What the data for this category looks like
PCB manufacturing production ledger data sources include Gerber files, drill files, and BOM lists provided by customers, plus engineering production instructions, drilling and lamination parameters generated by CAM, and laboratory and equipment-collected data such as bath chemistry test results, AOI reports, electrical test reports, and slice reports. Data is updated per production batch, per shift, or continuously. It covers business documents across engineering, production, quality control, and laboratory roles. Fields include professional parameters such as drill hole diameter, lamination temperature, and bath concentration. Formats include structured tables and unstructured reports.
What Constraints These Characteristics Impose During Deployment and Upgrade
Multi-source heterogeneous ledger data from PCB manufacturing requires support for multi-format file parsing and structured storage during deployment. Configure STORAGE_S3_ENDPOINT to store original attachments such as Gerber files and AOI reports. High-frequency production batch updates create concurrent write pressure. Adjust database connection pool parameters to avoid connection exhaustion. Ledgers associated with multiple processes require metadata caching to improve query efficiency. Configure REDIS_URL to build a stable caching service. Ledger fields include professional unit parameters. Configure a structured database to store field validation rules to avoid data format errors during deployment.
How to Configure Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
MONGODB_URI | mongodb://username:password@host:27017/pcb_prod?authSource=admin | Stores structured ledger data associated with multiple processes, requires specifying the business database and authentication source |
REDIS_URL | redis://:password@host:6379/0 | Caches frequently accessed production batch ledger metadata to reduce database query pressure |
STORAGE_S3_ENDPOINT | http://s3-cn-south-1.example.com | Stores original ledger attachments such as Gerber files and AOI reports, must match the object storage service address |
DB_MAX_LINK | 200 | Handles high-frequency database write requests from continuous shift-based collection to avoid connection exhaustion |
PG_URL | postgresql://username:password@host:5432/pcb_measure?sslmode=require | Stores structured measurement data with units such as bath chemistry tests and electrical tests, requires support for transactional updates |
ROOT_KEY | Set based on actual measurement | Enables plugin loading permissions to ensure that plugins such as file processing functions can be registered normally |
Three Common Misconfigurations
- Issue: Running the docker command to start the marker_images container returns port occupation or image pull failure. Cause: Port 7231 was not opened in advance, or the image repository permission configuration is incorrect.
- Issue: After upgrading to FastGPT v4.17.0, an error occurs when importing Gerber format ledger files via URL. The backend log prompts
cannot fetch internal url. Cause:FE_DOMAINwas not configured as the service domain accessible within the factory intranet, causing internal URL verification to fail. - Issue: File processing plugins cannot be found in the backend plugin list. Cause: The corresponding plugin directory was not mounted during deployment, or
ROOT_KEYwas not configured to enable plugin permissions, causing plugin loading to fail.
How to Verify Proper Configuration
- Run a database connection test command to verify the connectivity of the configurations set for
MONGODB_URIandPG_URL, and confirm that the corresponding business databases can be read and written. - Start the Redis service and run the ping command to verify that the caching service configured via
REDIS_URLcan connect normally. - Upload a test Gerber file, and use the ledger import function to verify that the storage service configured via
STORAGE_S3_ENDPOINTcan receive and read files normally. - Restart the FastGPT service and check the backend logs to confirm that there are no errors related to database connection timeouts or plugin loading failures.
The values provided are common starting points and should be measured against the reader's own samples.