Data profile for this category
This category covers end-to-end injection molding processes. Data sources include resin batch property sheets, injection molding machine operating parameters, mold temperature controller data, workshop MES systems, and dimensional and appearance inspection equipment. Daily documents include injection molding process cards, raw material drying records, mold histories, first-piece inspection forms, patrol inspection logs, and material change and machine cleaning records.
Data updates are triggered by production batches, mold changes, material swaps, and shift operations. Fields include raw material batch numbers, drying temperatures, holding pressures, cooling durations, and corresponding units: degrees Celsius, seconds, megapascals.
Constraints during deployment and upgrade
Multi-source heterogeneous production data access requires adaptation to protocols and data formats of different devices. Reserve dedicated data parsing nodes during deployment to support upload of various parameter sets. Frequently updated production data requires the deployed knowledge base system to support low-latency synchronization. Optimize incremental update logic during upgrades to avoid overwriting audit data from historical batches.
Uniform validation rules must be configured for unit and format requirements of specific fields. This prevents audit logic failures for defects such as shrinkage and short shots caused by format mismatches. Mixed indexing for multiple document types must adapt to different structures of process cards, records, and other document formats. Adjust indexing strategies during upgrades to match differences in document lengths, ensuring retrieval accuracy.
Configuration settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
DB_MAX_LINK | 100–150 connections | Adapts to concurrent connection demands for multi-source data, preventing data synchronization interruptions caused by insufficient connection counts |
MONGODB_URI | Dedicated database address pointing to workshop production data | Isolates production data from other business data, ensuring accuracy of data sources for audit logic |
REDIS_URL | Configured as a local cache node address, with cache duration set to 300 seconds | Reduces response time for high-frequency queries, supporting high-volume audit data calls during shifts |
STORAGE_S3_ENDPOINT | Bound to the object storage endpoint for workshop document storage | Unifies management of indexing and reading for documents such as injection molding process cards and drying records |
FE_DOMAIN | Configured as the access domain name of the internal audit system | Ensures document links referenced by the knowledge base work normally in audit scenarios |
Three common misconfigurations
- Symptom: PDF parsing times out, but parsing service logs indicate success. Cause:
STORAGE_S3_ENDPOINTis not configured to point to workshop document storage. The knowledge base cannot pull PDF files such as injection molding process cards normally, triggering the timeout logic. - Symptom: Docker-deployed services display abnormal prompts every 30 minutes, and recover after restart. Cause: Connection parameters for the cache node configured in
REDIS_URLare incorrect. Session cache fails periodically, triggering service exception alerts. - Symptom: After upgrading to FastGPT v4.17.0, the system still shows the old version number. Cause: The front-end static resource package was not updated, or
FE_DOMAINis configured to point to the deployment directory of the old version. Version verification fails as a result.
How to verify correct configuration
- Run a multi-source data synchronization test. Check whether injection molding machine parameters and mold temperature controller data can be imported into the knowledge base normally. Confirm the validity of connections for
MONGODB_URIandREDIS_URL. - Upload a PDF file of an injection molding process card. Verify that parsing and indexing work normally. Confirm that
STORAGE_S3_ENDPOINTis configured correctly. - Trigger a supplier quality audit process. Check whether referenced document links can be accessed normally. Confirm that
FE_DOMAINis configured correctly. - Check the system version log. Confirm that the FastGPT v4.17.0 version identifier has been loaded. Verify that the upgrade operation took effect.
The values given are common starting points and should be measured against the reader's own samples.