What data looks like for this category
Data sources include batch ledgers for wood pulp and waste paper, DCS and QCS control systems, on-paper machine measurement equipment, laboratory testing systems, energy and water treatment systems. Data update frequencies cover three categories: real-time, shift-based, and per-roll. Daily generated documents include pulp preparation sheets, beating records, paper machine operation logs, online quality curves, laboratory test reports, and sheet break and product change records. Data fields include pulp ratio parameters, beating degree values, sheet grammage, moisture content, and paper defect types. Grammage unit is g/㎡, beating degree unit is °SR.
What constraints these characteristics impose on HTTP interfaces and external systems
Data update frequencies cover real-time, shift-based, and per-roll. HTTP interfaces must adapt to different request cycles. Set short request intervals for real-time data. Pull shift-based and per-roll data on fixed schedules. Data sources are scattered. Interfaces must connect to multiple types of systems. Unify data formats to fit downstream audit workflows. Single data entry sizes vary. Response data for online quality curves and sheet break records is large. Interfaces must support variable-length requests and responses. Pulp and paper audit processes rely on precise field matching. Fields transmitted via interfaces must strictly match standard parameters for pulp preparation, beating, paper machine operation, and other links. Avoid missing or misaligned fields. In high-frequency update scenarios, interfaces must have stable concurrent processing capabilities to prevent data backlogs.
How to set up configurations
The following configurations are based on FastGPT v4.17.0.
| Configuration Item | Recommended Practice | Rationale |
|---|---|---|
Authorization | Bearer {system-assigned API key} | Adapts to authentication requirements of most external industrial systems, and ensures secure interface calls |
variables | Enter business identifiers such as pulp batch number, paper machine number | Used to pass dynamic business parameters in interface requests, matching data pull requirements across scenarios |
responseData | Return only core fields for pulp preparation sheets, beating records, and online quality curves | Reduces invalid data transmission and lowers interface response latency |
| Request timeout | 600 seconds | Adapts to transmission requirements for large-volume data such as online quality curves, preventing timeouts caused by large data volumes |
| Pull interval | Configure based on data update rhythm: set real-time data to 10-30 seconds, shift-based data to 8 hours | Matches data update frequencies across pulp and paper links, avoiding data omission or repeated pulls |
| Concurrency limit | Calibrate based on actual measurements | Adapts to data pull requirements of paper machine clusters of different scales, preventing system resource overload |
Three common mistakes
- Symptom: Interface calls return a 401 unauthorized error, or
Authorizationfield verification fails. Cause: The API key is not filled in according to the Bearer Token format, or the key has expired and not been updated. - Symptom: Pulled data fields do not match business requirements, and some core fields are empty. Cause: Core fields to return are not specified in
responseData, or correct business identifier parameters are not passed invariables. - Symptom: Interface calls time out, or response data is truncated. Cause: The request timeout is set too short and does not adapt to transmission requirements for large-volume data such as online quality curves, or the concurrency limit is set too high, leading to insufficient system resources.
How to confirm correct configuration
- Call the test interface, check if the returned
responseDataincludes preset core business fields, and verify that field names match business documents. - Simulate requests with different update rhythms, check if interface returned data matches business data for the corresponding cycle, with no duplicates or omissions.
- View system logs to confirm that
Authorizationauthentication passes, with no unauthorized error reports. - Adjust request parameters to verify that business identifiers in
variablescan correctly filter data for the corresponding batch or paper machine.
The values provided are common starting points and should be measured against the reader's own samples.