users understand complex data information and quickly identify potential problems and anomalies.
Traceable
The system processes key data such as production process parameters and equipment testing in the production process in real time. Through specific data traceability, we can observe each battery in real time, quickly locate problems, and take timely adjustment measures, which greatly improves the controllability and production efficiency of the production process.
High energy saving
The system can help enterprises reduce equipment cost investment in the initial stage of production lines and lower industry entry barriers through cell capacity prediction. At the same time, it can save power consumption by saving on the steps of chemical composition and volume composition, achieving the purpose of energy conservation and emission reduction.