What the data for this category looks like
Supplier and process quality auditing for complete vehicle final assembly involves multi-source business data. Data sources include ERP/MES systems, VIN and configuration systems, supplier batch ledgers, tightening tools, EOL offline inspection lines, and quality traceability systems. Daily documents cover production orders, VIN lists, assembly work instructions, per-station tightening data, offline inspection reports, rework records, and consistency release documents. Data is generated in real time per vehicle and batched per shift. Core fields include VIN code, part batch number, torque value, inspection result, and station number. Units include newton meters, count, date, and other standard units.
What constraints these characteristics impose on deployment and upgrade
The real-time high-frequency data and full VIN-linked end-to-end characteristics of this category impose multiple constraints on deployment and upgrade. Multi-source heterogeneous data access requires adaptation to interface protocols of different systems, demanding flexible storage and connection parameter configurations. Real-time tightening and inspection data generated per vehicle creates high-concurrency requests, so database connection pool capacity must be sized to meet peak load. Upgrade processes must avoid interrupting VIN-linked quality data collection, as this could delay production tempo. Auditing under mixed-line production requires association of full documentation for individual vehicles, so knowledge base context caching and recall logic must adapt to VIN-centric association rules. This configuration applies to FastGPT v4.17.0.
How to set the configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
DB_MAX_LINK | 300–500 connections | Multiple types of quality data are generated in real time per vehicle, and a large number of concurrent requests occur per shift. Sufficient database connection pool capacity is required to support peak load |
MONGODB_URI | Authentication connection string for enterprise internal MongoDB cluster | Used to store VIN-linked quality auditing data, rework records and other business information, ensuring data persistence |
PG_URL | Connection address for enterprise internal PostgreSQL database | Used to store metadata for supplier batch ledgers and assembly work instructions, enabling fast retrieval by VIN |
STORAGE_S3_ENDPOINT | Access address for enterprise-grade object storage | Used to store large-volume documents such as tightening data and offline inspection reports, meeting storage requirements for massive files per shift |
FILE_TOKEN_KEY | 32-bit random encrypted string | Used to generate secure file access tokens, preventing unauthorized access to sensitive documents related to supplier quality auditing |
FE_DOMAIN | Dedicated internal enterprise secondary domain name | Deploys services in an internal network environment to avoid unauthorized external access to sensitive production quality data |
Three common mistakes
- Symptom: After deployment, the dedicated supplier quality auditing directory cannot be accessed, and the interface returns a 404 error. Cause:
FE_DOMAINis not correctly configured to point to the enterprise internal dedicated domain name, or the auditing page route is not added to the frontend access whitelist. - Symptom: Local code changes cannot be synchronized to the online deployment instance, and the auditing page does not update. Cause: The local code directory is not mounted via a Docker volume, or the corresponding service container is not restarted to apply code changes.
- Symptom: Database connection failures or port conflict errors occur when deploying with docker-compose. Cause:
MONGODB_URIorPG_URLis not correctly configured to point to the correct enterprise database instance, or a container port conflicts with another local process.
How to confirm the configuration is correct
- The configured
FE_DOMAINis accessed, and confirmation is made that the dedicated supplier quality auditing page loads normally, with no permission errors or 404 prompts. - An assembly work instruction corresponding to a real VIN is uploaded, and confirmation is made that the file can be stored normally and accessed via the storage service corresponding to the configured
STORAGE_S3_ENDPOINT. - Two consecutive quality auditing queries related to the same VIN are initiated, and confirmation is made that subsequent responses can associate previous VIN information.
- The database monitoring panel is viewed, and confirmation is made that the current database connection count does not exceed the configured
DB_MAX_LINKthreshold, with no connection alarms generated.
The values provided are common starting points and should be evaluated against the reader's own samples.