What the data for this category looks like
The data supporting equipment inspection and maintenance Q&A for lithium-ion cell manufacturing comes from raw material batch records, workshop MES systems, slurry and coating testing equipment, dew point monitoring devices, formation and grading cabinets, and laboratory testing equipment. Data update frequency aligns with the production rhythm of each battery batch and individual cells. Daily business documents include batching records, coating and calendering parameter tables, winding or lamination ledgers, liquid injection records, formation and grading data, OCV and safety test reports. Data fields cover professional electrochemical indicators such as slurry ratio, calendering thickness, ambient dew point value, and internal resistance parameters. Requirements for recording accuracy of moisture content and cleanliness are extremely high.
What constraints these characteristics impose on the deployment and upgrade phase
Data for this category is multi-source and dispersed, has high update frequency, and uses highly specialized fields. These traits create multiple constraints for the deployment and upgrade phase. Multi-source data requires storage configurations adapted to different access protocols to avoid data synchronization delays. High-frequency real-time data requests require optimization of database connection pool and cache configurations to prevent service overload. Identification of specialized fields requires preset matching rules to ensure the Q&A system accurately extracts business information related to cell manufacturing. Additionally, electrochemical systems have high data consistency requirements, so strict permission verification must be configured during deployment to prevent unauthorized access to sensitive test data.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
MONGODB_URI | mongodb://<admin account>:<password>@<database address>:<port>/fastgpt?authSource=admin | Adapts to multi-source real-time cell manufacturing data storage and supports high-concurrency read and write requirements |
REDIS_URL | redis://:<password>@<cache address>:<port>/0 | Caches real-time dew point monitoring and formation and grading cabinet data to reduce access pressure on the core database |
STORAGE_S3_ENDPOINT | Fill in according to the access address of the enterprise's own object storage service | Stores large-volume business documents such as coating and calendering images and OCV safety test reports |
DB_MAX_LINK | 180–250 connections | Matches the high-frequency data requests generated per battery batch to avoid database connection pool exhaustion |
FILE_TOKEN_KEY | Randomly generated 32-character string with no special characters | Protects the access security of uploaded inspection records and batching documents |
FE_DOMAIN | Front-end access domain name deployed within the enterprise | Restricts front-end access sources for the Q&A system to ensure internal data security |
Three common mistakes
- Symptom: After deploying the v2 version of the marker component, logs show an OCR error. Cause: No image preprocessing parameters adapted to lithium-ion cell manufacturing documents are configured, so the system cannot accurately identify specialized fields and formats in coating and calendering parameter tables and OCV safety test reports.
- Symptom: A missing configuration error is prompted after a newly deployed environment starts. Cause: Connection information for
MONGODB_URIorREDIS_URLis not filled in correctly, so the system cannot initialize core data storage and cache modules. - Symptom: No image understanding model option appears when creating a knowledge base in FastGPT v4.17.0. Cause: The image recognition plugin switch is not enabled in the system configuration, or the dependency packages for the corresponding model are not deployed.
How to confirm configurations are correctly set
- Run the system's built-in health check script to confirm that the connection status of core configuration items such as
MONGODB_URIandREDIS_URLis normal. - Upload a coating and calendering parameter record document to verify that the Q&A system can correctly extract field information such as slurry ratio and calendering thickness.
- Initiate a query related to equipment inspection to confirm that the system can return matching business content such as batching records and formation and grading data.
- Check the configuration of the front-end access domain name
FE_DOMAINto confirm that authorized internal personnel can normally access the Q&A system interface.
The values provided here are common starting points and should be evaluated against the reader's own samples.