What the data for this category looks like
Supplier and process quality audit for furniture and wood product manufacturing covers panel, solid wood, custom furniture, and door manufacturers. Daily processed documents include order breakdown drawings, cutting lists, edge banding and drilling programs, coating process documents, hardware material lists, assembly and packaging records, and other related materials. Data mainly comes from order design systems, panel and wood batch ledgers, CNC cutting and drilling equipment logs, ERP/MES systems, and moisture content testing equipment. Update frequencies cover per order, daily, and per material batch nodes. This category is driven primarily by custom orders. The number of panel components is large and must match on-site installation space dimensions. This differs from the fixed BOM production model used for standard home appliances.
Constraints on deployment and upgrade from these characteristics
The multi-source heterogeneous data sources, high-frequency update rhythm, and customized production characteristics of this category impose multiple constraints on FastGPT's deployment and upgrade process. First, mixed access of unstructured documents such as order breakdown drawings and CNC programs, and structured data such as ERP and equipment logs must be supported. Adaptable configurations for data storage and synchronization must be planned in advance during deployment. Second, the high-frequency updates per order, daily, and per material batch require adjustments to system concurrent connection and caching policies. This prevents service freezes caused by data synchronization overload. Third, the custom-order-driven characteristics of multiple panel components and multiple documents require reserving sufficient storage and computing resources during deployment. During upgrades, ensure that key production documents and audit records are not lost during data migration. Fourth, errors in the audit process directly affect production delivery. Relevant data verification rules must be configured during deployment. During upgrades, ensure data format compatibility between old and new versions.
How to set the configurations
This guide is compatible with FastGPT v4.17.0. The following configurations are formulated based on the parameter specifications of this version, combined with the business characteristics of furniture and wood product manufacturing.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
DB_MAX_LINK | 100–150 | Adapts to concurrent requirements of multi-source data synchronization, matches the high-frequency data access volume of panel batches, cutting lists, and similar materials |
MONGODB_URI | mongodb://username:password@host:27017/fastgpt_furniture | Used to store unstructured document data such as order breakdown drawings and assembly records, meets the document storage requirements of this category |
REDIS_URL | redis://:your_redis_password@redis_host:6379/0 | Caches frequently queried data such as panel moisture content and hardware material lists, reduces load pressure on the primary database |
FE_DOMAIN | https://furniture-audit.fastgpt.com | Configures the access path for the frontend page, ensures normal redirection for functions such as login and document upload |
STORAGE_S3_ENDPOINT | https://s3.cn-north-1.amazonaws.com.cn | Stores large-volume document files such as CNC programs and coating processes, adapts to the large-file storage requirements of this category |
Three common mistakes
- Phenomenon: Only the login module is displayed when opening the frontend interface, with no registration entry button. Cause: The
FE_DOMAINconfiguration does not correctly point to the root path of the frontend deployment, causing frontend routing loading exceptions and preventing registration-related components from rendering. - Phenomenon: All custom supplier audit applications cannot be viewed after upgrading from FastGPT v4.8.20 to v4.8.21. Cause: The
MONGODB_URIis configured to a new instance address and does not point to the original database, so the system fails to migrate historical application data. - Phenomenon: When importing cutting lists in batches, the upload progress fails halfway with a storage permission error prompt. Cause: The bucket permissions corresponding to
STORAGE_S3_ENDPOINTare not correctly configured, preventing large-volume documents from being uploaded normally.
How to confirm the configuration is correct
- Access the configured
FE_DOMAINaddress, confirm that the registration and login entrances are present on the page, and that the account creation and login processes can be completed normally. - Perform a database connection test, verify that the
MONGODB_URIandREDIS_URLconfigurations can establish normal connections, with no connection timeout or authentication failure errors. - Upload a small order breakdown drawing document, confirm that the document can be uploaded and stored normally to the configured object storage service, and that the upload record can be viewed in the system.
- Check the system logs, confirm that the concurrent connection count of
DB_MAX_LINKdoes not exceed the configured threshold, with no frequent connection disconnection or overload prompts.
The values given are common starting points and should be measured against the reader's own samples.