What the data for this category looks like
Data for this category primarily originates from orders and size charts, CAD patterns, fabric and accessory inspection equipment, hanging production systems, needle detectors, and customer sealed samples. Daily produced documents include process sheets, patterns, layout plans, cutting orders, first-piece sealed samples, process quality tables, and packaging size matching lists. Data updates follow the rhythm of each order, each style, and each batch. Fields include size, fabric batch, piece count, process quality inspection results, and more. There are no unified fixed units, and values adjust according to the corresponding documents or production links.
What constraints these characteristics impose on workflow orchestration
This category has many styles and strong seasonality. Pieces are irreversible and manual processes are intensive. Workflow orchestration must adapt to frequent style changes and temporary adjustments. The need for multi-document association requires workflows to support cross-data source calls for documents such as process sheets and layout plans. The variables configuration must be used to store temporary piece batch and size ratio information. The high frequency of data updates requires workflow node trigger logic to bind to real-time production nodes, avoiding expired fabric and accessory inspection data. At the same time, errors directly lead to customer rejection, so multiple link verification nodes must be added during orchestration. These nodes cover key steps such as size verification and color difference inspection. This page is written based on FastGPT v4.17.0.
How to set configurations
| Configuration Item | Recommended Approach | Basis for This Approach |
|---|---|---|
variables validity period | 12–24 hours | Matches the production cycle of each style and batch for this category, avoiding expired data interfering with subsequent audits |
| Node trigger rules | Trigger according to the process node bound to nodeId | Aligns with the production rhythm of the hanging production system, ensuring audit timing synchronizes with actual production |
| Form required fields | Piece number, fabric batch, first-piece sealed sample number | Covers core fields from process sheets and first-piece sealed samples, meeting audit traceability requirements |
| File upload limit | 1000 MB | Accommodates large-size production documents such as CAD patterns and layout plans |
| Historical record retention count | Top 6 entries | Adapts to the inquiry scenario of multi-layered question trees, avoiding information overload that affects audit efficiency |
| Node retry count | 3 times | Addresses temporary communication fluctuations from needle detectors and production systems, reducing manual intervention |
Three common mistakes
- Phenomenon: The historical records of the global variable
variablescannot be modified, and old style data remains in the audit process. Cause: The validity period rule forvariableswas not configured, and the default retention period is too long, leading to cross-batch data confusion. - Phenomenon: After uploading a CAD pattern or layout plan, the workflow node prompts that the file format is not supported. Cause: The upload whitelist for the corresponding file type was not set, only general image formats were opened, and CAD vector files were not covered.
- Phenomenon: The multi-layer process audit question tree has repeated questions, and users report redundant processes. Cause:
variableswere not configured to store collected information between nodes, leading to repeated requests for the same quality inspection data from users.
How to confirm the configuration is complete
- Trigger a simulated cutting process node, check whether the current batch's fabric batch and piece count information is correctly stored in
variables. - Upload a test CAD pattern file, confirm that the workflow node can normally read and associate it with the corresponding audit link.
- Start a simulated multi-layer audit process, confirm that collected information will not be repeatedly queried, and the historical record retention quantity meets expectations.
- Simulate a node communication failure scenario, confirm that the workflow will automatically attempt recovery according to the configured retry count.
The values given are common starting points and should be measured against the reader's own samples.