What data looks like for this category
Data sources for pulp and paper quality traceability include wood pulp and waste paper batches, DCS/QCS systems, paper machine online measurement equipment, laboratory testing, and energy and water treatment systems. Daily generated documents include pulp preparation sheets, beating records, paper machine operation logs, online quality curves, laboratory quality inspection reports, and sheet break and product change records. Data update frequencies are split into three categories: real-time, per shift, and per paper roll batch. Fields include pulp ratio parameters, paper machine operation parameters, grammage, moisture, thickness, defect types, and more. Most units follow physical measurement standards.
Constraints on HTTP interfaces and external systems
Data sources for this category are scattered, and update frequencies vary widely. Real-time data such as online quality curves requires interfaces to support high-frequency push. Documents at the per shift or per paper roll level are suitable for batch pulling. Multiple field types include physical quantity parameters, so interfaces must verify that field formats and unit requirements align. Cross-department collaboration needs require interfaces to connect multiple systems including material preparation, pulping, and quality management. Unified authentication must be implemented using the Authorization parameter. High-speed continuous production generates large per-roll data volumes, so interfaces must support chunked transmission. The recommended single chunk size is 800–1200 characters, which matches the single-data length of online quality curves.
Configuration settings
These configurations are based on FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
Authorization | Bearer {custom secret} | Meets cross-system cross-domain authentication requirements and complies with general industry interface specifications |
| Timeout | 600–1200 seconds | Covers the maximum time required for batch pulling of per shift records, to avoid mid-process disconnections |
responseData | Return in original field format | Retains original data units and precision, adapting to the high-precision needs of quality analysis |
variables | Bind paper machine ID and batch number as fixed parameters | Automatically associates full-link data for a single paper roll, reducing manual entry errors |
| Retry attempts | 3 | Addresses interface call failures caused by network fluctuations, without impacting production real-time processes |
| Batch pull limit | First 100 records | Balances data transmission volume and processing efficiency, adapting to per shift data scale |
Three common configuration mistakes
- Issue: CSV datasets created via HTTP interfaces do not match results generated in the platform interface. Cause: Field order for documents including pulp preparation sheets and beating records was not mapped correctly, leading to data alignment errors.
- Issue: Interface calls return status code 400, prompting unsupported request format. Cause: The request body was not transmitted in JSON format, or the
Authorizationparameter was not configured properly. - Issue: Interface calls time out, and real-time online quality curve data cannot be retrieved. Cause: The timeout duration was not adjusted to match high-frequency data pulling, or the single request data volume exceeded the threshold.
How to verify correct configuration
- Call the test interface with a single pulp preparation sheet record, check if the
responseDatareturned includes core information such as pulp ratio and batch number. - Simulate batch pulling of per shift paper machine operation records, verify if the number of returned records matches the actual generated record count, and adjust the batch pull limit to a reasonable range.
- Trigger a cross-system authentication request, confirm that laboratory report data can be accessed normally after including the
Authorizationparameter. - Simulate a network fluctuation scenario, check if the interface automatically reconnects according to the configured retry attempts, with no duplicate data submissions occurring.
The values provided are common starting points and should be measured against the reader's own samples.