What the data for this category looks like
Core data for this category covers full-process injection molding documentation and real-time production data. Daily documentation includes injection molding process cards, raw material drying records, mold histories, first-piece inspection reports, patrol inspection logs, and material change and machine cleaning records. Each document includes fields such as process parameters, raw material batch numbers, mold IDs, and test results. Data sources include resin batch property sheets, injection molding machine operating parameters, mold temperature controller data, manufacturing execution systems (MES), and dimensional and appearance test results. Data updates are triggered with each production batch, mold or material change, and each shift’s patrol inspection. There is no fixed update cycle, but updates are tightly tied to production schedules.
What constraints these characteristics impose during deployment and upgrade
Production data and documentation for this category are tightly tied to production schedules, and are multi-source and heterogeneous. They include real-time production metrics such as injection molding machine parameters and mold temperature data, as well as static documentation such as process cards and mold histories. During deployment, compatibility requirements for connecting to multiple systems must be addressed. Because data updates are triggered with each production batch, mold or material change, and each shift’s patrol inspection, storage configurations must reserve expansion space to handle sudden data increases. Upgrade processes must avoid interrupting real-time data synchronization, otherwise documentation for production links may be lost. Additionally, data errors can cause batch defects, mold damage, or even safety issues. During deployment, fault tolerance mechanisms must be configured to ensure abnormal data is not directly imported into the review workflow. This page is written based on FastGPT v4.17.0.
How to configure settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
MONGODB_URI | mongodb://fastgpt:password@mongodb:27017/fastgpt?authSource=admin | Supports storage needs for multi-source production data, and enables high-throughput document read/write operations |
REDIS_URL | redis://:password@redis:6379/0 | Caches frequently accessed process parameters and mold histories to reduce database load |
STORAGE_S3_ENDPOINT | http://192.168.1.200:9000 | Connects to local storage media as the document storage carrier, suitable for private deployment scenarios |
FE_DOMAIN | http://192.168.1.100:3000 or https://your-frp-domain.com | Adapts to private deployment access paths, supports normal access after public network penetration |
FILE_TOKEN_KEY | Randomly generated 32-bit string | Ensures security of document upload and access, preventing unauthorized access to production documentation |
Three common configuration mistakes
- Incorrect storage port when configuring
STORAGE_S3_ENDPOINT. For example, mistakenly using port 80 instead of the 9000 port of a local network-attached storage (NAS) device, which causes document upload failures and returns a 404 status code. This occurs because the actual service port of the local storage is not verified, and a generic default value is used directly. - Failing to synchronously update the
REDIS_URLenvironment variable in the docker-compose file during upgrades. This causes cached process parameters to expire, leading to old data in review results. This occurs because the binding relationship between cache configurations and production data is overlooked. - Not configuring
FE_DOMAINto the public network domain name after FRP penetration. This causes static resource loading failures during external access, and the interface cannot properly display review results. This occurs because internal network access addresses and public network penetration addresses are confused.
How to confirm configurations are correct
- Run the docker compose up command, check container runtime logs, and confirm there are no connection errors for configuration items such as
MONGODB_URIandREDIS_URL. - Upload an injection molding process card document, verify that the document can be stored normally and indexed correctly in the review workflow.
- Access the platform via the configured internal network or public network address, confirm that the interface loads normally and the document preview function operates without errors.
- Trigger a simulated document cross-review, confirm that the returned results include relevant fields for corresponding production data.
The values provided are common starting points and should be evaluated against local deployment samples.