What the data for this category looks like
Normally, production ledger data for furniture and wood product manufacturing enterprises comes from order design systems, sheet and wood batch records, CNC cutting and drilling equipment logs, ERP/MES systems, and moisture content test data. Daily documents include order breakdown drawings, cutting lists, edge banding and drilling programs, coating process documents, hardware material lists, trial assembly and packaging records. Data updates occur by order, daily, or per material batch node. Fields include panel size, material batch, processing parameters, hardware model, moisture content value, and more. Common units are millimeters, cubic meters, and percentage.
Constraints imposed by these characteristics during deployment and upgrade
Custom order-driven production models create a large volume of highly personalized panels. Deployment must adapt parsing rules for multi-source heterogeneous documents. Data update frequencies vary, so a node-triggered incremental synchronization mechanism must be configured. Fields such as hardware and process have low standardization, so configuration space for custom field mapping must be reserved. Equipment logs and ERP data have significant format differences, so flexible structured data access adaptation must be supported.
How to Set Configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
DB_MAX_LINK | 120–150 connections | A single order corresponds to multiple panels, and frequent database access requires a stable connection pool |
STORAGE_S3_ENDPOINT | Enterprise internal object storage access address | Large production documents such as order breakdown drawings and process files must be stored |
REDIS_URL | Local private Redis instance address | Frequently called sheet batch and hardware list data must be cached to reduce database load |
FILE_TOKEN_KEY | 32-bit random encrypted string | Access permissions for sensitive documents such as order breakdown drawings and trial assembly records must be securely verified |
PG_URL | Calibrated based on actual testing | Structured production ledger data from ERP/MES must be connected, adapting to the enterprise's existing database architecture |
Three Common Mistakes
- Calling the reranker component returns false. Logs show the call succeeded but no valid output is produced. The cause is that the access key for the corresponding model is not configured, or the document parsing format does not match the reranker's input requirements.
- Setting a custom retrieval count of 6 via the API does not take effect. The system still returns a fixed number of entries. The cause is that the retrieval pool upper limit parameter corresponding to configuration items such as
DB_MAX_LINKwas not adjusted. - After upgrading to FastGPT v4.17.0, production ledger synchronization tasks cannot be triggered normally. The cause is that the adjustment content of incremental synchronization rules in the version update notes was not reviewed, and the corresponding configuration was not updated.
How to Verify Successful Configuration
- Submit a test order to verify that the system automatically pulls corresponding order breakdown drawings, cutting lists and other documents and completes indexing.
- Call the ledger summary interface to confirm that returned fields match the original production data.
- Check the cache instance status to confirm that frequently accessed sheet batch and hardware list data has been normally cached.
- Test the document rearrangement function to verify that the returned result is a valid sorted list of production documents.
The values provided are common starting points and should be measured against the reader's own samples.