What the data for this category looks like
This category covers liquid milk, yogurt, milk powder, and dairy ingredient processing enterprises. Core documents include raw milk acceptance records, standardized ingredient lists, pasteurization/UHT process records, Clean-in-Place (CIP) cleaning records, filling records, and reserved sample microbial test reports. Data sources include milk source testing equipment, Manufacturing Execution System (MES), homogenization and heat treatment equipment, online temperature and flow sensors, CIP systems, and Laboratory Information Management System (LIMS) laboratory management systems. Data updates are performed per single milk tank and single production batch. Online process parameters are pushed in real time, and test reports are synchronized upon batch completion. Data fields include tank number, batch number, test time, process parameter values, and operator identification. Each parameter is paired with industry-standard testing units.
What constraints do these characteristics impose on HTTP interfaces and external systems
Dairy processing data is strongly linked by tank number and batch number. Real-time pushed online process parameters require interfaces to support precise data retrieval by unique identifiers, to avoid resource waste from full-volume retrieval. Multiple system data sources require interfaces to adapt to different authentication rules. Interfaces must be compatible with authentication formats of various internal enterprise systems. Real-time data requirements mandate that interface latency be controlled within a reasonable range. Timeouts will lead to missing process parameter records and affect traceability efficiency. Single-batch data volume is manageable, but there is a need for batch retrieval. Interfaces must support limiting the volume of data returned per request to avoid overload.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
Authorization | Bearer {docking system API key} | Adapts to Bearer token authentication standards for enterprise systems such as LIMS and MES, ensuring interface access security |
variables | Bind tank number and batch number as global request variables | Matches the feature of dairy data being linked by tank or batch, enabling precise retrieval of records for the target batch |
responseData | Filter for total microbial count, fat content, and pasteurization temperature fields | Focuses on core process and test parameters of concern for quality traceability, reducing invalid data transmission |
| Request timeout time | 30 seconds | Matches the real-time push rhythm of online process parameters, avoiding data lag that affects traceability efficiency |
| Request retry count | 2 times | Addresses temporary network fluctuations in short-link scenarios for dairy processing, reducing the probability of single request failure |
| Single return data volume | No more than 500 records | Adapts to the conventional data scale of a single production batch, avoiding interface overload |
Three common mistakes
- Phenomenon: The
responseDatafield returned by the interface is empty. Cause: Data is not filtered by tank number or batch number, and no valid data for the target batch is found after retrieving full-volume historical records. - Phenomenon: The request returns a 504 timeout status code. Cause: The request timeout time is set too long, exceeding the real-time window for online device data push, leading to link backlog.
- Phenomenon: The interface returns mixed data across batches. Cause: Precise batch parameters are not bound via
variables, and using generic variables triggers full-volume data retrieval.
How to confirm that the configuration is correct
- Call the test interface of FastGPT v4.17.0, pass the
variablesparameter with a known valid tank number, and check whether the returnedresponseDataincludes core test and process parameters. - Simulate temporary network interruption and recovery, observe whether the interface triggers the retry mechanism, with no errors and complete returned data.
- Check whether the format of the
Authorizationheader meets the authentication requirements of the docking system, with no authentication failure log records. - Export the same-batch test report from the docking system, and compare each value with the
responseDatafield returned by the interface to confirm data matching.
The values given are common starting points and should be measured against the reader's own samples.