What data for this category looks like
Data for this category typically comes from CAD/CAM software, order BOM systems, sheet metal inventory ledgers, laser cutting machine and bending machine device logs, and workshop MES systems. Daily generated documents include sheet metal unfolding drawings, CNC cutting programs, bending process cards, nesting drawings, first-piece inspection records, and process transfer cards. Data update rhythms follow order delivery, daily production scheduling, and equipment changeover adjustments. Common fields include sheet metal specifications, bending compensation coefficients, process transfer status, device operating parameters, and order numbers. Common units are millimeters, kilograms, pieces, and hours.
Constraints imposed by these characteristics during deployment and upgrade
The multi-source heterogeneous data characteristics of sheet metal cutting and bending require deployment to support data access in multiple formats such as CAD drawings, device logs, and BOMs. Unified parsing rules for cross-data sources must be pre-configured. The high-frequency update rhythm requires adjusting data synchronization frequency during deployment. This balances real-time performance and server resource usage, avoiding performance degradation caused by frequent synchronization. The multi-variety, small-batch business model leads to non-fixed ledger fields. Flexible metadata adaptation capabilities are required to support on-demand addition of ledger fields. The storage and parsing requirements for large-scale engineering drawings require adjusting file storage and index configuration parameters during upgrades. This avoids processing failures caused by oversized files.
Configuration Settings
The following configurations are based on FastGPT v4.17.0.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
REDIS_URL | redis://default:yourpassword@redis-server:6379/0 | Used to cache nesting calculation results and real-time process status, ensure low-latency ledger queries, and adapt to high-frequency data update requirements |
STORAGE_S3_ENDPOINT | http://minio.internal:9000 | Stores large-scale engineering files such as sheet metal unfolding drawings and nesting drawings, adapting to private cloud deployment storage requirements |
DB_MAX_LINK | 20–30 | Adapts to multi-source database concurrent access, avoiding ledger generation failures caused by exhausted connection pools |
| File upload size limit | 1000 MB | Compatible with upload requirements for large CAD drawings and nesting drawings, matching the document size characteristics of this category |
| Data synchronization cycle | Every 15 minutes | Matches the update rhythm of orders and equipment changeovers, balancing real-time performance and server resource usage |
FE_DOMAIN | https://fastgpt.yourdomain.com | Configures the frontend access address to ensure normal generation and display of ledger reports |
Three common configuration errors
- Symptom: Image download times out or is interrupted when executing
docker-compose pull, with runtime significantly longer than expected. Cause: Domestic mirror sources are not configured to speed up pulls, and dependent images are not pre-cached during private deployment. - Symptom: Duplicate ledger data generation occurs after starting multiple service replicas. Cause:
REDIS_URLis not configured to implement distributed locks, leading to repeated execution of concurrent tasks. - Symptom: After uploading a nesting drawing, the knowledge base index speed is too slow to generate corresponding ledgers in a timely manner. Cause: Index parameters are not adjusted for large-scale engineering drawings, leading to excessively long parsing and indexing times.
How to confirm successful configuration
- Execute
docker-compose up -d, then usedocker psto check that all containers are in healthy status, with no abnormally exited logs. - Upload a sheet metal unfolding drawing, confirm that the system can normally parse and generate ledger fields including sheet metal specifications and bending coefficients, with no parsing failure errors.
- Start 2 service replicas, submit ledger generation tasks for 3 different orders, confirm that there is no duplicate data or task conflicts.
- Access the frontend page corresponding to
FE_DOMAIN, confirm that the preset ledger report template loads normally, and a complete report is generated by associating the corresponding data sources.
The values provided are common starting points and should be measured against the reader's own samples.