Data Profile for This Category
Daily data sources for the spinning and weaving category include raw fiber inspection reports, ERP systems, real-time data from spinning machines and looms, evenness testers, fabric inspection machine test results, and order specification documents. Data update frequency changes with production batches. New records are generated for each raw material batch, each shift’s production run, and each piece of fabric produced.
Typical documents include cotton blending lists, process setup sheets, equipment operation logs, yarn inspection forms, grey fabric inspection forms, and defect logs. Fields cover fiber fineness, spinning twist, loom speed, defect location, order piece length, and more. Units include tex (tex), revolutions per minute, meters, and others.
Constraints for HTTP Interfaces and External Systems
Scattered data sources and high update frequencies require interfaces to support multi-source data pulling and low-latency responses. This ensures alignment with real-time production rhythms. Diverse document structures require interfaces to support custom field mapping. This allows accurate integration of device and test data from different sources into process documents and exception reports.
Single-batch data volume fluctuates with production scale, so interfaces must support batch processing. Interfaces must also adapt to exported files from different test equipment to avoid data parsing failures. Some test equipment exports binary files, so interfaces must support parsing and converting this type of data.
Configuration Guidance
This guidance is based on FastGPT v4.17.0, adapted for HTTP interface integration in spinning and weaving scenarios.
| Config Item | Recommended Setting | Rationale |
|---|---|---|
Authorization | Fixed Bearer + platform-generated API key | Used for interface identity verification to prevent unauthorized access to production data |
variables | Predefined business field mapping, such as {"fiberGrade":"","twistRate":"","pieceNo":""} | Meets the requirements for transferring batching and process parameters in spinning and weaving |
responseData | Structured JSON format including defect type, process parameter, and test result fields | Matches the output format requirements of process documents and exception reports |
| Request timeout setting | 30–60 seconds | Adapts to the latency requirements of real-time device data pulling and avoids production wait timeouts |
| Batch request limit | Top 10 entries | Matches the single data processing scale per shift or per fabric piece and prevents interface overload |
| File upload size limit | 100–500 MB | Adapts to the size of original test data files exported by fabric inspection machines and evenness testers |
Common Misconfigurations
- Phenomenon: A parameter missing error is returned when calling the session interface, with a status code of 400. Cause: The
variablesfield is not configured correctly, and required business parameters such as fiber grade and spinning twist are not passed. - Phenomenon: A cross-origin error occurs after the frontend calls the interface directly. Cause: Allowed cross-origin domains are not configured on the platform, or cross-origin request specifications are not followed, resulting in interface request interception.
- Phenomenon: The interface returns an unsupported format error when uploading defect files exported by fabric inspection machines. Cause: Supported file types are not configured, and file content is not correctly mapped to the
responseDatafield.
How to Validate Correct Configuration
- Call the test interface, pass preset cotton blending parameters, and check if the returned process document includes correct fiber grade and batching ratio fields.
- Simulate uploading a defect record file exported by a fabric inspection machine, and confirm that the interface can parse the content and write it to the corresponding fields in the exception report.
- Call the interface after configuring the
Authorizationheader, and check that the return status code is 200 and no identity verification errors occur. - Set a reasonable timeout duration, pull 10 pieces of equipment operation data in batch, and confirm that the interface completes the response within the set time.
The values provided are common starting points and should be measured against the reader's own samples.